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Digital Execution Roadmap: Digital and Analytics Social Eminence 2.0

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Digital Execution Roadmap

Practitioner-led learnings from driving digital transformation for global enterprises

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The world was already inexorably moving towards digital. Recent events have accelerated our collective digital journey and ushered us into the era of digital business – where every company must become a technology company.

At HCL, we have helped thousands of enterprises leverage digital interventions to reimagine their business and how it delivers value. We are delighted to share these learnings here in the Digital Execution Roadmap portal, bringing you actionable and practitioner-led insights to navigate your digital-led business transformation journey.

Happy reading!

Anand Birje
Anand Birje

Anand Birje

Senior Corporate Vice President and Global Head, Digital Business,
HCL Technologies

Featured insights

Digital transformation is upending talent expectations

Social eminence June 11, 2021

Introduction

2020 has forced many organizations to take on faster, iterative, and more aggressive approaches to digital transformation. They did this to accommodate new market rules, take advantage of new opportunities, and offer enhanced customer experiences.

With these efforts, leaders are also realizing that bringing along their talent, and addressing talent challenges, has never been more critical to the success of their transformation efforts. According to HCL’s Digital Acceleration report  that surveyed 400+ business and IT decision-makers across the globe, lack of skills within the organization is one of the top three challenges in furthering digital transformation. Leaders are increasingly paying more attention to this aspect in their attempts of digital acceleration.

Digital transformation initiatives reveal growing talent gaps

Organization-wide digital transformation initiatives typically address challenges related to four key areas:

  • Disconnected parts: Siloed divisions and multiple instances of software systems and inconsistent data prevent financial visibility and transparency and delay business decisions
  • Lack of end-to-end execution: Fragmented and cumbersome business processes that prevent efficiencies and collaboration
  • Lack of agility: Difficult to integrate new acquisitions and pivot quickly toward new sources of revenue
  • Need/desire to reinvent customer experiences: Provide a unique, faster, and engaging customer experience across their products and services.

These operational challenges are typically reflected in the workforce and how employees perform. With time, companies may have attracted and rewarded employees that know how to adapt to the inefficiencies, develop workarounds, and optimize how to function in complex environments. As a result, employees may be less likely to want to reinvent, or challenge the current model, because they’ve learned to succeed and survive in it.

In addition, companies may not have invested over time in evolving skillsets and behaviors, blending in new approaches/perspectives through new hires, or recognized the growing gaps in their workforce. These different forces compound the workforce gaps and make digital transformation harder to plan, initiate, and execute successfully, leading to non-optimized customer experiences as well.

Finding and engaging the existing talent potential

But in these gaps, leaders can also recognize the talent promise and potential that lie in their organization. The same adaptability and flexibility that employees have demonstrated in adjusting to complex, convoluted processes, and interactions in their organization, demonstrate their potential for reimagining, reinventing, simplifying, or automating the work.

To engage the workforce in the transformation process, leaders can focus on three key actions:

  • Show early commitment and authenticity
    • Leaders must be willing to demonstrate early support and commitment to the upcoming digital transformation
    • Being inclusive, inviting people to early planning discussions, encouraging them to reimagine what the future could look like, with visible support, are techniques that can be used
    • Leaders must do so with authenticity and candor, outlining the boundaries of the exercise, and sharing with selected employees how long and arduous the journey may be
    • Often, early workshops to discuss current challenges and how to address them provide a great opportunity for employees to lean in and demonstrate their interest and potential; this is a great chance to find employees with the courage and mindset to create the future, and not protect the existing turfs, power, or status quo
  • Give an opportunity
    • While assembling their core team for the transformation, leaders have a crucial responsibility to provide both a shot and a challenge to selected employees
    • The role must be both a real chance to design the solution and a personal challenge to learn new skills or levels of responsibility
    • Challenging people positively (not threatening them) can help them stretch and contribute in the most compelling way
  • Surround the team with expertise and encouragement:
    • Employees want to be successful and empowered; they also want support and access to expertise when they need it
    • To complement the knowledge about the company’s ways of working, leaders must recognize where external expertise is needed and find ways to provide it in a way that makes the core team more powerful (not inadequate)
    • Choosing the right consulting partner, providing the right training, connecting with others who can share past transformation experiences are ways to empower the core team
    • Finally, leaders must remain engaged, present, and supportive to help their core teams hit their stride

Understanding and managing talent expectations

Throughout the digital acceleration life cycle, the entire company landscape may evolve, including talent and its expectations. Most organizations will experience attrition at key roles during the transformation.

Throughout the digital acceleration life cycle, the entire landscape of an organization may evolve, including talent and its expectations.

Leaders need to actively manage their team’s evolving expectations by:

  • Letting them experiment
    • Experimenting is an essential part of learning and also aligning as a team; successful core teams learn to trust each other and constantly evaluate how to get the work done
  • Creating situations where it’s okay to say “I need help”
    • If employees are challenged in their transformation roles, they’re bound to experience situations where they don’t have the answer
    • Allowing them to partner with others, sharing where they are struggling, and getting them the help, greatly maximizes their chances of success (and for the core team too)
  • Using the core team’s motivation for a better solution to drive the change
    • Core team members can imagine the new world/solution together and keep each other accountable on their commitments
    • It’s often the sum of the individual drives of wanting to build something better that generates the organizational momentum at scale
  • Rewarding and recognizing through bonuses, promotions, or role expansions
    • Digital transformations are long, arduous journeys, and careers don’t take a break through them
    • Leaders can work with their HR counterparts to reward, recognize, and help advance the careers of those who are contributing and demonstrating strong value
    • Mid-transformation promotions or expansion of roles are often great motivators and opportunities to celebrate accomplishments
  • Staying connected to the mission, purpose, and ambition of the transformation
    • One essential role of a leader is to continuously reconnect the core team and stakeholders to what the transformation is really about, thereby improving the business and customer experience
    • It provides a chance for each employee to reconnect their own expectations with the broader purpose of the transformation, and a way to re-energize for upcoming milestones
  • Finally, how you run the digital transformation program is a reflection of what you’ll achieve in the actual transformation 
    • If the objective is to drive toward a more simplified, connected, and agile way of working, practicing those behaviors during the transformation itself is crucial
    • It’s a great way to experiment/pilot and learn as we go
    • It’s also a powerful testimonial to a leader’s commitment to actual and sustainable change

Conclusion: The no-going back rule

Recognizing talent gaps, engaging and unleashing talent potential, and managing talent expectations are key factors in successfully executing digital transformation and offering better customer experiences.

There is one more lesson that is really important. Once employees have tasted empowerment, independence, and experimentation, this is how they will want to continue to work going forward. The challenges, trials, and hardships that they’ve gone through also make them tremendous, credible champions for future change. As leaders, you may have created a new generation of contributors, and they need to stay engaged to continue to help the company evolve.

The digital transformation will also likely have completely changed expectations and norms on managing talent, sometimes forcing other groups to look at their own talent in more proactive and engaging ways. That’s a great outcome, and a great opportunity to engage your talent to stay ahead in the digital transformation game.


Associate Vice President, Digital & Analytics

From stakeholders to transformers: engaging executives to drive success - part 2

Social eminence June 11, 2021

“From Stakeholders to Transformers: Engaging Executives to Drive Success” is a two-part article series that first explores and identifies what makes a transformer, and then provides actionable advice on how to create your own transformers to drive business transformation and establish an inspirational vision. In the first article of this series, the five key traits of a transformer were defined and explained.

Make transformation initiatives impactful enough to compel a stakeholder to step up into the role of a transformer.

So how do you get to transforming leaders? As I emphasized previously, transformers are MADE, not born.

Even if someone doesn’t match the exact skillset outlined in the previous article, there is still potential for them to become a powerful transformer for driving transformation. You can play a vital role in creating stakeholders to transformers by following this advice along your journey.

The five rules to follow when creating your own transformers:

  1. Develop a relationship before you need something

    Depending on a workplace’s culture, relationships can often be transactional and based on task completion rather than genuine connection. Instead of simply picking someone who you think would be a good change-maker and assigning them this role as a task or deliverable, invest in the relationship first. Share information with this individual, reach out to them regularly, and take the time to get to know them.

  2. Find what drives your transformer

    Everyone has different things that motivate them. Find what fuels your transformer and run with it. Is it information about your project? Do they care more about recognition and access to future opportunities? Analyze the landscape and invite them to key events, if that’s the case. Is it to see your project as a way to accomplish their own objective? Is it more about playing their role to achieve a larger purpose? Or is their key motivator something else entirely? Find out what drives them, what they care about, what resonates with them, and invest in that.

  3. Learn how to set and tell the story

    Keep in mind that every transformation is a story waiting to be told, and good stories have the following components:

    • A challenge to address- What business problem are you trying to fix?
    • A vision for something better- What is the successful outcome you’re trying to reach?
    • Key contributors for and against- Who is in your coalition of the willing? Who’s not and do you need to win them over?
    • A roadmap- What are the three to four key milestones?
    • A little bit of magic- What makes your project special? What will compel people to contribute?

    How are you going to make this business transformation initiative impactful enough to compel a stakeholder to step up into the role of transformer? Tell the story.

  4. Continue to make progress and provide value

    No matter what, an initiative needs to be making progress. Think of progress as your fuel; it’s what establishes your credibility and makes people pay attention.

  5. Create the opportunity for the transformer to step up

    The final, and arguably most important rule for this business transformation journey, is creating an opportunity for your transformer to step up into their role and have a clear inspirational vision. You’ve invested in the relationship, you’ve set the story, you’ve made progress, it’s time to step back and give your transformer the space they need to excel. This may involve additional efforts to prepare them and provide guidance, insight, and clarity.

Build a composite transformer.

Even if you follow all these rules and execute the journey with few flaws, it’s unlikely that you will find all the traits of a transformer in one single person. That’s okay! Find what you need and who can deliver it. Some stakeholders are better at vision, others at energy or coalition building. It helps to look for these traits, but oftentimes, different people will bring different things to a project.

Look around at work, who’s displaying the traits you need, who could be a transformer if you helped them?


Associate Vice President, Digital & Analytics

A distinct line between tech adoption and digital transformation

Social eminence June 11, 2021

Over the last few months, many organizations found themselves forced to make the switch to remote operations and adopt a slew of digital technologies across the business, as they attempted to navigate the sudden, COVID-19-induced reality of social-distancing and lockdowns. Amidst all these paradigm shifts and the overall digital revolution, it is important to understand that there is a distinct line between tech adoption and digital transformation in this digital economy.

At its core, digital transformation refers to the process of placing the end customer, and subsequently all the stakeholders across the value chain, at the center of a business process experience. It is an inclusive process where all the stakeholders across verticals are in alignment within a business model that delivers value by leveraging the latest advancements in digital technologies like AI, machine learning, cloud computing, and IoT, in tandem with the people that make up the organization, to create and drive customer-centric experiences.

Merely purchasing and implementing a software suite in response to a localized issue does not equate to digital transformation. Organizations must therefore consider two key points— recognizing and responding to the shifting trends in consumer behavior and avoiding siloed initiatives that target specific issues.

Organizations must recognize and respond to the shifting trends in consumer behaviour and avoiding siloed initiatives that target specific issues.

Are your strategies adapting to changing trends in consumer behavior and expectations?

If there is one place where COVID-19 has placed us ahead of ourselves, it is the rate at which people are adopting digital channels to various ends. The post-COVID-19 world has led to unexpectedly increased customer readiness toward trying new digital channels for interacting with businesses. In most sectors, at least a 50% increase in digital adoption is coming from new users, and this trend leading to increased digital operations is visible across geographies and industries.

Some sectors such as retail and entertainment are performing better than others, and newer models of AI and machine learning in emerging fields of telemedicine and online fitness programs are gaining traction too. Traditional sectors such as banks, which typically have a relatively higher resistance to digital technologies such as IoT and machine learning, are showing an increased rate of adoption as well. Top players in banking are going paperless across their business processes by using smart solutions that leverage the latest developments in tech to deliver frictionless experiences to their end customers. As a result, banks are reporting higher satisfaction, greater revenues, and capabilities for dynamic expansion with agility for a digital revolution. The trend is clear with both neo-banks like Chime, and established global players like Citigroup, who are reducing their physical footprint and focusing on digital channels, improving efficiency while simultaneously driving better customer experience. Such overarching strategic moves are good examples of digital transformation done right.

To take a second example from a different industry, automotive insurance offerings can be enhanced by building auto-crash detection capabilities, and the towing, assessments, and claims processes can be taken digital. This will not only lead to highly optimal operations but will also help drive higher customer satisfaction and improve returns.

Digital transformation helps companies drive changes strategically through an ongoing process where being receptive to changing consumer trends helps in the formulation of effective roadmaps. These roadmaps can then be used to build better value propositions by leveraging the right technological advancements, leading to all-round benefits.

Are your products in sync with the new reality?

When big organizations shift to the latest architectures and deploy cutting-edge solutions, they often anticipate that these changes will help create better value propositions. According to a report, 62% organizations are struggling to define the objectives and outcomes of digital transformation. While digital transformation does optimize existing processes, real transformation places the customer at the heart of this change. How is the shift to cloud enhancing the value proposition of your existing service and client management processes? Are your product offerings in line with the latest trends in consumer behavior, and is the marketing team leveraging the right channels? To be able to give the right answers to these questions, it is crucial to avoid siloed initiatives that solve singular challenges and correspond to teams or departments rather than the organization as a whole.

To leverage these questions to drive positive change, senior leadership must not only embed true ownership in product roles but also ensure that the product strategy is fine-tuned to tasks that negotiate portfolio offerings with concrete features in alignment with the current organizational strategy. For example, by leveraging cloud infrastructures with IoT and simple protocols for intelligent devices, companies operating in the home goods and services industry can realign their strategy to deliver products that add value to the customer in an increasingly home-based digital economy. The key here is to recognize the links that bridge the biggest gaps between the organizational strategy and its execution.

While digital adoption and remote work are enabling companies to function in a mildly coagulated COVID-19 economy, top players are differentiating themselves by transforming the core of their business models. For example, global fashion giant ZARA which led the digital revolution in the fast fashion industry recently announced its plans to invest another $1bn to enhance its digital operations by integrating their online store with physical stores. As a result, the company reported a 90% increase in online sales during the global lockdown. Business models might differ across industries, but the ability to deliver value digitally is rapidly becoming a hot ticket to claim a chunk of the digital economy.

In the coming months, an increasing number of companies will succeed in optimizing their businesses through the adoption of digital technologies. However, being shocked into tech adoption is a far cry from true digital transformation. Enterprises that wish to come out of the current situation stronger, and with long-lasting competitive advantages, will need to take a more thoughtful, cohesive approach. This should involve leveraging all-round digital transformation to deliver offerings that respond to the needs of today’s digital travelers, and build truly digital, forward-looking experiences for their employees and customers.


darren.doyle_324386's picture Darren Doyle June 02
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Associate Vice President - Digital Consulting, Digital & Analytics

From stakeholders to transformers: engaging executives to drive success - part 1

Social eminence June 11, 2021

“From Stakeholders to Transformers: Engaging Executives to Drive Success” is a two-part article series that first explores and identifies what makes a transformer, and then provides actionable advice on how to create your own transformers.

Research has found that the top driver of project success is having actively engaged executive sponsors, people I like to call “transformers.” Surprisingly, research also shows that less than two-thirds of projects have these executive sponsors. So why the disconnect?

Because too many executives aren’t taking the leap from stakeholder to transformer.

Whether they have assigned power or not, anyone who has a defined stake in the outcome of an initiative is considered a stakeholder. This individual has the opportunity to influence, advocate, or resist change, and they ultimately may determine whether a change will stick. Think of Rosa Parks refusing to leave her seat on the bus, for example; she had no explicit power other than to stay seated. Parks simply had a stake and by advocating for change, she influenced civil rights in America in a dramatic way.

Being a great stakeholder doesn’t require intimate knowledge of the solution or a lot of time, but it does require curiosity, perspective, and a willingness to trust. Put action to those characteristics, expand your skill set, hone in on those around you, and you’re on your way to becoming a transformer.

Transformers often are the catalysts, accelerators, and drivers of business transformation. They step up beyond what’s expected of a good stakeholder and make business transformation happen.

THE FIVE KEY TRAITS OF A TRANSFORMER

  1. Vision that inspires and engages others

    Oftentimes in a complex initiative, the end-goal may seem out of reach or even impossible. Transformers make the connection between the vision and the reality of what needs to happen to make it possible, and they communicate that in engaging ways. Without an inspirational vision, it can be incredibly difficult to motivate and compel others to do their part for the change. However, unless you can ground your vision into actionable steps and roles, the final product will remain only a figment of your imagination. Finding someone who can articulate and support an inspirational vision is essential to project success.

  2. Energy to work through obstacles

    Think of transformers as catalysts that provide the energy for the transformation to happen. Transformers do this in different ways: they can motivate the team, they can create urgency for a resolution, they can focus the light on a key aspect of the initiative, etc.

    I work with a CFO on an 80-million-dollar program who is excellent at finding energy in different situations. He sometimes refers to himself as the “flight attendant during a turbulent flight,” because he can calm people down, he understands that people take cues from him, and he also helps to guide the moment with his enthusiasm.

  3. Ability to walk in other people’s shoes

    The best transformers step out of their own role and live the change through the eyes of a different stakeholder. This is often simply referred to as empathy, but I think of it more so as “empathy-forward.” These transformers anticipate what the change will do from the point of view of the recipient, they force discussions early, they show by example, they know when to pull back and wait, and most importantly, they listen and appreciate other perspectives.

    There is a CIO at an insurance company I’ve worked with who is particularly adept at this. She asks questions about personal impact, asks about plans, and brings up the difficult questions early, not to force the resolution, but to create the conversation.

    The best transformers step out of their own role and live the change through the eyes of a different stakeholder

  4. Power to reinvent where needed

    The ability to know when to start over or find a workaround is essential when it comes to being a problem solver. Transformers understand that things might not always work out according to their plan, so they create the conditions for a meaningful discussion of the issues, and they give themselves and others permission to reinvent when it’s the best option.

  5. Coalition builder

    Throughout a project, transformers must set the stage for different stakeholders to align on a common set of facts and perceptions surrounding the change. This trait also involves knowing when to ask, to hold, or to push. Great coalition builders find the common threads between stakeholders to unite them and drive the business transformation.

So what is key to driving transformation ? Keep in mind, transformers are made, not born. Everyone has an initiative has an opportunity to go from being a stakeholder to a transformer. In the second article of this series, I will walk through five rules to guide you through the journey of building your own transformers.

Stay tuned for Part 2: Your Road to Creating Your Own Transformers.


Associate Vice President, Digital & Analytics

The AI frontier: driving reliable and stable IT operations

Social eminence June 11, 2021

In 2020, I came across an article that talked about how Artificial Intelligence (AI) is expected to be the new catalyst for software development. The article stated that artificial intelligence-powered software development tool providers had raised more than USD 700 million in just 12 months. And this was before COVID-19 compelled enterprises to undertake rapid digital transformation.

Of course, this move forward has been accompanied by an accelerated growth in artificial intelligence adoption. According to HCL’s Digital Acceleration report, artificial intelligence has catapulted to become one of the biggest drivers of technology investment for business and IT leaders globally.

AI’s Role in IT Operations

With the increasing adoption of the concepts of Site Reliability Engineering (SRE) in mainstream enterprises, automation is becoming more intrusive in IT operations. In this blog post, we shall explore the prevalence of AI and Machine Learning (ML) in application IT support, rather than in infrastructure support. I believe application IT support is a more complex problem to solve.

Let’s look at the three types of tickets such as service requests, incidents, and alerts that typically get created in IT operations and consider how AI and machine learning is used to handle each type.

Service Requests

Service requests handling has the most common use of AI/ML because Standard Operating Procedures (SOPs) can be created easily for such tickets. Once we have an SOP, Natural Language Processing (NLP)-based understanding and classification models with Robotic Process Automation (RPA) can enable automated resolution of these tickets unless authentication is required. In such cases, opsbots (chatbots) could be an alternative for self-service portals. Chatbots also bring an added advantage of helping visually challenged people.

Incidents

Incident handling can be categorized into three use cases: Recovery, resolution, and prevention. Let’s start with the first; where we look at AI and ML as it is used to facilitate rapid recovery in the aftermath of an incident.

Recovery

Today infrastructure as code, service mesh, containerization, and micro-services architecture are becoming the norm. Automated recovery using AI/ML ensures HA (high availability) in these applications or platforms. This might include, but is not limited to, autoscaling of applications based on model rules, automated mission control operations such as segmentation, backpressure, and bulkhead creation among others. These remediation techniques can be applied automatically through AI/ML. These are achieved by integrating simple pattern recognition models with relevant actions that are automatically executed.

Resolution

Incident resolution involves routing, triaging, and remediating the incident.

Routing: For any conventional incident resolution cycle, identifying and routing the ticket to the right person or resource to resolve the problem is a typical waste. This is when lean management principles are applied on IT operations value stream

AI optimizes the ticket allocation process by referencing data from all previous ticket allocations – from the service desk to the various operations teams. It also takes into consideration existing information of ticket hops that have taken place previously. With the ability to automatically categorize a ticket using natural language processing and ticket type, allocation to appropriate teams is seamless and fast. In certain cases, these tickets are assigned to the exact engineer whose code base was problematic. This was possible using AI/ML and, the ability to trace an error back to the actual engineers based on backward traceability established by matured CI/CD practices

I recall my experience of working with a global retail giant struggling with a very high number of rerouted tickets. They needed to reduce the number of rerouted tickets and cut back on the resolution time. We approached the rerouting issue by using previous rerouting data to train the AI/ML models. These learnings were then fed into a vectorization model to classify subsequent requests. This proved to be an effective solution. Through continuous learning, the AI model increased the first-time successful allocation rate from an initial 30-35% to 91% of total cases within three months.

Triaging: This step in the resolution process takes the maximum time and effort in IT operations. AI/ML is helping operators triage incidents faster through the use of conversational UI-driven intelligent KeDBs. This enable semantic searches, advances in observability which provide 360-degree view of the state of dependent systems or actors during the incident, and suggestions of possible remediations based on semantic patterns.

Remediating: Notification in triaging would most likely lead to suggestions on remediation as elicited above. In matured cases, such prescribed remediations agreed by the operator are also monitored to eventually enable straight-through-remediation or self-healing. This is still quite rare in application operations space where SOPs are hard to come by for incidents.

Prevention

So far, we have been exploring how AI models and ML can help in the resolution of an incident. But how do we prevent incidents before they can even occur?

Preemptive resolution of possible incidents is perhaps one of the most ambitious applications of AI models in IT operations. Achieving something like this depends on learning models that can identify the strongest indicators, causes of an incident risk and the degree of threat. When it comes to preventing incidents, AI and ML can be used to model and predict systems behavior based on a range of parameters that we can analyze.

AI and ML can be used to model and predict systems behavior based on a range of parameters that we can analyze.

Preemptive resolution is perhaps one of the most ambitious applications of AI in IT operations.

At HCL, we use three distinct models to predict systems behavior depending on the level of maturity of the available data. These are:

  • Probability distribution which focuses on internal two-dimensional data
  • Topological data analysis which focuses on internal multi-dimensional data
  • Game theory which focuses on both internal as well as external multi-dimensional data

These systems’ behavior models leverage historical data to predict if a problem could occur in a particular system. This prediction, in turn, can alert teams to take proactive measures or corrective actions in a dynamic scenario. These actions could include scaling infrastructure, changing the load balancing configuration, or simply introducing added layers of monitoring to prevent issues from even occurring.

When it comes to changes to an existing system, the operations team use AI/ML to assess system behavior objectively before signing-off for release — all done in an automated way. Two such recently used techniques were mutation testing and resilience engineering (chaos engineering).

Alerts

In contrast to traditional IT systems monitoring, AI and ML can be used to observe a system from a business-down perspective. AI/ML is used to correlate events from various monitoring tools and make an inference of business capability/sub-process behavior. Intelligent alert aggregation reduces the number of alert tickets. It also helps in identifying the real source of an alert and thereby reducing discovery, triage, and remediation time for such alerts. Another outcome of this approach is eliminating any unforced errors in ticket prioritization and allocation. This in turn, saves costs and allows the operations teams to focus on areas that need more immediate attention.

Conclusion

From detecting anomalies to suggesting ways to remediate them, AI and machine learning models that analyze data patterns in systems have shown the potential to streamline every phase of operations and development. They find their place in most of DevOps and SRE implementations. But as it has become evident in my experience, the value of any technology is only as good as its implementation. That will continue to be the key differentiator for effective AI and ML adoption in an enterprise.

By understanding the underlying datasets and adopting appropriate AI/ML models, we can realize benefits of at least 55% reduction in tickets, 45% reduction in operators, and 70% improvement in NPS scores for IT operations team.


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Agile in a time of a pandemic: how enterprises can scale development during the covid-19 crisis

Social eminence June 11, 2021

There is no doubt that the world is going through unprecedented times. As the COVID-19 pandemic rages across the globe, the humanitarian cost of this crisis is impossible to quantify. Even as the victim count continues to rise, there is hope of recovery on the horizon. Governments, organizations, and public institutions are aggressively taking steps to ensure the protection and health of their people. However, this has brought about major disruptions not only in people’s personal lives but also in their livelihoods.

Professionals who do not have to brave the frontlines as essential workers, are now quarantined, adjusting to work-from-home models. This shift towards a work-from-home or remote access model has presented every business and industry with its fair share of challenges such as optimizing distributed locations, network security compliance, and ensuring stable productivity, among others. But these are not new challenges and at HCL, we have already proven that we possess the capabilities to continue driving results in such scenarios.

Delivering Value Quickly with Agile

I am reminded of my experiences working on a highly complex and large-scale project with one of the largest international aircraft manufacturers. The key objective was very straightforward: to deliver value quickly. This involved improving the development approach to drive an accelerated time to market, reduce costs, streamline project flows, and minimize handover delays.

Achieving these outcomes required a diverse and highly skilled talent pool, and I believed co-locating would limit our ability to create a high performing Agile team. The client disagreed. I remained persistent in my advice and slowly, but surely, I was able to demonstrate how the perceived shortfalls of distributed development could be mitigated using an agile-at-scale approach. In the end, we were successful, and the project delivered value as planned.

A similar situation also arose while working with a major European bank that sought to launch a global platform that would help optimize costs and enhance sales opportunities. We advised them to scale their team across the globe with a distributed agile at scale approach. With our model derived out of practical experiences of executing distributed Agile at scale, we ensured that speed and quality did not suffer by focusing on the core bottleneck issues around people, process, and technology. Within six-weeks, the client was on-track and completely satisfied.

Abandoning Fears, Achieving Results

For those of us in solution development today, the conversation has turned to similar challenges. My point here is very simple – the world has already gone agile and embraced DevOps. Today, over 97% of organizations practice a variation of agile development methods even as the performance of DevOps teams continues to rise. According to the latest figures from the Accelerate State of DevOps 2019 report, the share of DevOps elite performers has increased from 7% to 20% over the 2018-19 period. This isn’t surprising since these approaches work at scale and across various process challenges such as remote working and work-from-home, making them more aspirational and necessary.

In the wake of the COVID-19 pandemic, Agile teams have changed radically, going from being co-located to being 100% remote. And while many organizations have struggled to maintain or ensure equivalent productivity levels in this situation, my experience has been very different. In fact, our initial analysis into the first 6-weeks of remote working shows us that remote teams are more productive than co-located teams. We analyzed these teams across our European region to determine what makes them an exception and to unravel their common best practices. I should note that our sample size was restricted to DevOps teams with full-stack developers with a period of measurement over 3 sprints (6-weeks) between program increments.

Having said that, here are the recommendations that I offer to any organization seeking to accelerate their agile practices during these times of crisis to get ahead of the curve and deliver true value:

  1. Product and cross-functional teams

    The onset of the COVID-19 pandemic has unveiled some very interesting results for how teams are adapting and performing. We are witnessing a higher degree of performance and greater probability of success from Product or Feature teams during this critical period. This is mainly due to their smaller size, smaller iterations, high performing T-Shaped engineers, cross-functional and self-organizing nature, higher prevalence of trust and transparency and the focus on working towards a common purpose. Every team’s dynamics are being tested during these times and Product/Feature teams have been found to be more resilient and sustainable.

  2. DevOps maturity

    We have also noticed a direct correlation between a team’s velocity and the maturity of their DevOps practices. Balanced maturity across the entirety of DevOps practices tends to yield greater TCO benefits in terms of speed, quality, and predictability than isolated maturity in specific practices. This includes aspects such as Continuous Integration, Continuous Deployment, Continuous Testing, Continuous Provisioning, Continuous Planning/Elaboration, and Continuous monitoring and Observability. Teams that drive Continuous Delivery are naturally more adept at delivering software at speed. Consequently, our recommendation has always been to mature the DevOps practices evenly across these areas to gain sustainable, long-term benefits. I have explored this point of view on scaling DevOps in my Scaling Agile blog series where I have called-out the principle of eliminating or automating hand-offs as being an effective approach for development teams.

  3. Empathy driven through good engineering practices

    I strongly believe that Servant Leadership is the best approach that is applicable across all roles. In engineering, we enact this by showcasing and encouraging empathy towards and amongst fellow engineers. In a work from home environment, the best way for engineers to exhibit empathy is by following good engineering practices. This requires them to adhere to established and consistent practices like clean code, Boy Scout’s rule, continuous code merges, frequent Pull Requests, nightly builds, good code commit comments, remote pairing, following the 12-factor app principle, using Gherkins language for story elaboration, codifying Definition of Ready (DoR), and Definition of Done (DoD), along with the memorialization of design evolution and decisions with tools like Figma, and the adoption of collaboration platforms. Following these requirements diligently and with discipline enables team members to demonstrate trust and empathize with each other. And of course, this leads to a naturally higher velocity and quality from the team.

    In a remote work environment, the best way for engineers to exhibit empathy is by following good engineering practices.

  4. Working agreements

    It is important to moderate working agreements between team members, especially with remote teams. These work from home agreements typically contain numerous steps, such as allocating time for sprint ceremonies, following a remote pairing structure and principle, daily schedule for synchronous communication, making time for code merges, adhering to the memorialization principle, enacting rotation policies, utilizing the Pomodoro technique agreement, leveraging the Eisenhower matrix agreement for prioritization, following coding guidelines and architecture principles, to name a few. Our advice for every remote working team is to define and adhere to the working agreement, moderated by the Agile coach.

  5. Multi-team and hierarchical collaboration and communication

    There are always apprehensions regarding reduced velocity and effectiveness when multiple teams come together to drive decisions. Just a few instances of such ceremonies include PI planning sessions, QBRs, lean budgeting session, program backlog prioritization sessions, user experience research and analysis, usability testing, and integration testing. The heavy usage of collaboration tools like video conferencing facility, sync/async communication platforms, messaging platforms, and memorialization tools have proven to be effective when it is excellently moderated by Agile coaches. The results can be further improved by leveraging business and process architecture techniques with domain driven methods like Wardley mapping. With the surge of remote work, we’ve also noted that hierarchical communication has been a critical challenge. But it can be resolved by implementing the organization hierarchy in all communication and collaboration platforms and enforcing role-based access controls for a more streamlined result.

  6. Measurement

    During these uncertain and volatile times, it’s important to drive confidence within a team and effectively measure the appropriate metrics. But this has been a challenge during the current COVID-19 pandemic. With managers lacking trust in their engineers to deliver, the problem is further compounded by the proliferation of remote working as the norm. In such scenarios, my suggestion has always to ‘leverage’, rather than create, data that can be measured automatically from the DevOps pipeline itself. By following this demarcated approach, we can stay honest, transparent, and boost trust within and between teams. Objective metrics like the number of code merges, number of pull requests, code churn rate, DORA metrics of Deployment frequency, lead time to change, change failure rate, and mean time to restore have proven to be an effective and accurate indication of team performance.

Many organizations facing the current crisis may be hesitant to stay the course with agile team. They may believe that distributed teams are less efficient, slower to handoff work, and more prone to misalignments. They may resist the progress already made and may even consider abandoning agile development models entirely. They may even think that ending product teams and reverting to large, batch-based project development models is the only way to ensure survival. This would be a mistake.

While it is not unusual to experience uncertainty during these times, moving backwards is not the answer. It is easy to call out instances where distributed teams have been inefficient and co-location has been the only pathway to productivity. But this has only been the case because most organizations have not advanced and scaled their agile development practices adequately. And it does not take a pandemic to prove this to be true as experienced by all our FENIX customers who have either seen their velocities stabilize or increase over time.

In fact, now is the time, when businesses are trapped in a forced distributed framework that we can truly unleash the full potential of agile and take it to scale. But this is only possible if we leverage all the best practices at our disposal and ensure clear communication and transparency with business. Agile at scale requires teams to be adaptive and responsive to change. But this response can only be assured if it is supported with the right tooling, engineering practices, best-of-breed engineers and fail-fast as an approach with shorter iterative processes.


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Unleashing "No-touch" asset integrity management for the upstream oil and gas industry

Social eminence June 11, 2021

Unmanned production platforms can help O&G companies boost efficiency, safety, and cost-effectiveness and prepare for the new normal. 

Ever since the world's first completely automated, unmanned, and remotely operated oil and gas platform became operational in 2019, digitalization has emerged as a strategic priority across industry boardrooms. The Oseberg Vestflanken H platform comes with the promise of driving significant business outcomes in terms of cost, productivity, and employee health and safety, signaling the beginning of an era of digitalization and digital transformation and the end of an era of large crews working on offshore platforms. The paradigm shift to digital solutions and cognitive technologies such as augmented reality is especially relevant in the current, pandemic-struck reality, where social distancing, contactless operations, and automation comprise the new strategic mandate.

Digitalization is essential to enable actionable intelligence and a proactive operations approach.

How does this new reality affect asset integrity management (AIM)? Assets on offshore rigs and vessels such as pipes and tanks require thorough inspection, maintenance, and repairs regularly to ensure they continue to perform as per expectations. Oil and gas majors also rely on AIM programs to track asset deterioration due to corrosion and structural damage. Traditionally, human intervention has been key to the success of any AIM program. However, with the proliferation of IIoT, augmented reality, cognitive technologies, and advancements in sensor and communication technology, is the oil and gas industry ready for digital transformation through a 'no-touch' approach to AIM? The answer is: Slowly. But it's coming.

Why change?

The current situation with global lockdown in place has put the oil and gas industry in a tight spot. The U.S. diesel margins are currently at USD 11 a barrel, the lowest seasonally in the last decade. As margins shrink and demand tapers, the most obvious way forward to ensure profitability would be to cut unnecessary costs. The launch of Oseberg H hammers that point home as the platform cost 20 percent less than expected and has been built to ensure that oil production costs stay below USD 20 a barrel over the next 22 years. The idea was to build a platform with simplification at its core, minimizing capital expenditure, and leveraging smart automation to reduce operating expenses over time.

The U.S. diesel margins are currently at USD 11 a barrel, the lowest seasonally in the last decade.

Profitability is also closely linked with asset uptime. However, asset operators in the petrochemical industry are faced with aging assets that may lead to unprecedented downtime as a result of unnoticed material cracks and corrosion. The problem is compounded when incremental changes are made to the asset design, making it difficult to keep track of its structural integrity. There is also a lack of skilled resources in the space due to technology upgrades over the years and scarcity of new talent. With oil and gas companies relying heavily on human resources, a retiring workforce could result in business continuity challenges necessitates the adoption of a holistic, digital-first solution for AIM.  

From an organizational productivity point of view as well, paper-based processes, excel-based spreadsheets, and monthly reporting cycles are no longer sustainable. With thousands of physical assets – pipelines, plants, facilities, and equipment – getting connected to the internet, these legacy workflows cannot keep up with the amount of operational data being generated and are not conducive to providing real-time visibility into critical production processes. The need of the hour is to enable intelligent analytics and enterprise mobility to empower the operator, and in turn, reduce maintenance effort and cost by having a data-driven preventive maintenance strategy in place.

Further, there has been a call for bolstering employee health and safety measures in the upstream oil and gas industry. And the implementation of automated, remote AIM solutions will be a step in the right direction, allowing operators to monitor assets safely from onshore facilities.

Digital solutions for asset integrity management

Assets in the upstream oil and gas industry, such as storage tanks, pumping stations, filter skids, emergency shutdown devices, and wellheads are a part of a complex network of equipment. Moreover, not all equipment is fixed. Some parts are regularly moved from one location to another, making inspection planning an arduous task. That means there are too many moving parts and having a centralized view of asset performance is key to ensuring smooth production operations. That considered, digitalization via digital solutions and cognitive technologies such as augmented reality, are a prerequisite to enable actionable intelligence and transition to a proactive approach to maintenance operations. Oil and gas companies looking to drive production in a cost-effective need to minimize the possibility of unplanned outages, and there isn't an alternative other than predictive maintenance. Time-based inspection planning is dated and needs to be replaced with risk-based inspection planning, which is impossible without being able to analyze real-time, accurate asset data.

Oil and gas companies can leverage a range of technology solutions to usher in holistic digitalization and enhance their AIM capabilities, starting with:

  • Mobile technology: Streamline maintenance operations by providing operators with access to real-time data from oilfield sensor networks and Supervisory Control and Data Acquisition (SCADA) systems. Boost collaboration and communication among operators and field workers and reduce manual effort spent on data entry. Using augmented reality, guide field workers through the oilfield and assist with inspection and overhaul, reducing mean time to repair. 
  • Inspection data management (IDM): Migrate all legacy data to a digital and reliable IDM database and put in place standard processes to collect, populate, and analyze new asset data digitally within the IDM software. The software will serve as a single platform to manage all equipment types owned by the organization and provide up-to-date data for powering risk-based inspection.
  • Global Positioning System (GPS): Know where all your fixed and rotating assets are at all times, and save time and effort spent on tracking their movement or locating the equipment at the time of inspection.
  • Integrity Operating Windows (IOWs): Keep track of operating conditions in near real-time with early alert notification and take immediate corrective action to mitigate downtime risk.
  • Risk-Based Inspection (RBI): Build risk models that consume real-time asset data to help produce smart inspection schedules and allocate resources accordingly while delivering maximum efficiency, efficacy, and safety.

By accelerating digital transformation and ensuring the digital robustness of their AIM environment, oil and gas companies would be able to redeploy scarce financial and human resources effectively, helping them achieve their business objectives and thrive in today's VUCA world.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Customer engagement will drive travel & hospitality renaissance in a post-covid world

Social eminence June 11, 2021

Travel & Hospitality is arguably one of the worst hit industries by the COVID-19 pandemic. According to the World Travel and Tourism Council (WTTC), the pandemic has put around 75 million jobs at risk, while the loss in GDP for the sector is expected to surpass USD 2.1 trillion. At one point, nearly 96% of global destinations had imposed some form of travel restrictions, shutting off the influx of travelers. Sub-sectors have also been impacted severely: Airlines with capacity reductions of 70-80%, hotels with vacancy rates of 80%, and cruise lines, which became hotspots for infections, halting their services across the globe.

When seen from a value-chain perspective, the crisis appears to be even more devastating. The demand side has witnessed a significant drop in both new and advanced bookings, thanks to travel restrictions and the general environment of caution and anxiety around travel. This has also led to a high number of cancellations and refund requests, further leaching revenue. On the supply side, business owners now find themselves with a substantial amount of unused inventory, leading to dramatic schedule reductions and removal of service capacity. Downstream suppliers have been privy to the cascading effects of these losses and find their revenue streams choked off as well.

With the pandemic showing no signs of slowing down, the near future is going to be tough for the industry. Even if scientists miraculously find a cure within the next few months, public paranoia around travel and public venues will be at an all-time high.

To its credit, this isn’t the first time the industry has been delivered a harsh blow and survived to tell the tale. After the attacks of 9/11 and during the 2008 financial meltdown, consumers aggressively pulled back on discretionary spending, cancelation of planned travel, and businesses tightened their grip on corporate travel expense accounts. But the industry found ways to pull a renaissance of sorts by rethinking their operating models to emerge stronger.

The key to this resurgence lies in customer engagement, customer experience management, and process and business model reinvention in a manner that considers the ground realities of the post-COVID world. In the months, and maybe even years, that follow, the travel and hospitality sector will have to fight to win back their customers’ confidence and assure them that it is perfectly safe to leave their homes.

The Evolution of Customer Engagement:

According to a research by Preferred Hotels and Resorts, more than 50% of respondents worldwide stated that they will book a trip in 2020 as soon as the travel restrictions and lockdowns are lifted. The research further revealed that 75% of the respondents intend to travel with family. If things go well, most experts predict that the travel and hospitality sector will start gradual recuperation by the end of 2020.

However, organizations that would survive and thrive must consider the temporary and permanent behavioral changes among customers brought about by the current crises. These changes will play a major role and possibly define customer behavior and customer expectations in the days to come. Consumers will have two priorities when they travel post-COVID:cost-effectiveness, and health and safety. In a sentence, low-cost travel that assures a certain quality of hygiene, and promotes social distancing practices and norms, will do well.

For brands, building the two-fold image of being safe and economical will require innovations in the areas of self-service, social distancing, touchless interactions, and expanded digital content. Simultaneously, travel and hospitality players will also need to focus on building adaptable, flexible, and resilient processes and platforms that underpin effective customer experience management. This will also include providing customers with a means to interact with the brand from anywhere at any time, and facilitating a human experience, without necessitating close contact with humans.

For brands, building the twofold image of being safe and economical will require many innovations

Technology as a Customer Engagement and CX-enabler:

The travel and hospitality ecosystem is changing irreversibly. The industry, today, should look at this crisis as an opportunity to reassess their digital strategy. In the wake of the COVID-19 chaos, it is quite evident that consumers' perception of experience and engagement will have been molded by the current crisis. However, digital transformation around the key tenets of CX and customer engagement will be a key differentiator in this highly competitive market.

We are likely to see significant investments in the short/medium term on analytics that will enable the industry to conduct travel routes analysis and optimization for cost elements, and marry this information with external inputs such as route specific trends, competitive data, etc., to intelligently predict and fulfil demand. This will be complemented with a focus in the short- and long-term on business restoration planning by managing the constraints around demand, costs, staffing, and financial considerations. Journey maps of different segments of travelers will also need to be reexamined and reimagined, to drive maximum business value.

Going forward, contactless intelligent operations, large-scale automation, and initiatives related to customer safety and care, such as contact tracing, will all be part of the key digital themes dominating the travel and hospital industry.

Here are just some of the ways in which technology can enable them:

  • Analytics to map end-to-end customer journeys

    The travel and hospitality industry generates a massive amount of data across multiple channels and platforms. These include customer research, planning, price comparisons, actual bookings and reservations, itineraries, fare charts, enquiries, and customer feedback. Incumbents and new entrants alike can explore the use of big data analytics to harness this information about the customer journey and draw insights that can help them deliver more targeted services, better pricing strategies, and personalized travel experiences. Of course, data analytics tools will only serve the purpose if users are assured that their data is secure.

  • Facial recognition for touchless operations

    In a post-COVID-19 scenario, travel companies can leverage high-end technology such as facial recognition to build touchless operations. Instead of having customers wait in a long queue at check-in desks at hotels or airports, companies can use facial recognition software to scan guests and shorten lead times as well as ensure adherence to social-distancing practices. In 2018, a joint venture between the Alibaba Group and Marriott International announced that it was testing facial check-in technology, so, clearly, the technology is already being explored.

  • Artificial Intelligence and chat bots for smart rooms

    For the last few years, AI in the travel and hospitality sector is directly responsible for how people search and book accommodation and transport. Today, it is poised to drive even greater change. One great example of this is an AI smart-room solution developed by a leading hotel chain. Unlike conventional guest rooms, the AI-enabled rooms come with state-of-the-art voice control technology that delivers a more natural human-computer interactive experience. Such technology, when integrated with IoT, can open endless possibilities in hygiene management and personalized service delivery.

  • Robots as the new housekeeping staff

    Robots can ensure service continuity for hotels struggling with staff shortages caused by COVID-19. From cleaning rooms and managing guest luggage, to handling front-desk bookings and customer queries, robots can do it all. In the coming days, robots could well become an increasingly important part of the travel and hospitality value chain in a world where consumers will prefer touchless travel.

The Road to a New Normal is Paved with Digital:

As organizations in the travel and hospitality sector plan a recovery, they will need to tread carefully. Customers moving out of their homes or cities for the first time in months are likely to be overly cautious and have exacting standards. Old brand loyalties and affiliations will take a back seat to companies than can prove themselves fully equipped to tackle the challenges of COVID-19, and a misstep can have far-reaching consequences.

Planned application of digital technologies can help brands optimize costs, forecast and fulfill demand, plan for contingencies, and deliver exceptional experiences that are above and beyond customer expectations. Brands that manage this will find themselves retaining, as well as winning new customers and brand ambassadors.

In these dark days, I often recollect the words of Barbara Brown Taylor. "I have learned things in the dark that I could never have learned in the light, things that have saved my life over and over again, so that there is really only one logical conclusion. I need darkness as much as I need light." As the industry moves ahead, incumbents and new entrant in the T&H industry must heed the lessons from the current situation and prepare themselves for the possibilities, challenges, and necessary innovations demanded by the brave new world.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Are you resilient? Four pandemic-driven take-aways on managing change

Social eminence June 11, 2021

Like most, my life and universe have been directly disrupted by the COVID-19 pandemic. The impact on families, jobs, teams, roles, finances, and the economy are immense, and the fallout from the crisis has only just started making its effects felt. In real time, COVID-19 has transformed human behavior, interactions, and the rules of engagement at the workplace, making remote work and change management paramount.

This crisis is also providing brand new insights into how people can adapt at scale and speed, and with remarkable efficiency and resilience, especially with remote work. That, incidentally, is also my holy grail as a change management professional.

Resilience is typically defined as “the capacity to recover quickly from difficulties, or to spring back into shape.” In the field of change management, resilience is the ability of an individual or a workforce to seamlessly shift and adapt to a challenging new environment, job, or set of circumstances. Creating and engaging resilience is essential in driving change management efforts. But resilience is also incredibly hard to engage. From my observations of the past few weeks, I have captured four key lessons on what the current crisis is teaching us about resilience.

Lesson 1: Resilience is experience-based

Our ability to deal with the new rules or the “new normal” is directly connected to how we are experiencing the impact of the virus. If we or a close family member is sick, our emotional and rational experiences will be dramatically different from someone with no direct “exposure” to the impact of the virus. And the more this happens, the harder it would be to find a common ground to discuss how we can sustain change through astute change management. The more we push one opinion, the more the other side would reject it.

The takeaway for organizations is that they need to establish a foundational understanding of the current pains/issues and a course of action that will address them, before they can ask their workforce to adjust and change.

Organizations need to establish a common ground of current issues and a course of action to address them.

Lesson 2: Crises provide short windows to engage resilience at scale

Early on, when the pandemic was growing dramatically by the day, most people accepted or even embraced new rules for quarantining, shopping, and social distancing. Global companies shifted hundreds of thousands of employees to remote work to continue serving their clients. Small businesses adjusted too, creating new revenue workstreams when traditional ones were no longer feasible or available. What I found most telling was the willingness and speed at which most of us adjusted. The mobilization around a common goal (“flatten the curve,” for example) created a giant wave of immediate change.

Most organizations have thus shown that they can dynamically adjust, at speed and quite effectively, when the mobilization is taking place around a common rationale/story that is compelling and strong enough. While the window for collective mobilization is limited, organizations who rally around a common, collective urgency can change incredibly quickly.

Lesson 3: Collective engagement and commitment drive better individual resilience

Resilience is a very personal and individual trait. But today’s crisis also shows how people are using collective engagement and commitment to sustain their own resilience and fortitude. Think of the workers in healthcare, food/delivery services, education, public services, and many other sectors who find the strength to continue forward. For some, the motivation may be money-related, but it also comes from the value that they deliver to the community and to their families, and because of the commitments they’ve made. They are encouraged and supported by others to continue to push through and deliver essential services to the rest of us. Every day, we see new tributes to the “frontline workers,” and to those that have had to adjust to cancelled graduations, weddings, sports competitions, and so many more events. As a community, our recognition of the hardship and sacrifices becomes fuel for resilience.

The key takeaway here is that while change is inherently an individual process, the collective engagement of peers, managers, colleagues, and leaders can dramatically raise one’s own ability to change and one’s capacity for resilience.

Lesson 4: Sustaining resilience is both about necessity and compelling goals

Early on in a crisis, compliance can take center stage—we adjust to what authorities tell us to do, we modify our own behaviors because we’re either told, or strongly encouraged in the face of limited information. But sustained change and resilience ultimately need to be connected to a compelling, ambitious goal that can keep us going—flatten the curve, reduce deaths, find a vaccine, etc.

Ultimately, our resilience comes from our ability to translate a macro goal into a personal, meaningful one—protect our close ones, help our community, support others. If that connection between the bigger goal and the more personal one doesn’t exist, resilience falters.

For organizations, the lesson is that compliance is not fuel for real change and is often a dangerous illusion that leaders can misinterpret for engagement. Successfully mobilizing workforces for change requires a connection between the ambitious, collective objective and the personal, meaningful one. Resilience is about continuously answering the question “Why or for what/whom am I doing this?”

As I write this, our way out of the crisis remains unclear—how long will it take, how many more people will be affected, what radically different behaviors may become the new normal? But what is becoming more and more evident is that our collective and individual resilience, and how we engage it, will dramatically impact our ultimate success and what we learn from this crisis. As a change management practitioner, I remain unabashedly optimistic. By raising self-awareness and engaging our own resilience, we’re much more likely to succeed in creating and driving the sustainable change that we need.


Associate Vice President, Digital & Analytics

The tale of retail: preparing for a post-covid world

Social eminence June 11, 2021

The COVID-19 outbreak has forced enterprises to revisit, and relook at, their existing operational and business models. The rapid spread of the novel coronavirus (SARS-CoV-2) has prompted national and international regulatory authorities to restrict transportation and enforce nation-wide, lockdown measures. As a result, much like the Chinese city of Wuhan, many major global manufacturing hubs have either been completely shut down or have had their operations significantly reduced.

As expected, these restrictions have had a significant impact on supply chains. While every business relies on supply chains in one form or the other, the degree of reliance differs. As we tread steadily into a future of contingencies, some industries need a closer look in terms of the impact and adjustments. In this article, I will be focusing on retail as an industry segment will examine the impact and implications of COVID-19 for businesses operating in this domain.

Retail’s Challenges in a COVID-19 World

The World Trade Organization (WTO) expects global merchandise trade to decline by as much as 32% in 2020 due to the direct impact and fallouts from COVID-19. With the epicenter shifting toward major economies such as Europe and the US, the chances of a full recovery in 2021 are uncertain. The shifting dynamics of socio-economic interactions have also created an unexpected rift in supply and demand patterns, one of the many retail challenges in this scenario. As a result, there have been simultaneous supply and demand shocks across the retail sector. These shocks are expected to slow down the economy further.

Global merchandise trade is expected to fall by 32% in 2020 due to COVID-19.

In regions most affected by the spread of the virus, dubbed as ‘red zones,’ almost every retail outlet, barring grocery stores and pharmacies, has had to cease operations. Even in areas that are moderately and lightly impacted, there has been a steep drop in purchase volume from physical outlets. Most of the world’s quintessential brands such as Macy’s, Kohl’s, Apple, Urban Outfitter, and others, have acted upon government directives or company-level mandates to protect customers and employees and have shut down their retail outlets, globally. Many of these brands have announced indefinite lockdowns until further notice. Several other brands, such as Ralph Lauren, while announcing resumption of services from their virtual stores, continue to struggle with delivery challenges.

The impact is clearly visible across retail stock as well: L Brands, the parent company of iconic brands such as Victoria's Secret and Bath & Body Works, is down almost 50% year-over-year, despite strong cash reserves of over $2 billion.

Moreover, the state of uncertainty that exists around the length of the confinement period has shifted consumer interest away from and toward certain product categories across the retail industry. For instance, while the fresh food category has witnessed a sudden drop in demand, food products with longer shelf life have recorded a spike in purchases. This trend has created a lopsided sales and demand life cycle in the retail industry, defined by a marked fluctuation in demand.

While brick-and-mortar stores have taken a hit in terms of sales and demand, the effect on e-commerce has followed a different trajectory. Self-isolation and local quarantine measures have significantly increased e-commerce sales. As a result, many e-commerce providers are struggling to meet the massive influx of traffic and demand. This has, in turn, significantly impacted product life cycle management. Of course, this increase is not distributed evenly and is focused across a few categories reflecting some of the trends witnessed in brick-and-mortar retail.

The pattern of what is in demand in e-commerce has changed with a spike in the sale of essentials such as F&B items with long shelf-life, and healthcare products. A similar increase is visible for categories such as gaming and entertainment, as consumers act upon the realization that the current status quo is likely to persist for the next few weeks or months. On the other hand, categories such as apparel and luxury items have suffered as people are less inclined to make such purchases in these turbulent times. According to a Vogue Business estimate, luxury brands may lose up to €10 billion in profits in 2020, and start back on the long path to recovery only by the beginning of next year.

However, irrespective of the category, delivery of physical products is proving to be a major challenge due to the tougher movement measures implemented by governments over the last few weeks, severely restricting courier movement.

The uncertainty around sales and demand has given rise to several other challenges in the retail sector. On the inventory side, there is a dilemma in strategy formulation at the product and service level causing dramatic understocking and overstocking situations. As a result, CDCs are stretched to their maximum capacity and retail players face financial repercussions in the form of overinvestment or loss in revenue.

With global supply chains coming to an abrupt halt, businesses have had to adopt ad hoc supplier matrices to mitigate risks. This has led to retail companies facing numerous adversities on the sourcing and ordering front such as dealing with the uncertainties of makeshift replacements, and unpredictably longer lead times. Subsequently, businesses have had to sacrifice on supply chain visibility, leading to massive inconsistencies in operational data.

These challenges, combined with the lack of effective scenario planning, have given rise to governance issues. As a result, businesses are engaged in an uphill struggle to establish a collaborative environment that promotes business continuity and unfaltering customer experience. At the same time, they need to deal with confusion and lack of direction from the top, stemming from the absence of strong contingency and business continuity plans.

Developing a Course of Responsive Action

The COVID-19 pandemic has presented retailers with a test of resilience. Even beyond the pandemic, supply chains have undergone massive changes in the last decade, becoming more complex and globalized. The need for thoroughly redesigned operational models is, therefore, not new in the retail sector. However, COVID-19 has forced businesses into fast-tracking the entire transformation, and retail, as an industry, can be expected to undergo a major paradigm shift comparable to how 2008 transformed the financial and real estate markets, or how 9/11 transformed the travel industry.

In the short term, businesses will need to prioritize developing a completely Agile operational and cultural environment. This includes implementing a SWOT team to enable quick decision-making to track the business impact of the outbreak. This will allow them to monitor and rapidly react to both macro and micro factors. Additionally, they will need to critically analyze product launches and discontinuations. Lastly, they will need to abstract and act on crucial learnings from the ongoing crisis such as prioritizing the e-commerce supply chain while putting all planned commercial activities on hold.

In the midterm, we expect a growing focus on leveraging the lessons learned from the impact of the current pandemic to tackle risk. Retailers will also need to develop models that can forecast store re-openings and planned commercial activities. As the situation evolves, businesses will need to continue monitoring market dynamics at the macro and micro levels. Finally, as the crisis starts to fade, businesses will have their work cut out as they normalize supply chain decisions, renegotiate with suppliers, revisit market and product expansion plans, and redefine budget and sales targets.

While the short- and mid-term targets will be crucial in developing the foundations for proactive resilience, it is through long-term measures that retailers can prepare for a post-COVID-19 world and build a truly pandemic-proof, resilient organization. To achieve that, organizations need to take a planned approach to address the opportunities offered by this “new normal.” This will involve a greater emphasis on strategic sourcing and network planning, including integrating and creating visibility into end-to-end supply chain functions, focusing on agility and flexibility, strengthening disaster management, and finally digitalizing the entire supply chain.

This blog was also published in ET Insights.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Next steps: revisiting global healthcare in a post-covid world

Social eminence June 11, 2021

The impact of the COVID-19 pandemic is being felt across industries, heralding the onset of clear and irreversible changes to come. While BAU activities have slowed down or stopped for many industries, healthcare services is at more strain than ever before. Despite the full backing of governments and communities, public and private healthcare systems are fighting an uphill battle against a largely unknown enemy, while also coping with lack of adequate personnel and resources. And unlike other domains, lives hang in the balance.

As dedicated healthcare professionals adapt to meet these ever-changing challenges, it is important to constantly re-evaluate the current position of global healthcare services from a technology perspective—not just to plug the gaps and discover and implement improvements right now, but also to build significantly enhanced healthcare roadmaps for the future.

Re-evaluate global healthcare services with digital technologies in the COVID1-19 era for an enhanced future roadmap

In this article, we will discuss the key steps healthcare providers and enablers such as the government, need to take and promote to enhance their preparedness for crises situations such as COVID-19, from a technology and process perspective.

An Interconnected Healthcare Network

Technology already plays a major role as far as healthcare services is concerned. In fact, one could argue that it is one of the major differentiators between today’s national and global healthcare systems, and localized systems that existed earlier—whether it is collaborative research and real-time sharing of data across the globe, or the personal interconnected devices critical to providing real-time data in densely populated areas. We are taking rapid steps to take this partnership further with advanced analytics in population health management (PHM) platforms being implemented for various demographics.

Several countries have already taken a few decisive steps in this direction, further accelerated by the COVID-19 pandemic. For instance, in Germany, lifting restrictions on remote consultations has significantly improved connection between patients and doctors. Other countries such as Australia have also invested in technology-led healthcare, through ambitious plans for blockchain adoption in the near future. Without question, building a truly digital healthcare system is going to be tough, but this change will bring benefits across the value chain.

Take the US, for example. The digital development accelerated by the COVID-19 pandemic will have far reaching effects across policies for the three major elements making up the healthcare value chain: the payer, provider, and federal and state governments.

  • For Payers:

    There will be a pressing need to reduce, simplify, or eliminate co-pay and pre-authorization (PA) for treatment as well as for re-evaluating cover charges for COVID-19 and healthcare. In effect, this will accelerate employer-led healthcare while decentralizing online operations at the same time.

  • For Providers:

    The focus is already shifting toward enabling immediate and universal secure online visits to physicians, availability of online testing, and at-home preventive healthcare (for both physical and mental needs), and ensuring the movement of vital supplies through an intact supply chain that is integrated with the help of PBMs, Pharma, and Med-Tech organizations.

  • For Federal and State Governments:

    These developments will create the need for consistent regulatory guidance for the healthcare industry, connected patient health management programs that focus on Medicare and Medicaid patients, and maintaining the overall integrity of patients’ EMR.

Implemented properly, these changes will serve to make healthcare more available, agile, and affordable, which is vital for a country like the US, where in a 2019 Gallup survey, over 33% of all the American households surveyed, admitted to delaying care for serious and moderate issues due to the prohibitive cost and complexity involved in accessing healthcare. Combined with pre-emptive action and agile policy making by federal bodies, the healthcare systems would be much more capable of tackling and containing pandemics such as COVID-19.

Along with actively leveraging technologies, Centers for Medicare and Medicaid Services (CMS) has already taken several policy-level actions in this regard. One such decision has been ensuring physician payments for telehealth services, at the same rate as with in-person visits, for all diagnosis work. This is a good sign, and clearly denotes a willingness on the part of the federal agency to leverage technology for succor in these trying times.

The Technological Roadmap for Healthcare 2020, and Beyond

Posing a major threat to global healthcare systems, COVID-19 has firmly established the need for active action, and the establishment of a robust, collaborative, scalable, and agile digital healthcare infrastructure. Comprehensive planning focus from private as well as government bodies, and a technology-led roadmap that incorporates learnings from the current situation, will pay massive dividends in terms of saved lives, crises management, and global recovery.

To come up with an effective strategy and transformation roadmap, organizations in the healthcare industry will need to consider a few key points:

  • Ensuring Regulatory Sync-up and Synergy

    With the CMS approving Medicaid Section 1135 Waiver in over 23 states (guidelines are being constantly upgraded depending on the ground situation across states), the healthcare sector can expect more intervention by federal bodies in view of the current situation and beyond. This in turn absolutely necessitates syncing of regulatory guidelines across international borders with subject matter experts deciphering the best medical practices at all levels.

  • Undertake Strategic Digital Initiatives

    There will be a greater need to develop new healthcare delivery systems through digital advancements and provisions for affordable care measures at a lower expenditure. In order to do this, the industry as a whole will need to focus on building accurate analytical models by leveraging pervasive health data, focus on using technologies to facilitate less expensive, faster alternatives to doctor visits, and enhance patient experience while also improving the bottom line and maximizing profits.

    Industry leaders will also need to leverage cognitive capabilities to drive action in areas that require immediate attention in terms of identifiable business processes, and develop affordable care models. This can be done by sustaining existing investments made in core claim administration platforms, and achieving efficiency targets at scale.

  • Urgent dismantling of Digital Adoption Barriers

    Sustaining patient engagement outside of a traditional care setting is vital toward building rapport between patients and healthcare providers, and driving population management across risk pools. With the telemedicine market valued at USD 12,446.33 million in 2018, estimated to grow to USD 60,448.47 million by 2024, overcoming these challenges toward digital adoption is not only the right thing to do from a patient care perspective, but also a profitable venture to undertake.

  • Utilizing Next-gen Adjudication Systems

    Strong growth is predicted for the health plan core administrative market. This means that all health and third-party administrator plans are potential areas where adjudication systems can be implemented for core administrative growth.

  • Establishing a new normal through PHM, AI, and Remote Monitoring

    In this paradigm shift toward a digital healthcare infrastructure, it is important to choose between developing in-house solutions or buying a pre-built market solution with a proven track record. In the case of the latter, it is critical to evaluate vendor qualification through proper selection assessments. This can be done by evaluating cognitive platforms based on product features, costs, and required customizations.

Implications across the Healthcare Value Chain

The current global situation will have severe implications across the length of healthcare value chains. Understanding this value chain is important, as it is a vital tool in gauging productivity and overall satisfaction at each stage and touchpoint. Specially since the term value holds some ambiguity when it comes to healthcare—usually being a combination of one or more factors out of quality, speed of delivery, cost of care, or even availability.

However, as with any other industry, the payer and the provider are the two key touchstones in healthcare. Furthermore, the consideration of volume vs. cost is a prominent one as well, with the resultant implications being directly tied to what measures are used to achieve this balance, with technology and remote functionality playing a significant part in this process.

For the healthcare sector, the following table highlights how certain balances on the volume vs. cost scale are achieved through specific procedures and applications on part of both the payers and providers:

Volume vs Cost Classification Payer Value-Chain Procedures Provider Value-Chain Procedures
Low Volume + Low Cost Actuarial Valuations and Navigator Advisory
  • Digital Wallet and payment systems
  • Pre-Authorization of Treatment/Care
Low Volume + High Cost
  • Exchange Operations, Predictive Analytics
  • Quality Scores and Accreditation.
  • Configuration of protocols and devices
  • Optimization of funding and costs
High Volume + Low Cost Service Delivery through either phone or mail as well as Claims Submissions
  • Real Time Diagnosis
  • Follow-Up Protocols
  • Team and Wallet Configurations
  • Provision Accessibility
High Volume + High Cost Claims Adjudication Direct Payment through Non-Digital Wallets

Conclusion

The current scenario is rife with challenges and opportunities in equal measure for the post-COVID-19 healthcare world, almost certain to witness increased investments and importance given to global healthcare, including greater scrutiny and involvement by federal bodies.

A robust, forward-looking digital healthcare system built for compliance with evolving government regulations has a lot to offer, including enhanced customer interactions and improved efficiency through bots, telemedicine platforms, VR and AR for deeper patient-doctor communications, machine learning and AI to drive research at speed and scale, and blockchain and cloud-based platforms to secure medical data and provide efficient, scalable, and rapid crisis management capabilities. The greatest value of digital-led healthcare systems will not be delivered in the form of improved bottom-lines or increased revenues, but in terms of more customized, personalized, empathetic healing experience for patients, and the lives touched, improved, and saved.

This blog was also published in ETHealthWorld


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Impact of covid-19 on global supply chains & opportunities in a post-covid world

Social eminence June 11, 2021

Several times over the last few weeks, I have heard of 2020 being referred to as a bad movie with a particularly grim storyline. The repruccussions of COVID-19 are being felt more strongly with every passing day, and despite the unprecedented steps and cumulative efforts undertaken by governments, businesses, and individuals to stem its growth, the virus continues rampaging unchecked across the globe, causing loss of life and hitting businesses across industries and verticals. The fact that the origins of the virus lie in China, the de-facto factory of the world, has only served to accentuate the damage from an economic perspective with a significant percentage of supply chains reeling in shock and crumbling with each passing day.

As per a March survey conducted by the Institute For Supply Chain Management, nearly 75 percent of companies reported global supply chain management disruptions in one form or the other due to coronavirus-related transportation restrictions, and the figure is expected to rise further over the next few weeks. Other interesting figures that emerged from the survey included the lack of any semblance of a contingency plan for almost half the companies in case of a supply chain disruption leading back to China, and well over 50% of the companies also reported experiencing sudden, unexpected delays in receiving orders, a problem compounded by supply chain information blackout from China. 

Nearly 75 percent of companies reported global supply chain management disruptions due to coronavirus-related transportation restrictions.

The figures above serve to bring out the vulnerable state of global supply chain management, the lifeblood of our towering economies in sharp relief. However, the writing had been on the wall for quite some time. Consolidation of suppliers by geos, where efficiency has historically been the key strategy driver and limited focus on de-risking procurement and supply chains over the last several years, has contributed to the current state of affairs with shortages of key items globally. Barely 3 months into COVID-19 – the very foundations of the ultra-globalized economies that we see around us and live within today, have turned into question marks.

In this article, while alluding to the larger macro-economic problems, we will focus on the impact of COVID 19 on global supply chain management. In the later part of the article, we will also talk about new opportunities that may arise in a post-COVID world, as our race puts itself back together and attempts to glean learnings that would make us stronger, should such a situation arise again in the future.

With COVID-19 pandemic exposing the vulnerabilities of the global supply chains, global businesses must leverage digital technologies to rebuild economies and deliver business value.

Key Macro-economic Challenges Associated with Global Crises

The Manufacturing Challenge

Manufacturing today is a far more complex process than say just a few decades ago, with subcomponents required to assemble a single final product sourced from several places across the globe. The raw materials required to manufacture these subcomponents could also come from different countries and continents, and the finished/semi-finished goods may then require to be transported all over the world.

This massive dependency upon logistics make import, manufacturing, and export a difficult proposition in case of disruption to the supply chains.

The Procurement Challenge

At the other side of the coin lies the procurement challenge for the sourcing organization. In a globally integrated world, a drive towards efficiency has caused an increasing consolidation of production in lower cost geos – primarily based in China, Taiwan, Vietnam, or other low-cost economies. With the pandemic starting in China and hitting countries across the globe, and the resultant fallout and shortages, the need for distributing risk has become more evident than ever.

The Distribution Challenge

  • Distribution of products is going through some unique challenges with challenges in staffing of warehouses, a need for direct distribution, and more intelligent and responsive allocation across channels.
  • Retailing has also been impacted in a peculiar way – the lockdown and curfew scenarios across the world have led to a unique situation where there is demand as far as essentials are concerned, subdued demand in some niche areas, and big challenges in the luxury items segment – and we are likely to see several retailers down their shutters while many others will be severely challenged on operating margins and models.
  • On the consumer side, hoarding/ stocking of essential commodities and OTC medicines has led to unusual stress on the supply chains. This unnatural spikes in demand and the required supply fluctuations are extremely difficult to handle and together create a bullwhip effect in the entire supply chain often leading to artificial shortages.

Post-COVID: The Brave New ‘Digital’ World

From an industrial perspective, the current situation is likely to accelerate digital transformation initiatives for businesses across the globe, as they are forced to be face-to-face with their weaknesses and vulnerabilities. Technology-led business models will emerge as more critical and important than ever and will play a key role in defining strategy as we reimagine the global supply chains of tomorrow.

Based on lessons that are being reinforced and validated in the current global crises, there are several ways in which businesses can go about creating resilient supply chains in a post-COVID world. For one, there is an urgent need to reduce dependency on physical labor across transportation, logistics, and warehousing. This can be enabled through core digital technologies for Industry 4.0 like IIOT, Blockchain, Control Towers, AI/ML enabled demand-forecasting, rule based and self-adjusting stock allocations, autonomous devices like AGVs, drones, etc.

Factories that can modularize production and shift/adapt lines due to demand changes, will be the norm of the future. They would be backed by supply networks capable of communicating intelligently with one another, compounding their effectiveness and agility. Businesses are going to pay a lot of attention to making critical systems available on the cloud so that they can be remotely accessed by employees as they work from home. Safety will also be a key factor and supplier risk management will be at the core to all planning initiatives. One of the few positives of the COVID-19 scenario has been exposing us to the possibilities of remote working across industries, domains, and businesses and if sustained in the post-COVID world, this trend will lead to a renewed focus on environment-friendly operating principles.

All this notwithstanding, the human element is the most important one that will emerge as we progress in the COVID-19, and across to the post-COVID world. Given the projections on the number of infected/ hospitalized, it will have a cascading impact on the availability of even the core services. The situation in Italy, Spain, USA, or China worsened further due to the essential services providers like medical professionals, nurses, and forces impacted by the virus. This is also visible in some of the newer impacted areas like India as well.

At HCL Tech, our Supply Chain Practice has been at the forefront of leveraging digital technologies to ease and build global resilient supply chains. We continue to be committed to continuing our focus on leveraging key technologies and offerings and to support businesses with our expertise, as they recover and use their learnings from the current crisis to bounce back stronger and more resilient.

Some key elements, that will prove crucial in the supply chains of tomorrow include: 

  • Intelligent Procurement – To help organizations understand where and when to source using advanced machine learning algorithms based on past purchases, commodity pricing, agro and industrial trends, etc.
  • Supply Chain Control Tower – A single source of truth from sourcing to delivery for all trading partners, to see and adapt to changing demand and supply scenarios across the world.
  • Supply Chain Data Management with intelligent automation and analytics – End-to-end information management, taking the form of a data vault of sorts to capture supply chain transactions accurately with high consistency and minimum redundancy. This will help supply chain organizations gather insights around supplier performance, supply chain diagnostics, market intelligence, and risk management.
  • Supplier Risk Management – N-tier risk management helping organizations model cost structures, trend performance data, and visibility into extended value chain to keep abreast of any supply disruptions and secure capacity. This could help companies avoid sudden disruptions in supply chain and deal with lack of information – something that many major global companies including Sony, are facing today.
  • Supply Chain Simulation – Modeling new supply chain strategies based on business/operating model change, current and/or future supply/demand/logistics constraints. Helps to validate and identify the best cost-efficient network to achieve the necessary service level across the value chain.

To conclude, from a purely business perspective COVID-19 presents a slew of serious and sometimes unprecedented challenges for organizations cutting across the business environment, including a possible liquidity crunch, global supply chain disruptions, increase in trade barriers, and a shifting consumer mindset. However, the post-COVID world will see digital technologies playing a critical enabling-role in delivering improvements throughout the breadth of businesses, including more resilient supply chains, significantly enhanced user-experiences, and intelligent optimized processes to deliver business outcomes.

This blog was also published in Entrepreneur India.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

How to successfully scale agile and devops - part 4: driving success with process

Social eminence June 11, 2021

Welcome to my fourth and final blog in the series “How to Successfully Scale Agile and DevOps”. Earlier, we had discussed the importance of scaling Digital/Agile, and the major propositions of the “People” and the “Technology” dimension of driving agile at scale.

In this post, we wrap up this series by taking a deeper look at the third element of this equation, the one that brings everything together – the “Process” dimension. It’s only fitting that this dimension is placed at the conclusion of the series, since it’s the overarching framework within which the People and Technology dimensions operate. As a result, it is perhaps the most vital element when it comes to generating actual business results.

Motivation – The Foundation of Change

We begin with the simple question – how do you bring about agile processes in an enterprise?

As we would all agree, Agile model is more a philosophy and a way-of-life than a methodology with a bunch of steps. Philosophies and ways-of-life can only be adopted by humans and not machines. So, the process aspect is more about driving the change in people than anything else. Hence, the key foundation of a process change at scale is all about motivating people at scale to adopt the defined process.

I’m reminded of the ideas put forth by Daniel Pink in his masterful book “Drive” which perfectly illustrates the gaps in how we motivate and inspire people and offers meaningful solutions to these problems. I’m particularly interested in the three core aspects of the book that have proven invaluable in my own experience. Namely, the idea of autonomy, mastery, and purpose, as the real foundation necessary to drive motivation in any process reform. At HCL, our foundations of the “Process” dimension have been based on these same pillars. My work in implementing these process changes across large organizations have yielded substantive results; whether for one of the banks in the Netherlands, a large car manufacturer in Sweden, or the leading digital bank in South Asia.

Foundations of the Process dimension in DevOps has been based on the pillars of autonomy, craftsmanship, and purpose.

Driving Motivation Across Organizations

While many frameworks have proven useful in terms of driving enterprise transformation roadmaps, many of them do not address some key fundamentals relevant to an enterprise journey. Some organizations have adopted models such as Holocracy or Sociocracy in recent years. But we believe that these models are very nascent in their structure and unsuitable for true enterprise-level needs. And more importantly, they haven’t been tested enough in the crucible of the real-world market to prove themselves worthy.

It’s worth remembering that the most effective agile framework doesn’t only tell us what changes need to be implemented but also provides a roadmap and indicators of how to achieve these changes. Therefore, when it comes to implementing changes in Process, the tenets of autonomy, mastery, and purpose, are far more prescient. The methods involved in enacting each of these elements can be surmised as follows:

Autonomy

As Daniel Pink says in his book, “Control leads to compliance; autonomy leads to engagement”. Therefore, to truly make lasting changes, autonomy needs to be rooted in the DNA of any organization and team. This entails a complete redesign of the underlying structures to help empower people. It offers them the freedom necessary in making their own decisions, especially if scaling agility and DevOps is the goal.

While there are various ways for organizations to redesign themselves, in our experience, a combination of organization design constructs from Scaled Agile Framework (SAFe) and the Spotify agile model to elaborate on Team level redesign have proven to be effective mainly due to their simplicity, which is essential when driving change at scale. A key aspect of this simplicity that works in Spotify’s favor is its clean and simple messaging, which manifests as easy terms of the four organizational units – squads, tribes, chapters, and guilds.

By reorganizing people into these groups, we can drive greater efficiency and productivity during the entire development cycle. Squads operate like scrum teams with about 6-9 people dedicated to one feature/capability, operating in an autonomous and self-organized manner. Though it sounds easy, it is by far the most critical and toughest journey in the Agile scaling journey. How do we break large enterprises into a cluster of hundreds or thousands of squads? Two recent experiences from customers in Germany and Switzerland proved that getting an incorrect team structure could prove disastrous where the organization found their velocity slower than traditional models with the additional burden of harnessing a demotivated team after the redesign. Incorrect structures will result in driving high dependencies between squads which will eventually slower the rate of deployment of new features to business. There are two critical learnings to ponder when we redesign organization:

  • Use of business architecture to redesign teams where typically squads are aligned to L4/L5 capabilities in the enterprise business architecture model.
  • Designs and structures need to be agile by themselves. It is critical to continuously measure dependency affinity between squads and redesign Tribes if found necessary.

For one of our customers who were struggling with showcasing improvement in feature velocity post taking an Agile journey even after having set up the organization into squads, just a redesign of the squads enabled us to reduce the release cycle times from 12 weeks to 3 weeks.

The final key learning on Autonomy we had is the notion of “Aligned Autonomy”. Autonomy does not mean that squads can choose their own Agile methodologies, tools and sprint cycles to deliver features. We have seen chaos engulf when large organization drove autonomy literally. Aligned Autonomy would ensure:

  • Common cadence: Squads follow the same Agile methodology across the enterprise or at the minimum MUST align to a common cadence. Common cadence ensures that squads are aligned, ceremonies like Program Increment planning become meaningful, understanding and aligning metrics across squads becomes easier and driving Agility at enterprise level becomes measurable and seamless.
  • Aligned roles and team structures: Standardizing roles across the organization and minimizing them greatly helps in driving autonomy faster. Also, having standard squad sizes help. I know of a customer who drove standardization of squad sizes by designing team tables that could exactly seat only teams that adhered to standard size.
  • Common Tools: If not others, I would advise to have a common tool to track both user stories and tickets when we restructure to squads. As much as possible the CI/CD or DevOps pipelines across squads must be alike to  enable faster collaboration and seamless tracking.

The concept of Aligned Autonomy might be against the core principles of Agile but if we want to drive agility at an enterprise level, we have found this to be a must.

Mastery

Mastery as a concept within our framework is something that we’ve already had the opportunity to explore in our earlier discussions especially on the People dimension. It has to do with the process of identifying and nurturing people and teams to be good craftsmen/women in the job they do. It’s all about getting full-stack engineers and creating high-performing squads that I had discussed earlier.

Though this area started-off with big challenges, this is an area where we can leverage engineering toolsets to make the exercise objective and thus adoptable. Since the time I published the People part of this blog series and now, we have had tremendous success in driving mastery at scale across many of our customers. This validated our faith in the approach. Since I had elaborated at length on this in the People part of this series, I will skip it here.

Purpose

The third and perhaps most important aspect of the three pillars to drive agile at scale is the enforcement of a personal purpose at every level of the organization. Once more I’m reminded of Daniel Pink’s words – “While complying can be an effective strategy for physical survival, it's a lousy one for personal fulfillment. Living a satisfying life requires more than simply meeting the demands of those in control. Yet in our offices and our classrooms, we have way too much compliance and way too little engagement. The former might get you through the day, but only the latter will get you through the night.”

How can a CEO ensure that the engineer in a squad understands the purpose of their existence in the organization and are able to relate their contribution to the roadmap drawn out in the Portfolio layer? How can we continuously measure the alignment of squad output to organization objective?

We have seen the following practices enable answers to the above questions:

  • Communication from the top: Organizations who managed to successfully transform themselves always had a direct channel of communication from the board or CxO layer to the larger organization. This communication is open and live and should clearly articulate the objectives of the organization for next quarter, year and 5 years.
  • Urgency: Unless there is a sense of urgency for change driven from the top, transformations fail. We have been through multiple such experiences.
  • Bottom-up business case: In the new team structure, once the organization objectives are advertised from the top, business cases must be created by the squads themselves and aggregated at each level. This gives a sense of purpose and accountability from all squads.
  • Open feedback: In the new redesigned Agile organization, it is extremely important for teams to have a view into each other’s business cases so that dependencies are managed between themselves and objectives are pre-aligned. It is a good practice to have all business cases available for everyone to see and critic in a collaborative tool.
  • Obeya: We can then leverage Obeya as a concept to continuously measure the progress of a squad or tribe to the business cases they have signed-up to and solve impediments if any.

The above is not a complete list but we have found organization adopt all or some of it and reap benefits in being able to drive purpose within each squad and thereby achieve meaningful velocity.

Thus, my view on the process dimension of scaling Agile model is not about advising which Enterprise Agile framework an organization must adopt or what Agile methodology they should adopt. I had briefly spoken about the latter in one of my earlier blogs and the State of Agile report gives enough indication that SAFe, SCRUM and Kanban are the most preferred. My view is that an organization that successfully manages to drive Autonomy, Mastery and Purpose at an enterprise level, would be an “Elite” organization as defined in the State of DevOps report. Adoption of these attributes is never big bang and it always follows the bubble-effect of starting small and scaling out.

Conclusion

This brings us to the conclusion of this blog post and the series “How to Successfully Scale Agile and DevOps”. As we’ve observed, the true challenge of scaling agile and dev-ops requires us to take an approach that addresses People, Process, and Technology in equal measure. It’s not only about creating a cross-functional, autonomous team consisting of full-stack engineers who are masters in their craft who come together to deliver business value with purpose than code, it is about transforming an entire organization into such teams.

I hope this series of blogs has offered you an insightful glimpse into the immense possibilities that scaling agile and DevOps has to offer and given you some useful information that can help drive decisions that make your scaling journey one filled with success. I wish you happy learnings, and please find time to post your comments, experiences and queries so that we can learn from each other.


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Pandemic analytics: how data is helping us combat covid-19

Social eminence June 11, 2021

As society grapples with the public health and economic challenges manifesting in COVID-19’s wake, businesses rushing to realign themselves to this new reality are looking to technology to help. Data analytics in particular is proving to be an ally for epidemiologists, as they join forces with data scientists to address the scale of the crisis.

The spread of COVID-19 and the public’s desire for information has sparked the creation of open-source data sets and visualizations, paving the way for a discipline we’ll introduce as pandemic analytics. Analytics is the aggregation and examination of data from many sources to derive insights, and when used to study and fight global outbreaks, pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease.

Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease.

Here are three ways pandemic analytics are helping us get through the COVID-19 crisis:

1 – To Craft the Right Response

In the early 1850s, as London battled a rampant rise in the number of cholera cases, John Snow – the founder of modern epidemiology – noticed cluster patterns of cholera cases around water pumps. This discovery allowed scientists to leverage data to combat pandemics for the first time, driving their efforts towards quantifying the risk, identifying the enemy, and devising an appropriate response strategy.

That early flash of genius has since advanced, and 170 years of cumulative intelligence has proven that early interventions disrupt the spread of disease. However analysis, decisioning and its subsequent intervention can only be effective when it first takes into consideration all accessible/meaningful data points.

At Sheba Medical Center in Israel, healthcare administrators are using data-driven forecasting to optimize allocation of personnel and resources in advance of potential local outbreaks. These solutions are powered by machine learning algorithms that offer predictive insights based on all accessible data about the spread of the disease, such as confirmed cases, deaths, test results, contact tracing, population density, demographics, migration flow, availability of medical resources, and pharma stockpiles.

Viral spread has a small silver lining: the exponential creation of new data which we can learn from and act upon. With the right analytics capabilities, healthcare professionals can answer questions such as where the next cluster is most likely to arise, which demographic is most susceptible, and how the virus may mutate over time.

2 – To See the Unseeable

The accessibility of data from trusted sources has led to unprecedented sharing of visualizations and messages to educate the public. Take for example the dynamic world map created by Johns Hopkins’ Center for Systems Science and Engineering, and these brilliantly simple yet enlightening animations from the Washington Post. Such visualizations are quickly teaching the public about how viruses spread, and which individual actions can help or hinder that spread. The democratization of data and analytics tools, combined with mass ability to share information via the internet, has allowed us to witness the impressive power of data used for good.

In recent months, companies have brought pandemic data gathering in-house to develop their own proprietary intelligence. Some of the more enterprising companies have even set up internal Track & Respond Command Centers to guide their employees, customers and broader partner ecosystem through the current crisis.

HCL realized early in the outbreak that it would need its own command center dedicated to COVID-19 response. Coordinated by senior leadership, it gives HCL data scientists the autonomy to develop creative and pragmatic insights for more informed decisioning. For example, developing predictive analytics on potential impact to HCL’s customers, as well as the markets where HCL services them.

With the goal of enabling leadership to respond quickly throughout the development of the COVID situation, we employed techniques such as statistics, control theory, simulation modeling and Natural Language Processing (NLP). For simplicity, we’ll categorize our approach under the Track & Respond umbrella:

  1. TRACK the situation quantitatively and qualitatively to understand its magnitude.
    • Perform topic modeling in real-time across thousands of publications from international health agencies and credible news outlets; automate the extraction of quantifiable trends (alerts) and actionable information relevant to a manager’s role & responsibility.
    • Create forecasting which will directionally track and predict when regions critical to HCL and its customers will reach peak infection, and conversely, a rise in recovery rate.
  2. RESPOND using a mathematical model of the situation as a proxy for the actual pandemic.
    • Create a multi-dimensional simulation model using robust and contextual variables to produce a meaningful prediction customized to the leader using it.

3 – To Diagnose, Treat, and Cure

On December 21, 2019, an AI system operated by a Toronto-based startup called BlueDot detected the earliest anomalies relating to what was then considered a mysterious pneumonia strain in Wuhan. The AI system accessed over one million articles in 65 languages to detect a similarity to the 2003 SARS outbreak. It was only nine days later that the WHO alerted the wider public about the emergence of this new danger.

Developing healthcare solutions is a challenge of solving data at scale, and this is where AI can play a crucial role. AI technology has already been deployed to help diagnose the Coronavirus through imaging analysis, decreasing the diagnosis time from CT scan results from about 5 minutes to 20 seconds. Through automation, AI can not only help cope with the rising diagnostics workloads but also free up valuable resources to focus on treating patients.

AI and ML can also be used to speed up the pharmaceutical development process. So far, only one AI-developed drug has reached human clinical trials. But even that solitary success is extremely impressive as the technology was able to expedite a process that typically takes years.

It’s quite possible that AI in conjunction with medical researchers can help reduce drug development timelines to mere months or weeks. With the world still in urgent need of a COVID-19 vaccine months after the first reported death, this human-machine synergy in the pharmaceutical space is the need of the hour.

Where We Go from Here

As the world braces itself for the impact of the COVID-19 outbreak, it is important to remember that technology is nothing but the cumulative innovation of humanity over time, and in technology we have the tools necessary to help us survive and protect ourselves. We do not know what lies in store for us in the coming weeks and months, but we will face it together, and our greatest strength will be in how we share, analyze, and derive insights from our shared knowledge.

With the right technology applied in the right direction, we have the potential to contain and minimize impact of disease today and in the future.

This blog was also published in ETHealthworld.com.


david.sogn_319532's picture David Sogn October 18
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Associate Vice President – Digital & Analytics

Building nimble and efficient platforms with modern microservices

Social eminence June 11, 2021

The world of enterprise software development came of age with the inception of ‘single purpose’ software applications aligned to a specific business function. Accounting programs in the finance domain were a common example. But with time, more applications arrived to spread the benefit of enterprise technology across multiple business functions such as manufacturing, supply chain and inventory management.

ERPs were designed to foster process efficiencies by transmitting information across business functions and collating the same on a central system for actionable decision making. Unfortunately, however, problems started creeping in when businesses customized these applications to cater to their own unique requirements. More often than not, increased customization rendered these applications slow and clunky, since they were too rigid to scale and were not created on open standards. Frequent iterations were a challenge due to the bulky nature of these applications. The IT department that was supposed to incite productivity became the reason for slowness.

Of course, ERPs are just one of many such systems. Other applications such as customer relationship management (CRM) systems also fit the description perfectly and are equally cumbersome. This class of applications are commonly referred to as monoliths.

From a software lifecycle management perspective, monoliths carry larger risk than smaller applications. Implementation, update, and maintenance of these applications can be a daunting task since there are too many moving parts that require simultaneous attention.

The Shift toward Microservices – Rewiring Software Architectures

Today, businesses mostly revolve around consumers. And it is customer experience that dictates business outcomes. Given this scenario, leading companies have set the standards for instantaneously responsive, personalized, and increasingly predictive real-time services across all customer touchpoints. At the locus of personalized service delivery lies smartphones which have made customers used to continuous improvements in applications instead of long upgrade cycles.

Technologies such as the cloud allows on-demand delivery of application functionalities, database storage, and other IT resources through the web rather than costly on-premise hardware solutions. However, simply shifting a monolith application to the cloud means relocating the same clunky software architecture on a separate system – along with all the shortfalls. So, companies need to focus on building nimble and agile applications that can accurately uphold the differentiation the business provides while continuously enhancing the capabilities they offer. This will allow them to engage customers quickly and meet demands as soon as they appear.

For instance, as Netflix made the switch into an online ‘only’ source, they had to focus on customer experience while ensuring that customers were getting access to personalized selection of content rather than browsing by genre. They must adjust personalized content and how it appears on millions of devices they support. Additionally, they also had to scale the application and content delivery rapidly. Especially with the release of a new show when viewership is expected to spike (take the instance of Orange is the New Black).

So, how did the streaming giant manage to achieve all this? The answer - microservices framework. Slowly but surely, enterprises across industries are adopting microservices which allow software. to be more agile and independently scalable. The pattern allows developers to localize change and reduce impact that might lead to lower availability.

With this architectural style companies have the liberty to deploy application functionalities as discreet lightweight services. These functionalities interact with businesses through a set of well-defined application program interfaces (APIs). This approach works well for most businesses since it allows them to deliver small application changes incrementally, while speeding up delivery and reducing service disruptions. Considering that mobile and other digital applications are extremely dynamic and require frequent updates, microservices prove to be extremely effective there too.

A recent survey reveals that 63% of companies are currently using microservices architecture, out of which 60% are doing so to attain faster turn-around times for new service and product deployments. with another 54% to foster digital transformation and, in the process, drive next-gen applications. It is important to understand that Microservices architecture does not essentially entail cobbling up several software components together. Rather, it involves the seamless functioning of independently deployable application functionalities that can communicate with each other through Application Programming Iinterfaces (APIs). These interfaces allow enterprises to escape monoliths, as they serve as a ´contract’ between microservices.

In order to simplify their transition from a monolith architecture to a micro services framework. , enterprises need to create a strategic transition roadmap right at the start itself. The ideal starting point for the adoption of microservices architecture would be to take an ‘A-B-C’ approach.

  • First Abstract: Create a layer of abstraction to access capabilities required to service the customers, employees, partners, and machines – API layer
  • Next Build: Align capabilities to leverage the APIs to improve user experience. Untangle the experience from how systems are architected
  • Finally Change: Break the back-end services to more manageable microservices

Simplifying the Transition – Overcoming Challenges that Come with Adoption

There’s no denying, microservices are poised to become the default model of software lifecycle management going forward. However, according to a survey from Lightstepa whopping 99% of the organizations have reported that they face challenges when leveraging microservices in software development.

Microservices are poised to become the default model of software lifecycle management going forward.

To maintain business agility, each component of a microservices-based architecture should be easy to develop, test, deploy, and release. Automating the entire software development lifecycle includes continuous integration, testing, and delivery (CI/CD) process in microservices. This helps the architecture to perform at full potential in terms of speed and consistency.

The trouble increases manifold when there’s a need to test hundreds of services, their integration, and interdependencies. One way to solve this would be to deploy service virtualization strategy for microservices. It can help provide developers and testers with tools to quickly simulate testing environments of a complex production environment, reduce dependencies and allow ease of integration. IT teams need to take on the responsibility to define the right capabilities (domains) that enable the functionality of a system.

With a microservices architecture that’s driven by APIs an organization might have to keeps track of hundreds of services running simultaneously. In such circumstances, keeping track of even the smallest of the incremental changes in an application is tough. As services are deployed, developers need to embed telemetry and analytics into the platform to simplify operations and change management.

Finally, every team involved in the microservices value chain needs to take responsibility for securing the services since it’s a distributed responsibility. Ensuring that calls are always routed through a secure service API gateway helps in establishing consistent security policies.

In short, teams developing microservices should care about ensuring quality, operating, and securing the service as much as they care about developing it.

Rounding Up

While software architecture design might not appeal to all decision-makers across the board, one can’t help but agree that software applications now lie at the core of how a business operates. Their nimbleness, overall performance, and resiliency directly impacts business agility and ultimately revenue.

Microservices represent a radical shift in the way how organizations approach application development while moving to a software-centric model. It’s time that businesses start exploring its potential to redefine the services that they deliver to their customers.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

How to successfully scale agile and devops – part 3: driving success with technology

Social eminence June 11, 2021

Welcome to my third blog post in the “How to Successfully Scale Agile and DevOps” series. In my previous blog post, I covered key propositions of the “People” dimension of driving agile at scale. In this blog post, we will deep dive and look at the critical “Technology” dimension and discover important elements that I believe can be leveraged to implement process automation and strengthen the digital strategy from a technology perspective.

The technology dimension of scaling Agile hinges on two ‘prerequisites’ and two ‘continuums’.

Prerequisites

There is a common pattern of two prerequisites in the technology area that successful organizations have driven:

  1. Technology Standardization

One of the prerequisites for the continuums to be successful is to reduce the number of technologies that enterprises must manage. In a large bank, I noticed that they had around 5 business process management (BPM) tools for process automation and case management and were evaluating a sixth one to be onboarded. This is a recipe for disaster as the more technologies such as BPM tools are utilized, more will be the need to have DevOps pipelines and more difficult will it become to drive continuous delivery.

One standard technology, say one BPM tool if we take the above instance into account, for each area in the simplified reference architecture given below would be ideal:

embarking

My suggestion while embarking on this journey would be to standardize on scaling Agile and DevOps tools and technologies that provide the ability to code rather than configure because the future is about running “everything as a code”.

  1. Legacy Modernization

Legacy modernization has become mainstream because of the advent of agile methodology, DevOps tools, and more importantly, micro-services architecture which demands monoliths to be broken. There are many digital strategies that pundits profess for legacy modernization but the ones I have found to yield benefit are:

  • Wraparound strategy where we wrap the legacy architecture with a modern layer which could be a microfocus layer, an application programming interface (API) layer, or a data lake layer.
  • Rebuild strategy where we identify digital use cases in the legacy applications and rebuild them in a modern way or rebuild the whole legacy infrastructure in a modern way.

Whatever be the digital strategy that works for you, please embark on a legacy modernization drive. Value is not realized just by changing things at the front-end layer, value can only be realized if it trickles down to the lowest layer of the reference architecture.

Continuums

Now that we have seen the prerequisites that can define your overall digital strategy, let’s come to the interesting part of ‘continuums’. I termed these ‘continuums’ because I don’t believe there is an end to these tenets. I am seeing them evolve rapidly and taking different forms and shapes.

Enterprise DevOps

According to the State of DevOps report by DORA, there is a direct co-relation between driving high maturity in DevOps and organizational performance, which thereby, creates better business value. The report found that enterprises that are performing well on the two key DevOps metrics of ‘throughput’ and ‘stability’; including faster lead times from commit-to-deploy, lower change failure rates, and faster incident recovery times; have a significant edge over low performing businesses.

To drive improvements in the above metrics, the most effective way of implementation that I have come across is to adopt the strategy of waste elimination from lean management. What is waste in software development lifecycles? Handoffs. Every handoff is a waste as it reduces throughput, increases the risk of quality, and creates differences. Given below are the different hand-offs that happen in a typical software development lifecycle (SDLC) and the DevOps tools and techniques that can be adopted to eliminate these handoffs.

embarking

H = Handoffs

Problems

  • People-dependent
  • Information leakage
  • Competency leakage
  • Accountability issues
  • Too many touchpoints for business
  • Cultural issues
  • Higher cost
  • Longer go-to-market (loss of competitive advantage and opportunity)

embarking

embarking

Each of the tools and techniques to reduce handoffs can be categorized into following areas of DevOps: Continuous planning, continuous integration, continuous deployment, continuous inspection, continuous provisioning, and continuous monitoring. Some of these areas are evolving, for instance, continuous monitoring is evolving into observability as a code. If you have not commenced your DevOps journey, then the best place to start would be in an area closer to production.

Since we are talking scale here, the key point to note on DevOps is to drive it at enterprise level and not at a project or program level. I strongly believe that enterprise DevOps definition available as a platform should be centrally driven while its realization can be done by the feature teams or squads. Though the initial few months (max. 6 months) can be driven through allowing closely monitored experiments across the enterprise, the learning of these experiments should be brought in to the central enterprise DevOps platform. Apart from implementing the tools and techniques called out earlier at an enterprise level, the enterprise DevOps team would also look at improving developer experience through developer portals which can be one-stop-shops to educate on the tools and pipelines in the platform.

I don’t think any enterprise can realize the true value of scaling Agile if they do not mature on their DevOps practices at an enterprise level and across all DevOps areas.

Platform as a Marketplace

Interestingly, as we speak of feature teams and squads, platforms are also becoming one of the key needs to drive Agile at scale. Though I will focus here on technology platforms, the same applies to business platforms like pricing, contact centers, and KYC platforms, among others. At an enterprise level, there are always redundant things that teams end up implementing.  Reducing this waste of redundant code is important to drive reusability, leading to standardization, higher efficiency, and improved governance and control. This can be achieved through enterprise platforms.

Below is a summary snapshot of possible platforms that I envision in an enterprise:

embarking

In a digitally mature enterprise, enterprise platforms need to be subservient to feature teams/squads. Platforms should exist to make the life of feature teams easier and simpler to add value to business. Thereby, platform backlogs must be filled by feature teams (specifically chapter leads) and platforms must be rated by feature teams for their ease of use and ability to add value. This inverts the pyramid of a platform setup which is important to drive digital at scale. Likewise, to setup a platform, a platform team must be equipped with the following squads (2-4 people per squad):

  • Onboarding and governance squad: The mandate of this squad is to onboard new tenants into the platform and define standards and guidelines that tenants must adhere to. In its matured state, this squad develops a developer portal with a predefined DevOps pipeline.
  • Business acceleration squad: This squad can be directed toward developing reusable business components by continuously looking at new components introduced into the platform.
  • Technology acceleration squad: The purpose of this squad will be to develop reusable business components by continuously looking at new components introduced into the platform and happenings in the industry.
  • DevOps squad: End-to-end DevOps pipeline to take any code introduced into the platform from the time of check-in all the way deployment and then monitor continuously.
  • Operations squad: This squad supports the platform and ensures that all environments (development, testing, preproduction, production) of the platform are running per the defined SLAs. This team is also responsible for upgrades, patches, SRE, and chaos engineering.
  • Innovation squad (Optional): This squad keeps experimenting to discover new things for the platform.

Finally, enterprise platforms should not be content with just driving reusability and standardization across the enterprise. In its mature form, I have seen them work as marketplaces— marketplaces where anyone in the world can contribute code to the platform. It derives its ability from the open source world but there is no reason why this cannot be repeated in an enterprise provided the platform squads called above can reach a high state of process automation maturity. I have seen at least three instances of platform marketplaces in large enterprises namely an enterprise DevOps platform as a marketplace, an API platform marketplace, and a digital component library platform marketplace.

embarking

Measuring effectiveness

As we embark on the two continuums, it is imperative that we baseline certain primary and secondary metrics at the beginning of the exercise and keep measuring them at regular intervals.

Primary metrics

I would lean heavily on the State of DevOps report on the primary metrics to measure. They would be:

  • Deployment frequency
  • Lead time for changes
  • Time to restore service
  • Change failure rate
  • Availability

I would suggest a useful, sixth metric:

  • Lead time to quality:
    Time taken by a team or a developer to pass a quality threshold set in the DevOps pipeline. This metric allows us to measure the time taken to pass each quality gate which, in turn, helps us to take corrective action and improve the gating policies themselves.

Secondary metrics

These metrics can be many though I have called out a few basic ones to start with. These metrics give us further insights on where exactly the problem is which is impacting a primary metric, and thereby, helps us to take the suitable corrective action:

  • Code churn rate
  • Build rate
  • Number of pull requests
  • Number of code merges
  • Code smells and warnings
  • Low level design analysis – CAST, JDepend

It is important to note that none of the above metrics (both primary and secondary) are derived or calculated manually. All are derived automatically through data available in the DevOps pipeline across the different areas. This will be a key implementation objective of driving continuous planning area of DevOps maturity. At HCL, we have a tool named Application360 that seamlessly integrates with most of the industry standard DevOps tools and thereby makes it easier to generate the above metrics.

To conclude the blog post with a quote from the continuous delivery book, “Hope is not a strategy”, and unless we drive the people, process, and technology aspects together, scaling Agile and DevOps and achieving digital maturity will prove to be an uphill task. However, while achieving this state may prove to be complicated, difficult, and resource intensive, the journey is well worth the effort and the rewards along the journey are immense. In the next and final edition of this series, I will be discussing the “Process” dimension of scaling digital successfully. See you then!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Reinventing for the digital age via the fenix 2.0 framework

Social eminence June 11, 2021

From the perspective of marathon runs, October 12, 2019 was a historic day. Kenyan long-distance runner Eliud Kipchoge completed a marathon in under two hours at Vienna, 1:59:40 to be precise. This feat was considered historic, an achievement worthy of Roger Bannister himself. While Kipchoge's run will not be considered a world record due to the heavy engineering before and during the race, the very same planning enabled him to do the impossible and as such is a worthy study.

A set of initiatives focused towards reducing the marathon time were planned and executed by various teams. This included –

  • Identifying the right location and circuit – A flat, straight circuit close to sea level was chosen
  • Ideal weather conditions - An 8-day window was chosen to ensure the perfect weather
  • V-shaped pacesetter formation to prevent head wind impact
  • Ensuring optimal route - Marking the fastest route on the road along with a car guiding the pacesetter
  • Lastly, a pair of shoes with inbuilt technology for improved efficiency

This coordinated orchestration led to the creation of marathon history.

When we study the organizations that have realized digital transformation success, the common theme is their orchestration of various digital pivots in a disciplined journey to translate strategic initiatives into successful execution. However, the list of such organizations is very small as inferred from a recent survey.

Most organizations can execute discrete digital projects focused on single initiatives, but they struggle to pull off the coordinated and sustained effort required to align multiple initiatives toward a digital transformation roadmap. Such organizations need an execution framework that can help orchestrate the transformation strategy and journey.

HCL's FENIX 2.0 framework is aligned towards enabling this objective.

FENIX 2.0 is an industry aligned digital execution framework that helps organizations rewire their core DNA to scale digital objectives. It was developed over the last few years through curated critical learnings from digital transformation journeys of progressive Fortune 500 organizations, where we were a strategic partner. It drives organizational change towards a culture of iterative but always on innovation and high performance along with a modern engineering approach towards execution. FENIX 2.0 also helps enterprises make critical decisions on rethinking business architecture enabled by foundation of composable and consumable technology architecture, to create business agility.

FENIX 2.0 is an industry aligned digital execution framework that helps organizations rewire their core DNA to scale digital objectives.

FENIX 2.0 Dimensions – We’ve considered the facets that make or break transformation and grouped them into five dimensions, which our framework addresses:

Fenix 2.0

Business Experience Design brings a domain focused and experience driven perspective to identifying the initiatives aligned with transformation goals. A rich understanding of innovation and disruptions happening in the industry along with experience and business process perspective help identify capabilities along with desired outcomes. These capabilities are then translated into a product or program roadmap.

Organization Agility enables the flow of value in the enterprise by aligning leadership, organizational structure, operating model, and culture. It involves designing the right enterprise structure aligned with value stream and products, and enabling workforces that are adaptive, collaborative, and always upskilling. These changes are driven under a well-defined organizational change management strategy.

Digital Execution must be high quality and backed by well-thought out digital operations to ensure sustained transformation. The key driver is ‘automation first’ meaning a large part of development and operation cycle are automated. In addition, with ASM 2.0, FENIX brings in a new perspective to running operations which is suitable not only for digital programs but also for traditional support engagements.

Architecture and Technology form the technological core of the enterprise, enabling rapid changes in design, development and operations. In transformation programs, business value is delivered incrementally, and it is important to respond to change quickly to enable introduction of new products, capabilities and alter experience based on feedback. Hence composable architecture adoption is key and a Cloud Native, API / Microservices based architecture along with platform-based approach enables it.

Data First approach focuses on creation of adaptive data platforms by transforming the existing data platform into a future-ready responsive platform capable of delivering real-time intelligence. Furthermore, this approach ensures intelligent data management via ethical data governance, self-healing data quality, universal metadata management and data science to enable better decisioning using AI with consideration for ethical AI governance.

Moreover, a digital culture provides the underpinning for digital adoption in an enterprise. A leadership that enables and promotes a culture of co-creation, collaboration, risk-taking and thought leadership lies at the very heart of transformational change.

A leadership that enables and promotes a culture of co-creation, collaboration, risk-taking and thought leadership lies at the very heart of transformational change.

These dimensions also provide the foundation for the two other constructs of FENIX 2.0 – Transformation Journey and Quadrants.

FENIX 2.0 Transformation Journey – Transformation journeys should not only focus on business outcome-oriented initiatives but also around other dimensions to enable high performance and sustenance. For example, organization agility enables people- and team-level transformation, changing alignment from projects to products and enabling scaling constructs like chapters or guilds.

MVSP

As part of FENIX 2.0 enablement, a contextual transformation journey is created for enterprises based on transformation objectives. However, this journey is not set in stone and is revisited regularly to understand progress, and adapt based on changing market needs.

FENIX 2.0 Quadrants - This is the most tactical element of the framework. The Quadrants guide enterprises in defining how to treat their operations as they move toward digitization. This is a way to make strategic and consistent decisions about when to innovate a new process, and when to scale, outsource or retire an existing process.

MVSP

As enterprise transformation initiatives result in various work types, the FENIX 2.0 Quadrant model maps these work types to four categories and defines operating models aligned with FENIX 2.0 dimensions. As an example, operations in the ‘Innovation @ Scale’ quadrant where MVPs are delivered in iterative cycles should be different from the ones in ‘Run-to-Retire’ where focus is on ensuring sustenance while reducing long-term investment; hence ASM 2.0 proposes Converged Ops and Segregated Ops model for these two quadrants respectively.

To summarize, HCL’s FENIX 2.0 framework helps organizations in both defining transformation initiatives and in executing them by aligning operating models with best-in-class engineering practices. While that’s quite a mouthful, it’s important to remember that true digital transformation requires a massive team effort in which every wheel and cog in the enterprise works in synchronization along the same roadmap. HCL with its FENIX 2.0 execution model delivers exactly that.

There are plenty of parallels to be drawn between a marathon and an enterprise. Making history, whether as Kipchoge or as a technology-led business, requires purposeful-yet-measured orchestration of various elements to make it come together at the right moment.


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Building an adaptive and collaborative workforce for succeeding in the digital economy

Social eminence June 11, 2021

Digital transformation is mainstream, and enterprises are no longer asking “why?” but “how?”. At the core of digital transformation is the ability to build adaptable organizations with a focus on continuous learning and process agility. Rapidly evolving digital technologies like cloud, IoT, and AI can be leveraged to create new business outcomes, but only if the enterprise is adaptive and composable at its core.

Organizational structures and cultures across industries are at the tipping point of change, as enterprises are challenged to create a technically savvy, culturally diverse, and agile workforce.

With businesses going digital, firms need to create a conducive learning culture to have their workforce ready for any challenge.

Organizational Structures are Constantly Evolving

The “born digital” leaders such as Google, Apple, and Amazon are built around an adaptive organizational core that’s difficult to replicate in legacy enterprises. However, such enterprises can commit to digital transformation by rebuilding organizational agility. Many digitally progressive enterprises have achieved this, including T-Mobile, Walmart, and Best Buy, by building collaborative cultures and delivering unique digital experiences to their customers.

To create organizational agility, enterprises need an adaptive workforce, strong technical and engineering talent, adoption of design/UX for business process restructuring, and multi-disciplinary teams. Business and IT teams can no longer afford to create silos and must work in constant collaboration.

With these opportunities come new challenges. Consider remote workers, who are leveraged to build on-demand teams from a global talent pool. A 2018 Forbes article stated that almost half of the U.S. workforce is remote, and this number is rising. The challenges associated with this shift not only include ensuring remote workers receive the required training, but also are well-versed in digital technologies and agile delivery processes. As a workforce solution, this strategy would enablethem to be integrated into multi-disciplinary teams.

Create a Workforce that Expects Disruption

Enterprises that thrive in the digital economy do so by hiring lean, agile teams of people who leverage technology as an extension of themselves and are ready for continuous learning. To achieve this, employers need to create a workforce solution wherein a conducive to learning culture exists at the workplace. Also, it should provide supplementary resources to help workers along this journey of continuous improvement.

By providing continuous learning opportunities, enterprises benefit from a workforce that is ready for constant changes in technology. A digitally adaptive workforce produces greater innovation, enterprise agility, and the capacity to predict, rather than react to market changes. Creating a culture of learning also helps enterprises hire and retain top talent. As studies have shown that for next-gen employees, the ability to learn while working is a top factor contributing to a company’s appeal as a potential workplace.

Below are some actions that business leaders can take to support a culture of continuous learning:

  • Evolve the Hiring Process

    Expertise is important than years of experience, and the ability to collaborate exceeds individual brilliance. Tim Brown, Founder of IDEO, established the term ‘T-shaped employees’, where depth, expertise and the ability to collaborate are the key attributes for employees. Hiring practices should change to reflect this transition; moving beyond scripted interview questions and testing candidates in simulated environments. Instead, an effective technique would be to employ the hack-to-hire initiative, which tests a candidates’ ability to innovate, collaborate, fail fast, and bounce back – all attributes that signal resilience and adaptability.

  • Combine Learning and Performance

    While the current generation of employees is typically more learning-focused than its predecessors, organizations need to incentivize continuous learning. This can be done through initiatives that link performance with a drive to learn. This is exemplified by companies that support temporary cross-functional roles for their employees. In doing so, would help build expertise beyond their function and gaining a more holistic view of enterprise operations.

  • Create Accessible Learning Paths

    Enterprises should create learning tracks tied to career progression both within and outside the organization. One approach is partnering with universities to launch credit-based programs that allow employees to upskill, upgrade their knowledge, and gain practical on-the-job experience by applying said skills.

    As a workforce solution, HR and IT should collaborate to make content easily accessible, ideally on consumer-grade technology platforms. It’s important to ensure that work and learning do not interfere with each other; for instance, instead of mandatory group sessions, enterprises could record webinars for on-demand access.

    Employees on a learning path should be able to gain experience by interacting with the teams working on projects that require the use of that skill. This promotes internal mobility while fostering cross-functional thinking.

  • Revitalize the Learning and Development Function

    The L&D function should shift focus from content creation and facilitation to a more complex role, leveraging technology leading the enterprise cultural transformation toward continuous learning. The objective of the L&D function should also include creating employee-centric learning experiences and promoting interdisciplinary thinking.

Investment in Continuous Learning Matters

Enterprises must rethink, restructure, and reinvent their approach to upskilling their workforce. While the outcomes are not instantaneous; investing in a culture of learning is no longer a matter of choice, but a necessity. Businesses that get it right will find themselves attracting and retaining the best talent, and in possession of a workforce that can keep up with the challenges presented by a dynamic world.Not only would businesses that get it right find themselves attracting and retaining great talent, but also have a workforce that can meet the challenges of a dynamic world.


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Scaling the digital execution model

Social eminence June 11, 2021

Companies achieving digital progression have developed a distinct structure that enables them to digitize their customer experiences at scale and at speed. Enterprises are also coming to terms with the fact that technology has shifted from being an enabler, to the key differentiator. This transition has made them realize the necessity of re-orienting themselves to operate like a hi-tech engineering company, irrespective of their business domain.

However, most companies find themselves facing a set of crucial questions while on this journey. What is the right operating model to optimize digital? How to scale Agile and DevOps initiatives? How to do things differently from the competition?

It is paramount for companies to identify their differentiators and choose the right execution model in alignment with the target areas. We know that customer centricity has so far driven agile programs, but it is also worth understanding if the processes and programs in place are conducive to agile execution. Hence, it is important for organizations to adopt a holistic approach that involves working on their strengths while mitigating their weaknesses when changing to the digital execution model. What’s more, with technology adopting a more front and center role for businesses, the agile model has expanded beyond customer-centricity concerns and today, is relevant to processes across the IT landscape.

Scaling and Pacing

In today’s digitally inclusive ecosystem, the agile model has become more mainstream and is being used in various programs across enterprises. For example, more and more back-office functions are seeing the application of agile in order to improve speed, bring efficiency to operations, and resolve issues.

In view of the agile model seeing increased enterprise-wide application, talent also needs to be scaled and optimized. While organizations focus primarily on process, for the agile model to bear dividends, the same importance has to be shown to people. Organizations must build and invest in their people, fine-tune their talent, and create an encompassing culture of engineering in order to get the best out of an agile environment.

Organizations must create an encompassing culture of engineering to get the best out of an agile environment.

The Key Tenets of the Agile Execution Model

Just like Rome wasn’t built overnight, the people-centric process must be allowed time to thrive. The changes will be incremental, and with right planning, successful execution will achieve the desired results. The execution model to scale agile programs involves:

People-centric processes require time, planning, and an agile execution model to change progressively.

  • Organizing: The product engineering team plays one of the most crucial roles in driving the agile program. They are responsible for building, running, and maintaining platforms that integrate the existing processes with the modernized tools and applications in order to make the product ecosystem responsive to Agile. A ‘discover-design-deliver’ model involves a thorough understanding of the product and the process that the team intends to build, develop it in alignment with the plan, and finally, deploy it successfully. It is worth understanding that the agile model requires product teams to live in perpetuity. Organizations need to migrate from project-based teams to product-oriented teams. These teams must have complete ownership of the products they develop. As a result, the team sizes will shrink, but they will live longer and be responsible for the products they develop.
  • Training: As team sizes get smaller, every resource must do the heavy lifting. This mandates team reskilling for organizations moving into the agile spectrum. The Agile principle will shrink the team size, but the cumulative value of the team will go up due to the higher value of the individual resources. Another factor, which will contribute to the increase in the team value, has to do with the increasing focus on hiring and retaining competent resources as opposed to senior resources. In terms of team building, this translates into a shift from experience-focused team building to expertise-focused team building. With all these changes in mind, it becomes crucial to train resources with the aim of increasing the value-per-person and make them take end-to-end responsibility of products. This significant shift in philosophy may be painful at first, but it offers greater collaborative scope and much-needed flexibility to optimize operations.
  • Operating: Agile and DevOps models are run on cutting-edge tools, but the process is run by humans. With team sizes shrinking, the overheads need to be reduced as well - since the teams won’t have the bandwidth for increased cycle times. This makes DevOps a key proposition. Additionally, with specific training, the teams can do significant automation upfront in order to manage their limited bandwidth better, and more importantly, increase the scope of validation. By facilitating It is, therefore, important for companies to realize that Agile can be optimized only when the resources take to the change proactively and utilize their improved skillset to achieve the best result. A smart enterprise can use the culture and tools in synergy, in a manner such that the latter augments the former, to accomplish its short as well as long-term digital goals.
  • Automating: A reskilled team’s capabilities can only be fully leveraged with appropriate levels of automation. It will not only standardize the output but also make the process cost-effective and reduce the time-to-market. The coding-testing-releasing-maintaining lifecycle of the product is critical to the sustainability of the overall operation, and automation provides the consistency that agile initiatives rely on. What’s more, automation also makes product scaling across the enterprise, what with its multiple teams at different levels of technical expertise, easier, lowering variability and improving consistency.
  • Measuring: A company that doesn’t measure its initiatives seldom improves. In the agile environment, enterprises also need to rethink their measurement processes, to ensure that they are capturing the business value created, instead of merely going by the volume of work.

Having access to the metrics alone won’t make a significant difference though. What is more important is to use these metrics to bring about a change in organizational behavior and philosophy. Story points on features will help paint an accurate picture of an organization’s operations and where it requires improvement and allow you to drive greater business value. The metrics are thus critical to improving operations and scaling initiatives by knowing which holes to plug.

While the agile model has been disruptive to industry mainstreams for some time now, it is rapidly becoming the new norm that is finding new applications every day. In view of this, organizations need to be steadfast with agile adoption to ensure that they don’t miss the digital bus. As a key service provider to some of the largest enterprises across the globe, HCL recognizes the opportunities of tomorrow and creates its services with an eye on the future. We identify with our clients, partners, and the ecosystem, and develop our service suite in line with the ever-evolving business landscape. Our vision is to create a sustainable future for the world through agile environment and innovative businesses.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

Human-centered design: a people-first innovation mindset

Social eminence June 11, 2021

It all starts with changing the belief that there’s a solution waiting to be discovered for the human problem you’re trying to resolve — and for the people dealing with that problem. Human centered design (HCD) is a framework central to any innovation process. Optimistic, empathy-based, and holistic, a human centered design ensures that regardless of the tools or processes used (like design thinking) the result will be purposeful, useful ideas that solve problems for people they are intended to serve.

HCD: A Process Focused on Human Needs

HCD is purposefully nonlinear. It requires cross-functional teams to discover, explore, and resolve problems through iteration and radical collaboration.

An HCD approach can not only solve problems but also help avoid them in the first place. Grounded in a deep understanding of the user, aligning around their shared problems, HCD guides idea generation based on factors like desirability and so on.

HCD is often confused with design thinking but they are not the same thing. Design thinking (DT) is a collaborative process based on co-creation that works to identify and create desirable and adaptable products and services through iterative steps, including empathizing, defining, designing, ideating, prototyping, testing, and repeating. HCD is the litmus test which guarantees that, in the end, the product actually solves real human and business problems.

For example, we used a design thinking process to conceptualize, from scratch, a digital product solution that would disrupt breakdown management for the trucking industry. We used HCD to ensure that the end product served and solved the human needs of each player in the breakdown process – from the driver to the mechanic.

Without HCD, the idea may have worked technically but not been adopted by the end user. People tend to adopt things that they find useful.

An HCD mindset also has the power to forge alignment across organizations. It establishes a common purpose of the effort.

This is why we believe in creating value propositions on the basis of a people-first design process at an engagement’s outset and focus on using HCD throughout.

In this quest, HCL’s end-to-end HCD solutions involve:

  • Learning and understanding user needs and business goals.
  • Innovation, design, and technology enablers and accelerators.
  • Creating and considering experiences for both the customers and the business.
  • Building and deploying solutions with measurable outcomes.

The Value of Understanding the Human Perspective

Design is about solving human problems. To really understand human needs, challenges, pain-points, concerns, behaviors and what drives them, an HCD mindset is imperative for exploring potential business models.

Applying an HCD-first mindset and approach ensures value creation for businesses and their consumers. In a fast-digitalizing business ecosystem, design thinking plays a crucial role in aligning products to customer expectations.

As business models shift, HCD helps businesses forge well-rounded digital strategies to develop an array of solutions for future end users. Organizations with human centered design thinking at the core of their operations – like Apple and Google – use HCD to create cutting-edge value by understanding their users’ purposes and goals. In knowing for whom they are designing, what they want to achieve, and why, companies like Apple and Google ensure that their design teams’ future efforts lead to a continuous and desirable product evolution and improvement.

Scaling Digital with Human-centered Design

Human-centered Design (HCD) is the litmus test which guarantees that, in the end, the product actually solves real, human, and business problems.

Through constant innovation across industries and cultural touchpoint, digitalization has made our lives more technically dependent and less human reliant.

This has brought us to a crossroads where technology has to be more human-friendly and attuned to our lives as it replaces ever more spaces of human effort. It should be capable of balancing operational efficiency with an optimized customer- and human-centric experience.

HCD acts like a Greek choir in this new landscape, whispering human perspectives and needs in the ears of those making digital decisions.

Embedding HCD as a strategic perspective accelerates the transformation and also increases a design’s value. Besides, it develops a creative culture of taking risks, trusting employees, accepting the incremental failure, and learning from it to improve and innovate.

Embedding human-centered Design (HCD) as a strategic perspective accelerates an enterprises' digital transformation initiatives.

Corporations are now establishing a human-centered mindset because they understand that a brand’s credibility depends on the impression it creates on the customer experience.

Applying a human-centered design approach ensures value creation for businesses and their consumers.

Hyper-personalization of products and services and customer-centric designed experiences – all can be credited to HCD thinking. Amazon Go or Apple smartwatches may just have flooded the market but the concept of designing for human need vs. just what a business wants to sell is not new. Organizations have long realized that they need to be omnipresent among existing consumers. To do so, they must offer what people actually want and need to solve real-life problems while also looking to break new ground in new directions for as-yet unmet needs. For instance, Apple’s iPad – a product that some argued at the time was a solution in search of a problem.

The HCD approach only underlines this market dynamic, assisting the organization leadership to develop the most effective solutions, business models and digital strategies aimed to solve real-human needs and solve their problems. As technologies become more advanced, HCD will ensure that smart solutions not only meet immediate customer needs and expectations but also factor in social considerations like human needs, wants, and behaviors.

Leading the Way: HCL’s Innovation Credibility

With HCL’s expertise and advanced competencies around human-centered design, the company has partnered with organizations across industries and geographies. Among them is a European banking major that is building a co-innovation lab to drive customer experience with a fully customizable application. The lab enables collaborative concept sharing and prototype development, which enables HCL to deliver a platform that aligns risk and finance datasets while integrating business processes.

Another partner, a world-renowned football club wants to increase their supporter base and optimize the experience, before, during, and after a match. Attracting untapped swaths of their international fan base was negatively impacting the client’s digital revenue.

HCL helped reimagine the fan experience by developing a personalized digital platform that delivers meaningful multimedia content, analytics, e-commerce, social media integrations, gamification, and real-time match experience. By diving into the life of the supporter, understanding their preferences and by analyzing trends, HCL created a roadmap to create a one-billion fan base and media reach. HCL also deployed a single digital platform to connect various channels like merchandising, ticket booking, player stats, social media, etc.

HCL partnered with a major European automobile maker to identify and suggest IA/UX best practices to be adopted and integrated across product life cycle management. Based on the reliable representation of audience, HCL identified key user goals, needs, challenges, and expectations. We came up with a design thinking model that helps users optimize their KDP application. The modern interface also enables a real-time, 360-degree view of all parts, resulting in an elevated, more informative, and useful customer experience.

The HCD development space may be nascent but is rapidly growing with an increasing number of companies and agencies specializing in HCD-driven digital solutions as technology advances and user and customer-centric experience becomes ever more necessary.

Figures indicate that HCL is doing it better than its competitors. A New York-based environmental group stated that HCL’s HCD digital solutions resulted in improving quality by 86%, increasing productivity by 68%, and enhancing customer satisfaction by 76%. While this underlines our innovation efforts, it also helps serve as a differentiator. HCL is a knowledge partner in understanding the human side of the digital landscape by creating robust and holistic business ecosystems with a human-centered mindset.


Senior Vice President - Digital Consulting Practice

Reimagining the enterprise culture for digital adoption

Social eminence June 11, 2021

Industries across geographies are fast digitalizing operations in order to optimize output and elevate customer experience while creating a sustainable and safe ecosystem. In such an evolved business landscape that is perpetually innovating, the digital endeavors are multi-faceted and organizations need to be considerate of a quantum of crucial aspects. Cultural change in perspectives is one of them. While the industry leadership is waking up to the merits of digital transformation and adopting technological innovations, the organizational culture is often found wanting, causing roadblocks for the process of digitalization. It is, therefore, paramount to an organization’s well-being that an all-encompassing digital strategy is put in place that synergizes with a progressive organizational culture.

A HCL-StraightTalk collaborative study found that while 70% of the organizations already have a digital strategy in place, only 10% of the organizations have a definitive deployment plan. This reflects dourly on how organizations are getting more steadfast in developing digital plans, but are being unable to make a headway with their execution. The cultural challenges are the foremost reasons why most organizations are failing to see their visions turn into executable practices. For digitalization to be seamless, successful, and holistic, a cultural change is required across sales, marketing, IT, and operations.

For digitalization to be seamless and holistic, a cultural change is required across sales, marketing, IT, and operations.

Need for Change

The HCL-StraightTalk study found that 69% of the organizations feel that customer experience is at the center of digital transformation initiatives, but almost 90% of organizational leaders lack visibility into existing business processes. This does not reflect favorably on a business model that must tick the right boxes for sustainable business operations. In order to keep customers in the center of business operations and elevate their experience, organizations need to identify the areas needing change in alignment with its digital strategy. Three critical criteria that should be fulfilled before embarking on the digital journey are business viability, technological feasibility, and customer desirability. The digital strategy must revolve around these three aspects, thereby clearly emphasizing the changes required across spectrum.

The study found 92% organizational leaders find it exceedingly difficult to keep pace with the technological changes and only 64% are investing in digital innovations to leverage latest technologies. It is, therefore, our prerogative at HCL to add value to our partners’ operations by understanding their ambitions and driving their digital strategy and digital innovations to achieve scalable digital engineering. As trusted knowledge partners, we bring to the table the vision of a holistic ecosystem that vitalizes organizations’ ability of keeping pace with technological innovations.

Adaptability is the Key

Transformation, of any kind, needs time and resolve. However, seamless change is only successful in the end by adapting to the needs of time. It is therefore no surprise that the key doctrine of cultural change aligned to digitalization is a gradual acceptance of the changed status. Employees are the key drivers of any organizational change. Their involvement will strengthen the process and system to the point where digital is not just a tool anymore; it becomes the inherent modus operandi.

Clarity of purpose coupled with a fitting organizational strategy is paramount to optimizing digital engineering, and adapting to innovations perpetually is key to sustained growth. Human perceptions and behaviors must be more forthcoming towards the changing technological landscape. This will invariably lead to breaking down the silos that are omnipresent between business and IT, making digital innovations and transformation a seamless and an inclusive process. At HCL, while most of our clients have different objectives, the challenges they face follow a basic theme: culture and mindset. So, while the end objectives may vary, the challenges are common.

Incremental Change, Exponential Growth

As I mentioned, transformation demands patience and process. Digital is ubiquitous, and while organizations identify the pain points, and ambitions, and devise their digital strategies, the execution is stifled by the cultural challenges. Transformation is expected to hit such pockets of resistance and slow traffic. However, a robust digital strategy considers those as a part of the process and factors it in at the very start. At the heart of a successful digital strategy should be striking the right balance between desirability, feasibility, and viability. And, it can only be fueled by cultural change and engineering discipline.

While changing culture around digitalization, it is important to develop digital execution expertise internally by ramping up the available skills in the company. It is also equally important to be able to measure the digital transformation over frequent time periods in order to understand if expected results are being achieved or certain aspects of the transformation initiative is lagging. Agility is therefore another key cog in the digital wheel.

At HCL, we believe in valuing every aspect and pay meticulous attention to every component involved in the digital transformation process. This, keeps us ahead of the curve.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

Cognitive solutions powering data marketplaces

Social eminence June 11, 2021

My previous blog touched upon the paradigm shift taking place in today’s increasingly distributed data landscape. As a natural extension of this transformation, I would now like to share some thoughts on how cognitive technologies are poised to power data marketplaces which have arisen in recent years. More so due to the integral role knowledge management now plays in the cognitive world with respect to training machines for business and data processes.

I believe that most 21st century enterprises have yet to fully tap the potential of cognitive technologies and have much more left to accomplish in the field. These technologies are far more powerful than the day-to-day data processes automation tools most organizations are aware of, and involve numerous innovations in machine-to-human or machine-to-machine interactions that can transform business outcomes.

Rise of Data Marketplaces

Just as oil was the most valuable fuel of the 20th century, many industry leaders believe that Data is the most valuable fuel for 21st century enterprises – but while oil may have its limits, data does not. Many organizations are already exploring ways to unify and speed up the way they use data in various business scenarios. As a result, we’ve seen the rapid emergence of Data Marketplace tools and platforms that seek to address this business requirement.

Essentially, data marketplaces are a “one stop shop” that businesses use for business requests, reports, and insights in an easy and direct manner. Within an enterprise, data marketplaces offer a simplified architecture that can easily collect, collate, organize and integrate, data from various sources to become a Unified Data platform. An effective Data Marketplace is able to structure the unstructured data across the organization, by creating a compatible data model across silos that standardizes data formats. This data is further emboldened through various enhancements such as data search interface and data visualization which allow for up-to-date, fast and easy projections and estimations of business scenario simulations, making it a valuable business tool.

This approach to accessing data allows businesses to utilize their company-wide data from anywhere through a single point of interaction. This saves time and effort, as data no longer needs to be sourced, selected, and interpreted for each business case. As a result, businesses are able to achieve cost savings and quick turnover timelines as issues of data replication and data movement are solved. However, as we continue to look at the changing digital data ecosystem, we can see that the potential of data marketplaces can be significantly enhanced when we leverage cognitive solutions to further extend their functionality.

For example, in one of my recent projects, I had the opportunity to work with one of the world’s leading market research companies to help realize their need for automated data delivery and processing. Together, we were able to truly unleash the business value of data by consolidating all their requirements into a graph database with a machine learning powered cognitive interface that could enhance search prioritization and quality matching. In this manner, cognitive solutions were leveraged to enhance quality requirements with the critical goal of ensuring that there was no mismatch in customer expectations vis-à-vis delivery.

Traditionally, most data operations have been done through traditional manual interventions that requires enterprises to spend an immense amount of workforce resources. However, cognitive solutions changes this as it can speed up the outcomes by simplifying tasks such as driving data governance, continuously updating metadata, handling knowledge management and most importantly, monitoring data operations.

Data Marketplaces in the Enterprise

Let’s consider for a moment the needs of the next-generation enterprise – speed, accuracy, and excellent customer experience. All these goals require companies to be quick to respond to changes, and develop well thought out business scenarios to leverage emerging opportunities.

Take for instance a major global retailer we work with who operates over 410 stores in 49 countries. The company has over 800 million annual customers, over 2 billion annual visitors to their stores, nearly 150 million app users, nearly 150,000 employees, and over USD 40 billion in sales. For such a company, the ability to integrate data from across diverse nations, customers, and people, doesn’t just end in the front-end but also extends across their value chain.

For them, ensuring a harmonious data ecosystem across geographies and sources is critical to being responsive, fast, and efficient in serving their customers across geographies with a high level of quality. Moreover, given their leading position in the industry, they also have access to data from numerous vendors, suppliers, and manufacturers that are part of the production value chain. Therefore, having active access to these disparate data sources, such as inventory data, finance data, supplier data, and customer data creates the ideal data pool needed to track lead times and efficiently manage their business plans over seasons, cycles, and different business scenarios.

In such a case, having access to a Data Marketplace is not only beneficial but also critical for sustained business growth and success. However, the challenge to being responsive at such a scale can prove daunting. While Data Marketplaces are useful in bringing data together, the final bottleneck remains invariably human. This is where AI and other cognitive technologies have played a big role and helped ensure rapid access to insights and intelligence.

Potential of AI in Data Marketplaces

Data Marketplaces in a cognitive world don’t have to simply be “one stop shops” but instead can act as deployed agents. These cognitive agents function like an engine that continues to handle data operations and governance including all administrative tasks to support daily needs such as information regarding consumers, business analysts, power users, executive leadership, casual users and most importantly, business process owners whose endeavor is to simplify processes to enable quick outcomes in a business agile world that is freed from a human worker’s knowledge and ability to make decisions.

Data Marketplaces in a cognitive world don’t have to simply be “one stop shops”, but instead, can act as deployed agents.

Over the last few years, I’ve worked with my team to develop this form of cognitive tool that takes a modern approach to data exploration. We simply call it the HCL Data Bot that is integrated to our data fabric ecosystem in our solution to help enterprises as they scale digitally. This cognitive tool was designed to help organizations manage data operations, processes, and system performance in order to help contextualize business needs and enable monitoring of business KPIs. Consequently, the integration of this bot within data marketplaces has been able to help enterprises easily discover actionable business insights and help users sift through the hundreds of data variables and fields, while also being able to locate data and link it to the appropriate metadata for a more comprehensive dataset.

This type of holistic integration can help users acquire the most optimum data selection that is suited to their business scenario and leaves the need for manual searching in the past. In fact, with advanced AI and NLP based tools, data bots can assess a user’s data requirement history and proactively offer a more specific dimension of selections, saving time and effort. Users can also easily discover the data’s availability, and the bot can share various useful details such as the previous use-cases of a particular dataset, as well as the feedback surrounding its previous uses.

AI Behind the Platform

Throughout my career, I’ve always placed an immense importance on design thinking and knowledge management, both of which have been core pillars of digital transformation. This approach is essential as it is more capable of understanding user personas and their value journey, thereby enriching the value of the end solution. HCL’s Data bot can provide prescriptive suggestions for orchestrating new data sets as they become available on the platform, thereby making the process more proactive while also being reactive.

Cognitive intelligence tools can also be used to assess the core effectiveness of the data provided. By evaluating the degrees of success of past deployments, cognitive intelligence tools can help businesses quantify the data KPIs and assess its value in achieving business goals. This process enables businesses to effectively plan the correct data for the correct business problems, by knowing which scenarios offer the greatest ROI, and whether it leads to better business outcomes.

Cognitive intelligence tools can also be used to assess the core effectiveness of the data provided.

Moreover, cognitive intelligence can play a valuable role in assisting in the management of data processes at their very fundamental level. Similar to virtual personal assistants, advanced cognitive intelligence tools can help in the processes that surround data administration by monitoring data flows on the platform. These solutions can also ensure an automated performance and quality check of the data marketplace platform.

Constant Transformation

As I’ve said before – digital data ecosystems are undergoing a paradigm shift where we need to adopt a Data Fabric approach to make data more accessible and actionable across the enterprise. Moreover, as more and more organizations begin to adopt a fully digital approach, the challenges of digital at scale can only be tackled with the benefits of cognitive technologies. I’ve already had the opportunity to work on numerous implementations of this kind and am convinced that cognitive solutions offer all enterprises the correct combination of tools with which to unleash their business intelligence potential and blaze into the 21st century.


venkatakrishna_c's picture Venkata Krishna C September 26
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Global Solutions Lead - Data and Analytics

How to successfully scale agile and devops – part 2: driving success with people

Social eminence June 11, 2021

Welcome back to the blog series on “How to Successfully Scale Agile and DevOps”. In my first blog post, I outlined the challenges faced by organizations as they attempt to scale up digitally and how the remedy lies in enacting change across multiple dimensions. The three key dimensions that require transformation for a successful outcome are People, Process, and Technology. I also mentioned the importance of Organization Change Management (OCM) in helping organizations fully enable the holistic changes needed to truly achieve successful outcomes from their scaling initiatives.

In this second part of the series, I will be discussing the People dimension and demonstrating how organizations can reboot and upgrade the “people element” within their Agile and DevOps teams to achieve agile transformation. So, let’s get started!

Cross-functional and Self-Organized Teams

Any organization that wants to scale Agile and Digital needs to orient its workforce to be self-organized and cross-functional. Self-organized teams possess unique skills and attributes brought together by a motivated group of people who possess the ability to make decisions and adapt to changing scenarios. Self-organized teams are able to take greater accountability of a feature or capability on any project and are constantly innovating. Cross functional teams are constituted of a group of people who are able to bring in all the skills required to collectively own a business feature or capability.

The best examples for self-organized teams can be found in the operating model of virtual teams who come together to play virtual games over the web. The best teams in this context are self-organized with no single leader. Each participant adapts to a servant or leadership role based on the skills needed to achieve the objective at any given point in time during the game. The switch-over of leadership is voluntary and it happens every few minutes.

Let’s assume a typical feature is being realized in a project through a simple three-tier architecture, the bare minimum roles that would be essential to create a cross-functional team are as follows:

  • Product Owner: Business representative who is the Product Manager for the feature
  • Analyst: Fulcrum between a Product Owner and the larger implementation team. In matured Agile teams, this role will cease to exist as the Product Owner matures to perform the duty of Analyst.
  • Scrum Master: Self-organized Agile teams do not need one. But let’s take a typical scenario in today’s world where Scrum Master are still required. A good scrum master needs to cannibalize his/her role but that’s a topic for another blog.
  • Developers: At least three developers, assuming we are working on a three-tier architecture.
  • Support engineer: Since we are talking about a cross-functional team, this team is expected to support the business feature as well.

Now this is only a 7-member team - small and nimble and I am even suggesting that two of the roles (Analyst and Scrum Master) must eventually vanish for an even more agile transformation.

Do your Agile teams look like this?

A common complaint by enterprises in the Agile world is the potential risk of chaos that overwhelm an organization comprised of self-organized teams that want to do things on their own. So, while it is important to be self-organized to drive agility, it is equally important to drive Aligned Autonomy to prevent chaos while driving Digital and Agile at scale. The subject of Aligned Autonomy is a critical component of the Process dimension of scaling digital and we will discuss it at length in a later blog post in this series.

While it is important to be self-organized to drive agility, it is equally important to drive Aligned Autonomy to prevent chaos while driving Digital and Agile at scale.

But coming back to the importance of having a truly agile team, let me share a brief story. Not too long ago, I was asked to assess and analyze the problems being faced by a team, let’s call them Team Trooper, that claimed to be working on Agile for nearly two years, but were struggling to see any results. Their cycle times had stalled at a minimum of 12 weeks with no further progress on the ground. Naturally, business leaders had started questioning the effectiveness of Agile and were considering remedial measures. So I took on the ask and went in to meet the team. Walking into the room I was stunned to see nearly 25 people. According to the program manager this constituted a “cross-functional” team since they needed many people to deliver the feature. While there were multiple problems with the team, my first step was to get each team member’s competency evaluated to be a full-stack developer or T-shaped engineer

The Elite - Full Stack Developers

Full-stack has become the buzzword in the industry. Everyone prides in calling themselves a full-stack engineer. In a recent interview I conducted of a “full-stack engineer”, I asked him how he would create a web service in the language of his choice. His reply was: “In the Eclipse project you are working on, you need to go to Options Create Web Services, give a web service name with the parameters being asked for and click OK”. I am not an Eclipse expert and I don’t know if the Menu option he cited is correct but one thing I knew for sure is that this person cannot be a full-stack engineer.

My wife and I both come from a coding heritage, so it wasn’t uncommon for this topic to turn up in our dinner table conversations. Are we full-stack engineers or have we lost the sheen of being full-stack? Knowing the full extent of this term makes me feel that the software world has come full circle. When I used to code in C and later in JDK 1.2/1.3, I used to write front-end code (sometimes HTML or Javascript, and sometimes in GWT/Swing), middle layer code in Java, design the database, and write the queries or ORM mappings to interface with the data layer.

I used to be good at query optimization and could look at Oracle’s query plans and optimize my queries and table/index definitions for better performance. I used to write the build scripts, test my code, and get it deployed across all environments. Me and my friends in the team used to have our own internal competitions on whose code compiles first, number of first-time compilation errors, the code with zero defects etc. We took complete accountability for the feature we were working on.

However, over the past decade or more, the industry has begun focusing on creating specializations and made developers myopic in their focus. We now have Angular 4 developers who don’t know anything about middleware code, APIs, data handling mechanisms, simple SQL queries, build and deployment, testing and more importantly not even other UI frameworks. This has resulted in the need for more and more developers to realize a feature and has been the biggest obstacle in creating truly cross-functional Agile team. That was one of the problem with Team Troopers. So, what is a full-stack developer or what makes a T-shaped engineer? For me, a T-Shaped engineer is one who depicts three types of skills: Technical, Engineering and Behavioral.

Technical skill: This skill is like a “T” which depicts the intersection between depth of knowledge in an area of expertise and the breadth of understanding across all adjacent technologies. This person has the ability to test their code and is also capable of being able to build and deploy their own code. For example, a full-stack UI engineer is one who brings in the depth of knowledge in JavaScript frameworks like Angular/React/Backbone etc., while also understanding and being capable of intermediate coding skills in all adjacent technologies namely Java/.NET, APIs, NoSQL databases or relational databases. They also have the ability to write not only unit tests but also functional tests in Selenium or another equivalent tool, possess the knowledge of static analyzers like JSLint/SONAR, and also have the ability to build and deploy the code leveraging GIT, CI tool and a deployment tool.

Engineering skill: This skill is often overlooked these days and is one of the major reasons for Agile teams not being able to drive velocity and faster release cycle times. It is the ability of a developer to bring in appropriate engineering practices during the implementation lifecycle. Working through a distributed version control system by following the Boy Scout’s rule, Pull Request rules, branching rules and discipline, daily code merges, daily builds, continuous deployment, following SOLID principles, writing code that passes the minimum checks in static analysis in the first run, following Clean Code principles, appropriate comments in GIT, regular updates in the asynchronous collaboration tools like Slack/MatterMost, and also making good use of Confluence/Wiki for project documentation etc. All these skills are critical to achieve velocity. In the book “Drive”, David Pink calls this attribute as Mastery and I have seen many organizations call this Craftsmanship. This skill cannot be learnt, it has to be practiced and practice makes a developer perfect to master the craft of engineering.

Behavioral skills: Cross-functional and self-organized teams are realized only if every person in an Agile team exhibits the appropriate behavioral skills. It is tough to define these traits as it depends on the culture within each team. Empathy towards others, servant-leadership, collaboration, trust and transparency are the basic necessary attributes. Many in the industry misconstrue this to be a bunch of outspoken developers. If you have listened to Susan Cain’s Power of Introverts TED talk, it becomes evident that 2/3rd of the population is comprised of introverts. Thus, by having an incorrect expectation on the behavioral trait, enterprises end up losing the good full-stack engineers. Get the teams to decide if an individual is depicting the appropriate behavioral traits rather than an interview with a manager or an architect to make that decision. But to get an in-depth definition of behavioral skills, I have found the definition of skill competency levels in the Dreyfus Skill Acquisition model to be useful and appropriate.

Framework for Scaling People: Dreyfus in a Diamond model and Team Configurations

Scaling Digital and Agile requires common team structures and configuration to achieve Aligned Autonomy and common cadence. Common structures need a common skill competency model on which people can be evaluated and mapped. If we do not manage to do this, we will end up having teams looking different and producing different velocities which does not augur well for an enterprise that endeavors to drive agility at scale.

It’s been a struggle in the industry to objectively define and adopt a skill competency model for the software world. The technical skills are easy to categorize. It’s always the mapping of behavioral competencies that have been a problem and that’s where we have found Dreyfus model to be useful. You may read about this model in Wikipedia where it is well-explained. Some organizations have chosen to adopt the SFIA model which is also good.

We at HCL utilize the Dreyfus model as the lens through which we can objectively define people’s competencies across the three skills of technical, engineering and behavioral. And in line with the Dreyfus model, we map people to five levels of competency – Novice, Advanced Beginner, Competent, Proficient and Expert.

We at HCL utilize the Dreyfus model as the lens through which we can objectively define people’s competencies across the three skills of technical, engineering and behavioral.

We are also moving away from the traditional pyramid model of structures of team competency mix to a more Diamond shaped model. There is enough research in the industry that states that Diamond models are productive and cost effective when we measure cost per unit of work (story points or functional points or complexity points). Does the Diamond model look alike across the organization? No. Based on our experience, we have realized that every application/product/platform goes through a 4-step evolution process namely: Ideation & Prototyping, Minimum Viable Product, Built at Scale, and Retire. The configuration of the diamond, we believe changes through this lifecycle as depicted in the diagram shared here.

Derfus

Realizing the People Dimension for Driving Digital @ Scale

At HCL, we make use of a number of techniques to evaluate, on-board and upskill our engineers by evaluating them on the three skills of Technology, Engineering and Behavioral. Technology skill evaluation is mostly automated through the use of industry tools with some amount of pair programming thrown in for Competent or Proficient or Expert engineers. Engineering skill evaluation is also automated through our own proprietary home-grown tool. And behavioral skills are evaluated by getting engineers to participate in hackathons and through the constant evaluation of their ability to work in a team effectively.

One of the key benefits of having an institutionalized common competency model across the enterprise alongside an evaluation mechanism is that it can naturally become a career progression roadmap for people, helping them to take ownership of their own competency development. In this scenario, people are encouraged to upskill themselves by going through the evaluation cycle and proving themselves to have achieved the next competency level.

At HCL, we make use of a number of techniques to evaluate, on-board and upskill our engineers by evaluating them on the three skills of Technology, Engineering and Behavioral.

With the overall view of the above topics, any organization that wants to transform its people to drive digital at scale needs to take the following steps:

  1. You need to define your own Dreyfus model framework, across technical skill, engineering skill, and behavioral traits that is contextual to your business.
  2. You need to redefine your entire HR systems and their skill models to adapt to the Dreyfus model.
  3. You need to adopt an objective evaluation methodology that is congruent to your model/framework.
  4. You need to subject the entire enterprise to this evaluation process so as to reconfigure it to the standards of the new model you’ve defined.
  5. Reconfigure people into skill levels.
  6. Reconfigure teams into a specific diamond model based on the lifecycle of the feature

The process for transforming the People dimension within the organization can be a daunting exercise. But it is fast becoming an essential one that cannot be ignored. As every aspect of the enterprise becomes more digital, the challenges that come with it require the lifeblood of the organization i.e. its people to be prepared for the next generation of challenges and opportunities.

Organizations need to consider the above said models and define their framework based on their specific needs. They need to create the tools and mechanisms necessary to drive the evaluation of these models and examine their own enterprises against their chosen model. And finally, organizations need to take on the process of reconfiguring their structures and teams to follow the Diamond model of configuration for optimized velocity, growth and innovation.

By taking these steps, companies are guaranteed to benefit as they experience a more consistent structure across the organization and create a more consistent culture, where people exhibit the same behaviors and share the same engineering ethics and technology traits. This enables the organization to drive Autonomy, Craftsmanship, and Purpose among their cross-functional and self-organized teams.

So, all the very best in your endeavor to reconfigure the People dimension of Digital at Scale. In the next edition of this series, I will be discussing the Technology/Process dimension of scaling digital successfully. See you then!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Human intervention critical to futuristic and sustainable digital transformation

Social eminence June 11, 2021

Globalization 4.0 has brought to the fore the old adage of human vs. machines. At a time when digital transformation of industries is rampant, enterprises cannot afford to delay the leap of faith. In fact, Globalization 4.0 is encouraging adoption of technologies with an emotional quotient, a path that industries should tread in the foreseeable future. This means that incorporation of human-centric digital strategies in their business goals is essential to thrive and flourish.

Industry 4.0 is witnessing companies generating an overwhelming amount of customer data. But is it used in ways that are emotionally intelligent as well? While tools like AI, ML, RPA, IoT, and Big Data and Analytics firmly establish a digital ecosystem, only an inclusive approach can plug the holes that still exist. A human-centric focus will ensure a seamless process and greater productivity across the spectrum. Listening to customers makes a whole lot of business sense. That way you have more relevant products. By engaging design thinking to explore customer and employee interaction, more well-rounded products and services are created. The pain points, motivations, and desires in a culture that promotes innovative thinking, is precisely what is known as Culture 2.0.

A human-centric focus will ensure a seamless process and greater productivity across the spectrum

Design Thinking

With Industry 4.0 expanding the digital horizon, there have been business models and strategies that companies have experimented with. In the age of hyper-consumerism, everything boils down to optimal experience. In this context, Human-centered Design (HCD) or design thinking has emerged as a smart choice among industry leaders. This approach, as the name suggests, puts humans in the center of digital decisions, ensuring positive business performances as well as elevated customer and employee experiences. Design thinking being a process and an outcome, businesses can see drastic improvement by adopting this methodology and framework. Human-centered design is unique, innovative, and agile. It is also aligned with the salient goals of business expansion and diversification. The outcome of design thinking is increased productivity, collaboration, and quality seamlessly translating into improved user experience. Human-centered design is actually changing the way industries function. Even traditional companies are focusing on user experience as a key component when it comes to solutions for employees as well as customers. The goal is to create services that take customization to a whole new level. The trick lies in communicating the value of HCD, which is much more than creating pretty designs. HCD transforms and reimagines businesses by making them more design- and user-centric.

In the age of hyper-consumerism, everything boils down to optimal experience. In this context, Human-centered Design (HCD) or design thinking has emerged as a smart choice among industry leaders

Culture 2.0

HCD allows companies to move beyond experiments and implement changes that are result-orientated and sustainable. However, the need to change is often met with resistance arising from apprehensions. Digital transformation often raises suspicions among that section of the workforces that is primarily employed to deliver manual, repetitive tasks. With robots getting smarter in Industry 4.0, industries are faced with the genuine prospect of massive replacements. How to strike a balance? The organizational culture must shift from being an inhibitor to a facilitator.

It is true that culture is one of the least appreciated assets in many companies. Technology or not, there should be incorporation of purpose into the company culture and that has to be well-defined. This will help build a digital ecosystem that is highly tangible and valuable to customers as well as employees. It’s basically a host of shared beliefs and values that brings about a change in behavior. It’s imperative for the C-Suite to stand by the cultural fabric, which the employees will emulate in terms of behavioral changes, to serve customers better. It is important for the leaders to realize that culture can be the biggest competitive edge for their organizations. Your employees need to stay inspired if you want to delight your consumers. This culture needs to be designed with all sincerity. But this is an incremental process. You need to be patient and persistent to ring in the changes that are crucial for successful digital transformation.

Human Intervention is Irreplaceable

Globalization 4.0 sheds light on the need to establish a synergy between humans and machines. Human intervention remains critical to how machines perform. The human perspective to problem-solving is multidimensional and is more apt for decision-making. While machines get smarter on the back of more exhaustive algorithms, human intervention in Industry 4.0 will not turn redundant. At HCL, our digital transformation capabilities are in line with this principle.

To meet Anand Birje at World Economic Forum 2019, visit here.


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Infusing cultural intelligence in analytics to drive customer centricity

Social eminence June 11, 2021

Perhaps the best way to describe cultural intelligence is to first state what it is not.  Typically, cultural intelligence is defined as “the capability to relate and work effectively across cultures”. This isn’t necessarily what I’m talking about. In the context of this article, cultural intelligence is the discipline that helps enterprises understand what is happening in culture as it relates to a brand, its products, its employees and most importantly its customers.

Cultural intelligenceCultural intelligence helps us find the human signal through all the market noise. It allows us to gain a deeper understanding of the customer, their communities, and their base-level drives which are integral in shaping their values, beliefs, and motivations. This information is discerned through a careful analysis of the cultural moments, trends, and fads which differ between cultures, and are critical in helping organizations shape their relationships with customers.

Case Studies in Cultural Intelligence

Let’s take the recent case of the Pepsi-Protest commercial that shows what happens when firms are not aligned with the cultural zeitgeist. The commercial, from Pepsi’s Content Creators League ad agency, shows reality celebrity Kendall Jenner magically settling a standoff between protestors and police by offering an officer a can of Pepsi. Immediately after its release, it sparked outrage and controversy, being rebuked on social media, and even being parodied on Saturday Night Live.

It’s no surprise then that it was promptly pulled from the air.

The mistake Pepsi made was one of cultural intelligence. The brand knew that political protests were on their core demographics’ radar. They knew that young people, more than any other segment, were activated and engaged with this nation-wide social phenomenon. And they thought they could tap into that vein to connect with them. Unfortunately, they made the mistake of stopping at “protest”, instead of delving deeper and understanding the reasons behind it. As a result, they ended up telling a story that offended, rather than inspired all potential consumers.

In contrast to Pepsi, there are many other brands who we can cite as positive examples that have executed such acts of marketing with elegant and sensitive cultural intelligence.

Nike sales Nike, which has a history of provocative marketing campaigns – from the “What will they say about you?” campaign for Middle-Eastern women to sponsoring Chris Mosier - the first Team USA transgender athlete. In the most recent case, Nike decided to capitalize on a very tangible cultural tension which exists in the US today by unveiling NFL quarterback Colin Kaepernick as the face of its brand during the League’s season kick-off game over Labor Day Sunday. The ad was met with overwhelming polarization but within two days Nike sales surged 31% and polls showed that the ad resonated positively with Nike’s core demographic.

So while companies have much to lose when attempting to connect across cultures and mindsets, it is more than worth it if it’s done with sincerity and sensitivity. Through a unified understanding of business, consumer and market a company can extract actionable insights and make sustainable plans for improving sales. Generally speaking, this thoughtful approach to cultural intelligence can help companies discern the following critical insights:

  • understand the customers’ demographics, location, opinion, relationship, and social network surrounding their brand.
  • understand how people are speaking about their brand and the shifts in perception of the equities that really matter to their audience.
  • understand how customers differentiate their products against a competitors and why
  • understand and anticipate the viability of an established sales strategy based on the marketplace demand (pre-lead) and whether the company is poised to capture existing demand relative to the competition.

Cultural Intelligence – A Business Imperative

Cultural intelligence helps us find the human signal through all the market noise..

Cultural intelligence isn’t simply about understanding the customer in a more meaningful way.  Companies and Brands must innately know who they are and confidently stand for more than just their product. Ideally this is drafted as an easily articulated and understood statement of what the company or brand believes in. Rather than being a piece of aimless motivational garbage, what I’m referring to expresses something that tends to resonate deeply and employees would not feel awkward discussing it over coffee or with their partners across the industry. 

Companies and brands must innately know who they are and confidently stand for more than just their product.

Most agree that this concept is very much different from the typical enterprise vision, goal or mission statement they’re used to. For example, most mission statements simply attempt to announce in one way or another that their brand is about more than simply making more profit for their shareholders.  However, as valuable as mission statements are, great brands tend to be built on underpinning values that give guidance to all aspects of brand and company activity.  They project a certain point of view on the world that engages people, both within and beyond the organization, as they radiate the values and commitment needed to bring their vision to fruition. 

For instance, Microsoft aim’s to make the planet smarter and improve lives by harnessing the power of artificial intelligence. Another such example is Nestle Japan and their commitment to act on the principles of “Creating Shared Value”, as a way to engage with socially relevant fields like nutrition, health & healthcare, rural development, environmental sustainability, and human rights in their local value chain.

I call this concept an “exemplary commitment”. It gets at something authentic and real, and as a consequence helps brands tap into what matters to their customers the most, as they take a market leading position.

Creating an “exemplary commitment” is not a silver bullet for driving brand growth or doing great communications, however it can be extremely helpful when it’s deployed correctly, and is useful in such situations:

  • when an organization needs its purpose articulated
  • when the company’s market lacks a thought leader
  • when a brand or company needs greater cultural connection

Brands need an extremely practical tool that can help them realize the power of their purpose, and use it as a means to guide the overall direction of their marketing and communications issues. This starts by staffing the right talent and integrating 3 seemingly separate disciplines into one team with a shared mission of better connecting their brand at a deeper level with their customer’s values. These three disciplines are:

  • Anthropology: a team of experience designers focused on exposing what connects consumers, critics, and culture to content and media.
  • Economics: a team of economists focused on understanding the relationships between those connections and valuable behavior indicators.
  • Analytics: a team of data scientists focused on establishing the calculations and algorithms that allow us to anticipate those behaviors.

At work when I speak with companies and help them use cultural intelligence to their advantage they usually get it right away. The concept itself is not particularly novel or ground-breaking. The challenge however is to scale their intelligence gathering in relation to what’s happening in culture (i.e. tap into the cultural zeitgeist) and act upon it in a way that authentically aligns with their brand’s purpose and commitment. In other words, how to take one successful site or campaign launch and replicate that success across multiple business units and a myriad of product lines.  What if things change with the customer base (as they invariably do) mid-rollout?

Today, companies and brands put too much effort towards rough ad hoc qualitative analysis that struggles to keep pace with the rapidly changing landscape of cultural connection and trends. This is where the power of analytics and cultural intelligence makes for an interesting thought experiment. Analytics has allowed businesses to quantify and model vast quantities of data and decipher meaning out of the chaos. It is at the intersection of cultural intelligence and analytics where we find the discipline of cultural analytics to emerge.

Cultural Analytics

Don’t get me wrong; cultural analytics is not necessarily a novel idea in the broader scheme.  It exists today, albeit still in its formative stages and has yet to be fully tapped by business. Cultural analytics is being developed to help organizations discover shared value systems from the pattern of behavior witnessed in managerial decisions, employee behavior, and companywide operational procedures.

By quantifying these data sets and applying analytic modeling solutions, we can understand and predict the organizational decisions and behaviors for the future. Or at the very least, shed light on currently existing problems and devise the means to solve them.

This is exactly what German company Multigence claims to do – use technology solutions to measure and evaluate individuals and groups – to better establish a cultural fit. Another example is the ad agency Sparks & Honey that evangelizes cultural intelligence and its infusion with technology with their in-house proprietary tool “Q” – an active learning system that deciphers signals and patterns within unstructured data to generate insights.

Currently, each of these solutions only targets a very specific and relatively controlled domain within culture and business. The Multigence Cultural Profile tool is able to measure, evaluate, and match a company’s culture with employees, candidates, and even other organizations, while Sparks & Honey observes consumer markets for cultural shifts and trends for marketing campaigns.

And while much of this may seem like science-fiction, we have only to look around at the significant progress being made in the field to realize that the era of cultural analytics is nearly upon us. Consider the groundbreaking work being done by Michel and Aiden, Harvard-Google data scientists in the development of Culturonomics, a field of study that deciphers human behavior and cultural connection and trends through the quantitative analysis of digitized texts thanks to computational lexicology.

This method of analyzing culture via language has tremendous potential on the social web where the overwhelming exchange of publically shared communication is via text. And while, culturonomics is far from a perfect system, it has proven successful in retroactive predictive studies that covered the Arab Spring, demonstrating its rigor and validity in the real world.

Cultural Intelligence in Analytics and Customer Centricity

I imagine a cultural analytics system that is able to untangle the much larger web of human interactions in an automated and user-friendly manner, across dimensions and use cases. With next-generation cultural analytics, we will be armed with an unprecedented, deep-rooted understanding of organizations and people like never before.

We can imagine a simple framework that demonstrates how scalable cultural intelligence would work in an organization by referring to the illustration below:

illustration

With this degree of cultural nuance factored into strategic business simulations, organizations will be able to offer their customers an empathetic and human connection unlike ever before. Businesses will be able to simulate how business decisions and strategic operations will play themselves out in the real world and take steps to engage them.

In the not so distant future, pioneering 21st century enterprises will lead the way in cultural analytics, using it as an essential tool in the creation of a truly customer-centric experience. The only question that will remain then is – will you be one of them?


david.sogn_319532's picture David Sogn October 18
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Associate Vice President – Digital & Analytics

Scaling digital across the enterprise: the key imperatives

Social eminence June 11, 2021

Digital technology has opened up new ways of doing business and has transformed the way enterprises manage their operations and create customer interactions across the value chain. From selling books to selling financial services – every business is now a technology-led business. It’s no surprise that more and more enterprises are launching digital initiatives to realize business model innovation and topline revenue growth. In fact, analysts have predicted that around $2 trillion dollars will be spent in 2019 worldwide on technologies.

According to a study by Harvard Business School, leading digital companies generate better gross margins, better earnings and better net income than organizations in the bottom quarter of digital adopters. The stakes are high in the race to achieve digital leadership. But dig a little deeper and cracks start to appear. Digital initiatives undertaken by many organizations are often in response to narrowly defined issues and exist in isolation from any comprehensive digital transformation strategy.

The Struggle with Holistic Digital Implementation

In a of large organizations, 78% of the respondents said they are implementing discrete digital projects and, amongst those that have a formal strategy, 46% encompass the business partially. In other words, initiatives are isolated which do not result in transformational innovation. With such piecemeal projects, enterprises often fall short of the desired outcomes and instead must contend with minor digital upgrades. The result- no discernible gains for the organization. Imagine an mobile application, which provides a great user experience and is used by customers to book tickets. But when the same customer goes to complain about his/her missing bag, the airline executives don’t have an answer. This is a classic example of a company that couldn’t recognize the holistic implication of its digital initiative and as a result, failed to digitize its end to end processes.

For organizations to truly transform themselves digitally, they cannot have pockets of brilliance intertwined with legacy applications, processes and old ways of working. So, the million-dollar question is- how can companies scale digital transformation across the enterprise whilst dealing with the challenges and the complexities of the journey?

Culture Propels Digital Change

I’ve always believed that scaling digital adoption is as much about reimagining technologies and processes as much as it is about cultural transformation. Digital leaders around the world are characterized by embracing technology as a driver of business success pivoted around a culture that enables innovation and reinvention. Suffice to say, cultural change lies at the very heart of a successful digital journey and is often larger in magnitude than the seemingly complex technology transformation. To adequately capture value from the digital investments, a flexible and open-minded culture must spearhead the technology and process transformation. Such an approach often yields new and innovative business models unheard of before.

For instance, a pizza company wanted to engage with its consumers not just at the time of delivery but before and after that as well. So, they created an algorithm using video analytics and graymatics to involve customers in quality grading the pizza, where users upon delivery took a picture and the algorithm graded the pizza on toppings, its placement, quality of cheese and other dietary parameters.

There are many such examples of companies leveraging digital technology to create game-changing innovation. But that’s not to say that scaling digital is unchallenging or straightforward. Enterprises must have in place the culture, the tools and the execution engine to be able to move beyond barriers to digital change and execute on their digital strategy.

The Prerequisites to Scaling Digital

Having led multiple large scale digital initiatives spanning organizations and industries, I’ve noticed that even the best implementations tend to overlook some essential areas. I believe that while it is easy to get started with digital, getting them right requires business leaders to keep a few critical points in mind during their digital transformation journeys.

Reimagine the supply chain of digital talent: Digital talent deficit is a major reason why enterprises fail to realize their digital strategy. Demand far outstrips supply, and most enterprises find it hard to bridge the talent gap. Our survey indicates that 44% organizations see ‘lack of internal skills’ as the biggest barrier in digital transformation. Scaling digital requires new talent, including full-stack engineers trained in new and emerging technologies and product managers who understand what customers want. The war for the top digital talent can only be won by reimagining the acquisition strategy and leveraging innovative practices such as hackathons, and programming challenges as well as -based technologies & platforms to identify, evaluate and train the right people, at scale.

Embrace an Agile-first, DevOps-led approach: Many traditional organizations are unable to break-free from the gravitational pull of their legacy roots and often struggle to ‘cross the chasm’ to digital reality. It takes experimentation, an assumption of risk and a change in approach to turn around the digital fortune. That’s where an Agile and driven approach makes the difference. The changes fostered by Agile and DevOps methodologies ensure a strong, flexible, and dynamic reformation of the organizational culture and leads to holistic transformation from the top-down.

Create composable and insights-led platforms that scale digital execution: It’s not a stretch to say that digital platforms and applications are what make digital-led business transformation a reality, through the power of platform innovation and application modernization. As markets and digital technologies continue to evolve, API-first, microservices-driven, modular, highly available and business-ready platforms have become a prerequisite. Another key consideration must be infusing data-driven insights into the overall digital platform design. Only by giving data its due importance can enterprises fully unlock the potential of digital platforms and create unified experiences to realize digital-led outcomes.

Fully leverage the digital eco-system: Digital disruption can come from anywhere today and business leaders are under tremendous pressure to get transformation projects right. That’s where expert partners can bring in a huge amount of experience, quality, and resources to a digital transformation initiative, in capabilities which enterprises find hard to source within the organization. That’s why investing in a meaningful partnership strategy is beneficial and cost-effective in the long run.

Digital is the ‘new normal’ for global enterprises and an opportunity to continuously improve the organization in innovative new ways. But scaling digital is not without its challenges and pitfalls. It may be worthwhile for CIOs and digital leaders to consider some of the above strategies as they continue to evolve on their digital journeys.


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

How to successfully scale agile and devops - part 1

Social eminence June 11, 2021

I began my journey into scaled digital and transformation nearly a decade ago. My first encounter with Agile at Scale was at one of the world’s largest global aircraft manufacturers. On day one, the task before us looked impossible to achieve, however the results of following the Agile way allowed us to deliver on-time. It was in that moment that I knew that the world of the future was going to run on Agile models.

And my belief has been validated because today, over 97% of organizations practice agile development methods in some manner or another, while the number of people working in DevOps teams has risen from 16% in 2014 to 27% in 2017. Agile DevOps have truly become mainstream. However, in the last couple of years we’ve also seen many organizations struggle to scale up operations with these methods.

Today, over 97% of organizations practice agile development methods in some manner or another

With that context, I invite you to join me on this blog series as I share my experiences and learnings on addressing the challenges of scaling agile and DevOps in this series on “Scaled Digital”.

Challenges in Scaling

About three years ago, I served as a subject matter expert and advisor on agile development for one of the world’s largest banks. The client had built a state-of-the-art, business critical trade settlement platform with a small co-located, team. The client CIO had mandated them to make this a global platform and sunset regional specific platforms for the purpose of cost optimization and to harness cross-selling opportunities. To achieve this mandate, the client needed to accomplish a number of goals – to scale their team, to distribute them across the globe, and to maintain the speed and quality with which the development pipeline was already running. The client had tried this with their own captive in India, as well as with many other vendors, however, they could not manage to on-board even a single agile development squad successfully.

It was a grim situation. They relied on this platform as a critical revenue generator since it managed high volume transactions for their investors. As a business-critical tool, uptime and stability was integral, considering that gaps of milliseconds could leads to millions in potential losses. The client had already spent over two years on failed ventures with other technology partners before they approached HCL. Our team spent some time on their problem and came to understand this as a “people problem” issue and within six weeks, we had managed to on-board a team that satisfied the customer’s expectation.

As a business-critical tool, uptime and stability was integral, considering that gaps of milliseconds could leads to millions in potential losses

This experience was a seminal one for me. In the next 3 months, I got into many such conversations where customers were struggling to scale their . It highlighted what would soon become established fact – agile and DevOps solutions faced unique challenges when they were scaled up. These challenges in scaling, as it turns out, are far too many and as varied as the organizations implementing them. However, the common truth among all was that while methodologies improved outcomes within teams and projects, they failed when aggregated across the enterprise at scale.

Unsurprisingly, the problem areas were usually the same - from a discordance in organizational culture to issues with different agile development models adopted to geographically distributed teams utilizing varied delivery methodologies to monolithic architecture in legacy technologies which are rigid to change to sourcing models which hampered collaboration resulting in disjointed performance management systems, I’ve seen them all in my career. And having worked on solving such problems for companies around the globe, time and time again, it has become clear to me that the issue in the industry is not about ‘adopting’ Agile or DevOps, it is about ‘scaling’ digital, both Agile and DevOps methodology included, and getting the entire enterprise to run at speed.

Enacting Change Across Dimensions

The simple fact is that agile and DevOps methods can’t work in isolation. Organizations cannot hope to reap any benefits unless they take a holistic view of their businesses. Sure, it’s certainly easier for specific divisions and projects to leverage these methods for themselves. But the positive outcomes will be diluted if the rest of the overall organization remains rigid and resistant to change and cannot run at the speed of the digital corner.

I firmly believe that this scale digital problem has to be driven in parallel across the three dimensions of People, Process and Technology enabled by a strong Organization Change Management (OCM) drive. OCM needs to be able to engage and transform all levels of the organization both top-down and bottom-up.

OCM needs to be able to engage and transform all levels of the organization both top-down and bottom-up

The top-down approach is about mandates and strategy definition and leading by example. I have been through examples where CIOs have run their townhalls in sprints, contracting was done in Agile sprints with autonomous and empowered contracting squads, and KPI definition across partners in a customer enterprise was done leveraging SCRUM. It begins with creating focus groups who are mandated to drive this change. Focus groups need to have representation from all parts of the organization where this change needs to be done, especially representation from business, as Agile done in silo within IT would not yield the value that we would expect from its adoption. Marketing and communication management is equally important especially from senior management whose communication is essential in order to drive the journey faster. This change journey needs to be directed by both Agile and DevOps coaches who are also part of the focus groups.

In the bottom-up approach, People, Process, and Technology - each of these three dimensions play an integral role in ensuring a successful, ground up, and sustainable transformation for any organization. If you want to get your teams to be Agile, have the ability to deploy code into production daily, follow lean budgeting and have a squad with zero scrum masters and zero testers, and have an enterprise with zero support, then hang-on for the next set of blogs where we will get in to the really exciting part of this series.

In the next blog post, I will focus on the People dimension to detail out how to evaluate, identify and train people with the appropriate technical and behavioral competencies to drive Digital at scale.

I look forward to seeing you soon!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Transform your digital data eco-system with a data fabric approach

Social eminence June 11, 2021

Organizations that were innovators and early adopters or had previous implementations began with a focus on incubating new technologies. This led to use case-based deployments that were built from scratch, primarily in the greenfield mode. However, the situation has begun to change.

Enterprises are becoming more distributed even as they continue to remain even more connected. By leveraging cloud-based data driven analytics, these organizations are tapping into new dimensions through which they can leverage data for better insights. In fact, we at HCL have used these principles for many of our customers across a number of varied industries, to drive maximum business value from data transformation platforms. Among many others, we are proud to count for a US-based telecommunications giant, a leading market research company, and a Europe based financial services enterprise as satisfied customers.

Today, most enterprises are either in the process of moving or have already moved towards scaling digital across all lines of businesses. This is particularly true in scenarios where analytics and data scaling initiatives need to align to new business models. Organizations are now working overtime to ensure this sync by modernizing their legacy systems by adopting new system architectures and principles.

Clearly, the time has come for organizations with heavy investments in cloud and big data ecosystems to reimagine their traditional architecture. Rather than continuing to create monolithic platforms, companies need to focus on a connected data ecosystem where big data, cloud, hybrid and traditional can coexist in mutually-beneficial harmony.

The New Paradigm

There is little doubt in my mind that we are witnessing a paradigm shift in the digital data ecosystem. The increasing focus on ensuring that data remains federated while staying connected is one of the critical features of this change. This shift has led to the integration of advanced technologies like artificial intelligence and machine learning into data management and operations, leading to increased business value from data.

At first, businesses were simply incubating big data capabilities in dug-in silos for use primarily in their point-use cases. Over time, businesses began to experience the benefits of distributed and connected systems and moved towards cloud data ecosystems offered by players like Azure and AWS. But the overall approach remained siloed and modern cloud-based implementations typically occurred in isolated pockets across the enterprise. Now, however, organizations no longer want to be constrained to a point-use case solution. They want to deploy these ecosystems across the enterprise level.

Our own big data and cloud analytics customers are now asking us to help them scale-up these pocket ecosystems. Today they want to leverage digital across every line of business in their organizations. This is no surprise. After all, data ecosystems connected across digital platforms enable businesses to execute multiple use-cases and potentially generate exponential value from their data assets. In addition to scaling up their digital data ecosystems, future-facing organizations also seek to leverage Agile and DevOps processes across their data ecosystem. And this is what makes this new paradigm such an interesting challenge.

So how do we bring all these potential capabilities together and connect this distributed ecosystem in such a way that it helps companies drive digital innovation & business outcomes?

Data Fabric: Taking Data to Scale

I like to think of this new seamless ecosystem as a Data Fabric, where each thread is a data set with its own capability. Together, these multiple threads are woven together to create a new functionality. This is the entire crux of this paradigm shift. The key goal is to make data more accessible, faster, and actionable. And we can accomplish this through automation, simplicity, repeatability, and discovery.

Adhering to these four tenets can ensure that a large data ecosystem remains stable as it is scaled up and out. From our perspective, a modern Data Fabric architecture pattern is the key to connecting application performance with application functionalities. Businesses can reduce data ingestion and preparation time in one go by utilizing a rapid pattern-based development approach. Thereby, a Data Fabric approach can be used to encompass any scale of data and origin while honoring its unique sensitivity.

A Data Fabric approach can be used to encompass any scale of data and origin while honoring its unique sensitivity.

In real terms, the Data Fabric approach can allow businesses to speed up their data warehousing processes and allow for a single harmonized visualization of their operations across the enterprise. Additionally, they can also reduce overall costs in the immediate term and benefit from minimal incremental expense as the organization continues to grow.

Case Study: Wireless Operator Deploys Data Fabric to Gain a Single View of Customer

The benefits of this approach are best explained through a real-world example. A leading wireless network operator in the US, with over 70 million customers, was looking for any way to gain an edge on their competition. They partnered with HCL to help them achieve this goal.  We were well aware that the market was fierce and mature, and that the client needed a data-driven strategy that would allow them to offer unique, customized and tailored offers & promotions to their customers, leading to market disruption.

For this they would need to consolidate over 80 distributed data sources, with over 1.7 petabytes of data, while also managing the daily incremental load of ten billion records. HCL helped them establish a next generation solution that wasn’t just another monolithic silo. So, we developed a data lake designed for business intent that was drawn from a number of distributed data lakes within the enterprise.

We employed a Data Fabric approach, like the one described earlier, that connected these disparate sources. Through it, the client was able to ingest, harmonize, and create visualizations of the raw data from across a centralized platform for sharper business insights.

HCL also helped the client establish a Transformation Library. This library consisted of reusable data transformation functions, as well as a Data Catalogue that enabled business users across departments and functions to centrally access data sets. A key value addition in this project was HCL’s creation of a sand box environment that allowed our client to perform data discovery and execute preliminary advanced analytics.

The results of these transformations were remarkable. The client was able to rapidly compile numerous and disparate data sources and use them to analyze new business models for marketing and operations. Further, the use of an Agile Analytics approach enabled the rapid execution of new promotions from inception to delivery as well as monitoring within a short period. Overall, the client was able to gain a single unified view of their customer, which enabled them to make processes like billing, plans, promotions, and devices a pain-free experience, leaving both customers and the business, delighted.

Scaling New Heights

In an increasingly competitive and cutthroat marketplace organizations need be able to leverage data to make lightning-fast decisions. With petabytes of information amassing over time, companies need this data to become more easily available, accessible, consumable, and actionable - centrally. The complexity of data adoption at scale needs solutions not just within certain pockets but on an enterprise level.

Only through an effective data scaling strategy can organizations gain the right insights and solutions which will allow them to learn fast and act faster. From using social data to gauge the effectiveness of a new product launch campaign, to assessing real-time data generated from devices in clinical trials for testing and proof, and even in providing well-defined and prompt responses to queries for regulatory mandates, fast and accurate data is key.

HCL’s digital at scale propositions have already enabled a number of organizations to successfully execute such transformations.

HCL’s digital at scale propositions have already enabled a number of organizations to successfully execute such transformations. With our DevOps based operating model, and our Data Fabric approach, HCL’s solutions are aimed towards engineering a large data transformation landscape that also modernizes legacy and traditional data ecosystems. This is the summit of digital transformation that modern enterprises need to conquer.


venkatakrishna_c's picture Venkata Krishna C September 26
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Global Solutions Lead - Data and Analytics

The 3r framework: a business first, technology second approach to digitization part 3: reimagine customer experience

Social eminence June 11, 2021

Our first post of the series introduced the 3R Approach to Digitization and its three dimensions, i.e., Rethinking products and services, Reimagining customer experience, and Re-engineering the value chain. Then we dove into the first step of how enterprises could drive digitization by rethinking products and services. In this post, I’ll be discussing the second step of the 3R approach – reimagining customer experience.

In today’s technologically disruptive world, it isn’t enough to simply provide an amazing product. Customers want more. They demand experiences that engage and amaze them. This shift in consumer expectations has already impacted business culture and strategies across industries.

If we rewind the clock a couple of decades, we can see how this shift began. Before Google was synonymous with ‘search,’ searching was an imperfect activity. Most people would target specific websites or stumble across links through other means, with no clear assurance of what they would find. Early search engines opened up the World Wide Web and made it easier to explore but the results were far from perfect.

Google radically transformed this activity. They reimagined the search engine into what we take for granted today. What differentiated Google wasn’t just its speed and effectiveness, but also its simplicity. Google showed the world that there was a better way to search — a way that was simpler, faster, and more effective.

Reimagining customer experiences has powerful outcomes and benefits for any business. It can turn users into evangelists, and products into indispensable, permanent fixtures of normal life.

Just ask Google, Apple, or Tesla.

Each of these companies designs their products and services with the customer as the sole focus. They dominate their competition by integrating the values of humanism, design thinking, and customer centricity into the technology of their products, resulting in a customer experience that is unparalleled.

As personal technology has evolved, so have the challenges for enterprises. Users have advanced from desktops to laptops to tablets and smartphones, and this intimacy of technology has given rise to a whole new generation of consumers.

Businesses who wish to win over these digital natives have to learn how they experience their products and interact with technology. Organizations that have predicted, and even directed, these user preferences have experienced immense success. The most famous example is Apple’s reimagining of the cell phone with the iPhone and music with the iPod. The result of Apple’s innovation is soaring profits from USD 38 million in Q1 2001 to USD 565 million in Q1 2006 to a staggering USD 20.1 billion in Q1 2018.

Clearly, rethinking products and services, along with reimagining customer experience can transform a company’s bottom line.

Reimagine the Power of Voice

As we’ve seen, in less than 10 years, the preferences for personal computing has transformed from desktop systems to mobile smartphones. The interface evolution with technology has been a defining attribute of customer experience and continues to evolve.

We are already witnessing the rise of one such branch of evolution — the rapid emergence of voice assistants, which have gone from our cell phones into our homes. Users can now simply ‘tell’ their machine learning and AI-powered assistants to execute a number of everyday tasks – from ordering groceries, making appointments, playing music, or simply controlling the household light and heating.

Products like Amazon’s Alexa and Google Home are the embodiment of simplicity, seamlessness, and, most importantly, a sophisticated and invisible technology doing its work unobtrusively from behind the scenes. The emphasis on delivering back-end technological sophistication via an elegant interface is what has made voice assistants an increasingly desirable product. Furthermore, the convergence of AI-powered natural language recognition with personal voice assistants has already put us well on our way to a new commercial segment — voice commerce.

Already, nearly 20 per cent of US consumers have made a purchase through voice e-commerce, while over 33 per cent are planning to do so in the next year. And as NLP technology progresses beyond the 70 per cent accent recognition, it may become a commonplace global phenomenon in less than five years. To buy something, simply ask for it.

Adapting Technologies

We’re witnessing similar technology convergence developments on the road. Take the case of personal transportation with companies like Tesla. The technology behind Tesla’s self-driving cars possible is built on the same principles as those used by SpaceX for the automated landing of their rocket boosters. Technology is being adapted across industries to reimagine customer experience and launch a new era of innovation.

In areas such as retail, we see similar examples of reimagined customer experience forging brave new paths. Today, a consumer can walk into an Amazon Go store and pick up their groceries and simply walk out.

Other companies such as Alibaba are approaching the same problem from a different angle. Alibaba’s Hema chain of supermarkets are hybrids of offline and online systems that seek to make their mobile app the heart of the shopping experience and reimagine both domains. By fusing the offline and online experience through a customer’s mobile device, Alibaba placed the power in the customer’s hand and gave them a unified yet flexible experience. For markets where the costs of large-scale technical investments are prohibitive, this hybrid approach may prove to be an innovation that serves billions.

Reimagine Leadership

Executives need to be the ‘imagineers’ of their products and services, always pushing beyond the now, and envisioning the future from a customer’s perspective.

The ability to rethink products and services and reimagine customer experience successfully opens up a world of opportunities for businesses. However, neither of these paths to driving digitization can be successful without the crucial final step.

Join me in the next and final blog post of this series, as we discuss the most important part of the 3R approach to driving digitization – reengineering the value chain.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 2: rethink products and services

Social eminence June 11, 2021

In our first post, we discussed the hurdles enterprises encounter in their efforts to address changing customer expectations and evolving technological paradigms. We introduced the 3R approach to digitization and how its three dimensions - rethinking products and services, reimagining the customer experience, and reengineering the value chain - the essential components to enable effective enterprise digital transformation.

In this article, we’ll be discussing the first step of the 3R approach - rethinking products and services.

Rethinking Products and Services

The world today, unlike a couple of decades ago, has dramatically transformed with the proliferation of the internet. A shift in consumption patterns has been witnessed. This has affected both businesses and customers in a fundamental way. Smart devices such as cellll phones allow them to interact anywhere and at any time. Several other technology advances are driving fundamental changes in these interactions.

Rethink to Adapt, Innovate to Survive

Under such circumstances, it is imperative for companies to rethink their products and services — not just for the imperceptible future, but for a present that’s already prevails.

There are several instances where enterprises have struggled to transform. Laggards like Blockbuster and Borders Books failed to rethink their value proposition beyond traditional models and were driven to oblivion.

it is necessary for companies to rethink their products and services - not just for the intangible future, but for a present that’s already here.

Today, physical books and music are a waning commodity, and renting or buying has given way to newer models like subscription. This shift is a testament to the revolutionary impact of technology on business. Companies that were unable to adapt in a timely manner lost the battle of technological evolution to upstarts such as Netflix and Amazon. These modern day behemoths are working twice as hard not to repeat the mistakes of their predecessors. Each company spends millions of dollars annually in product innovation, research and development to ensure they keep pace with the new emerging trends.

Technology lies at the core of rethinking existing products, developing new ones, and facilitating services that can address market demands —even those that haven’t been realised yet. Case in point, the digitization of music on iPods by Apple. Rethinking products and services has the potential to create new markets and fresh opportunities. The challenge is not to simply adapt quickly but to proactively define the next wave of change.

Discovering the Business Case

Earlier, running on a treadmill at the gym meant having to frequently look at your wristwatch to measure your progress. Today’s treadmills are more sophisticated, can track the time, distance covered and offer estimates of the calories burnt and your prevailing heart rate.

But how will you measure these metrics when you’re off the treadmill?

With a technology-enabled wearable device such as Fitbit, you can easily access this information throughout the day. From heart rate to quality of sleep, and the number of steps climbed, it is all readily accessible on your wrist.

We can conclude that a business’ ability to predict customer needs and rethink product development from the perspective of customer experience is the key to future survival. Companies that can rethink an ideal business case for their existing or new products and services will continue to stay ahead of the competition.

Rethinking at Every Scale

This rethinking has to be enabled at each level. Small, incremental changes throughout the process workflow can yield significant productivity and efficiency gains for the business, while giving products and services an edge they didn’t possess before. Consider how IoT-enabled smart trackers on individual products and vehicles can transform various aspects of a business.

With access to real-time information, businesses can map and monitor the movement of goods across delivery routes. This helps them accurately estimate the exact delivery date and time for their products, and manage their inventory more efficiently while optimizing customer fulfilment operations.

Organizations can save on resources with accurate inventory and logistical management. These savings translate into significant contributions to the bottom line while increasing the speed to market (STM) and driving customer satisfaction.

Revenue-growth management (RGM) plays a critical role here. Companies are increasingly investing in Big Data, advanced analytics, and other RGM technologies to ensure they stay ahead of the curve. Exploring the use of such technologies throughout operations has to become an integral part of how companies expand their capabilities and rethink their products and services.

For large global enterprises, their vast size and scale of operations can be limiting factors to such initiatives. A simpler solution for them could be to acquire or merge with firms that offer existing capabilities that complement their core competencies. This has been a commonly observed trend among companies which focus on transformation. Examples include Disney’s merger with Pixar over a decade ago, and the AT&T and Time Warner merger that is currently underway.

The Next Step

Exceptional companies have woven this idea into their DNA. Apple is actively developing self-driving cars —an area beyond its traditional domain but powered by technology which is its core strength. Similarly, Amazon, along with JP Morgan Chase and Warren Buffett's Berkshire Hathaway, is planning to make inroads into healthcare— once again leveraging Amazon’s core expertise of technology.

The future of consumer-facing industries largely depends on how they innovate. Organizations need to keep track of minor changes in customer behavior because they often foretell major shifts in business.

The impetus to rethink products and services is driven by exploring methods of making products more efficient, engaging and ultimately, human-centric. The core of any business has always rested on how well they delight their customers. The only thing that has changed is the approach to realize this objective, owing to which rethinking products and services is essential to driving digitization in any company.

In the next part of this blog series, I will be focusing on how driving digitization calls on organizations to “Reimagine Customer Experiences”.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 4: reengineer the value chain

Social eminence June 11, 2021

In my first post, I explained how the 3R Approach offers an ideal framework for organizations to orient their digitization and innovation initiatives through Rethinking products and services, Reimagining customer experience and Re-engineering the value chain. We discussed in detail the first two steps in previous posts. Today’s post is on the third and final step of the 3R approach – reengineering the value chain.

Looking Inwards to Move Forward

Businesses that have stood the test of time are built on a foundation of complex systems that come together to create value. Most modern value chains are discrete and organized into silo-styled stages around divergent operations such as market research, product development, marketing, manufacturing, distribution, and ultimately customer service and engagement. While the traditional methodology of business has given rise to these siloes, digitization is well on its way to dismantle such barriers.

While the traditional methodology of business has given rise to these siloes, digitization is well on its way to dismantling such barriers

New systems that are built on the values of digitization demand end-to-end integration across the value chain. At the end of the day, the transformative power of ‘rethink’ and ‘reimagine’ is meaningless unless they align complex business functions through standardization and automation techniques.

Enterprises now have access to cutting-edge tools and technologies that can help them execute this approach effectively and have complete clarity of their own operations. Key technologies such as the Internet of Things (IoT), machine learning, artificial intelligence (AI), analytics, automation and robotics, have utility across business operations in proven ways. These tools can transform various enterprise technologies, such as autonomous logistics, integrated planning and execution, logistics visibility, procurement, and warehousing management, into more optimized solutions.

The integration of technologies across the value chain enables organizations to greatly enhance their decision-making power and potentially even predict change. By capturing data at every node and action junction in the value chain, leaders become more prepared to manage disruptions and utilize digital modeling to prepare for potential situations and implement scenario-based action plans in real time as conditions change.

The benefits of reengineering the value chain percolate down the managerial chain to all business operations and vastly reduce time-consuming and repetitive tasks. Automation systems which use intelligent operations help enterprises drive down cycle times and increase accuracy. This process allows enterprises to detect, predict, and prevent all the pain points they may not have known existed. Machine intelligence can effectively replace intuition, saving millions in guesswork and generating millions or even billions of dollars in efficiencies over the long term.

The benefits of re-engineering the value chain percolate down the managerial chain to all business operations and vastly reduce time-consuming and repetitive tasks.

In effect, the true digitization of a consumer business, or any business for that matter, rests on reengineering our value chains through process standardization, automation, visibility, analytics, and collaboration capabilities.

Discovering the Unknown

For logistics planning, the problem has always been to ensure the availability of the right quantity of supplies at the right place and at the right time – a subset of the overall business challenge we’ve discussed earlier. With machine learning-based modeling enabling an enterprise, the inbound logistical management can factor in a number of variables such as order placement, shipping, warehousing and utilization to predict and plan for future requirements.

A real-world example is when Walmart leveraged their Retail Link machine learning system to analyze information flowing throughout their supply chain. With it they were able to discover gaps and make seamless corrections in real time. Honda, on the other hand, deployed machine learning to discover patterns in their warranty return notes and mechanic reports to backtrack quality issues beyond the assembly line. Similarly, Caterpillar was able to save its fleet customers millions of dollars by using their machine-learning based Asset Intelligence platform, powered by IoT data, to identify an optimized power generation process for ships carrying refrigerated containers.

McKinsey Global Institute’s 2017 report states that machine learning has received the largest share of internal investment. This makes perfect sense given the potential payoff that it has proven to have for the bottom line. Major players like Google and Baidu strive to lead this movement from the front and are rapidly pushing the technology forward.

As an organization takes these technological tools and applies them toward its own operations, the results can be just as effective. Consider Amazon, which, in their attempt to create a fusion between the real and digital world, launched the Amazon Go store, which was first operated internally for employee beta testing. Amazon is constantly experimenting and testing diverse technologies like voice recognition, computer vision, machine learning, and AI to integrate the convenience of the digital with the real.

Imagine a customer walking into a store to buy a shirt. What if the store could have the desired shirt, currently unavailable, delivered to the customers within hours?

Furthermore, the customer can try out shirts to know how they fit, but augmented reality tools can give the customer a clear visual of how they would look in that shirt across an assortment of colors, helping them make their decision. And, by using real-time inventory tracing, the shop knows where the desired color shirt is and how quickly it can be delivered to the customer.

In the next wave of digital transformation, this shirt would be custom-made within hours for the customer if it wasn’t already in stock. In fact, this isn’t that far from reality. Amazon has already won the patent to create an automated on-demand factory that will, one day, do exactly that, and possibly change the way retail works in the digital space.

Reinvention or Obsolescence?

As companies move forward in the age of technological disruption, they have little choice but to reinvent themselves. The volatility of business models is growing and what works will become more unexpected and surprising with each passing day. The 3R approach to digitization helps provide a concrete way to address the issues on the journey to reinvention.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 1: introduction

Social eminence June 11, 2021

The customer’s no longer who she used to be, so why are you the same?

A large number of businesses have found themselves struggling to cope with customer expectations in the era of digitization. The primary issue has been their inability to reimagine their offerings and rethink their digital strategy in line with this new, hyper-connected breed of end users. Although business leaders often talk about how they need to change the way they serve the customer and emphasize their vision of placing the customer at the center of the value chain, it is easier said than done. The only thing we know for certain is that there is no denying or stalling digitization. The question that remains is: how do we really get there?

Survival of the most adaptable

We are at the crossroad of a technological epoch. An avalanche of technologies, like artificial intelligence machine learning computer vision and IoT have begun to converge and mutate to form hybrid solutions. The retail industry has led from the front in terms of disrupting business by adopting a digital strategy incorporating these technological mutations in its digitization journey. For example, Walmart’s low-key acquisition of Spatialand, a specialist in VR tech, is testimony to the seriousness with which the retail behemoth takes the importance of a nascent technology. Walmart understands as part of its digital strategy that keeping up with the customer experience revolution requires cutting-edge technologies. And adopting any means of defining this transformation is a victory for traditional businesses looking for a digital makeover.

Consider Amazon Go and how this digital strategy addresses the specific pain point of long checkout queues. While the tech behind the endeavor is almost magical, it’s incredible to see how the customer experience changes completely when a single step is skipped. In fact, a survey indicated that 70 percent of buyers prefer buying from a retailer who valued their time. Amazon gave these buyers exactly what they wanted.

And the ambivalence of the retail businesses wondering if they can wait out these trends could result in shortened shelf life. Warning examples include Circuit City, an erstwhile iconic electronic seller that went out of business thanks to an inability to respond to digital disruptions and launch a digitization process.

The product gets a digital makeover

The retail business is just one part of the tech invasion. The products themselves are changing as part of the digitization process. Take the wristwatch industry for instance. Since its inception, it has barely seen one or two major disruptions that were centuries apart. Today, with wearables becoming part of the technological singularity obsession, the once-ubiquitous wristwatch faces a struggle for its very existence. Tag Heuer, the Swiss watchmaker, realized this early and has collaborated with Intel and Google to come up with smart watches. In spite of Apple’s first mover advantage in the smart watch category, Tag Heuer is likely to have takers for the brand loyalty its customers have shown over the years and its brand personality that is upmarket and fashionable. With niche players like Frederique Constant joining the race, wearable tech, already mainstream, may soon find itself the subject of fashion reviews.

The service transforms

Customer expectations from the service sector also transformed as we moved into the ‘anytime, anywhere’ ecosystem. With zero tolerance for delays and steadily diminishing attention spans, the modern, hyper-connected customer expects experiences that are seamless across channels, instant, and intuitive. And while the internet and its spin-off technologies abet and enable these behavioral patterns, sectors such as telecom find themselves scrambling to adjust their pricing and operational models to this change.

And as yesteryear giants like Kodak, HMV, and Blockbuster make way for digital prodigies like Netflix, Amazon, and Uber, Jack Welch’s words ring truer than ever: “If the rate of change on the outside exceeds the rate of change on the inside, the end is near." For the service industry, this digitalization of business brings with it worries on data security, privacy, and the need for hardware upgrades that create some serious cost pressures.

A bumpy ride for the large fish

With information at their fingertips, the modern customer is better informed than any customer has ever been in the past. And these digital natives demand not only the right product at the right time, marketed the right way, but for organizations to evolve and readjust the pace at which they change their minds and preferences.

For larger organizations, however, keeping up with this dynamic business environment can be challenging and sometimes impact the very foundations on which they were built. To adopt digital strategies that cater to a new generation of customers, established organizations need to confront internal and legacy hurdles that are a mix of human factors and technology. They may not always have a clear, holistic vision on their digital and GTM strategies for their offerings.

To adopt digital strategies that cater to a new generation of customers, established organizations need to confront internal and legacy hurdles that are a mix of human factors and technology

Despite having the right technologies to help capture the massive amounts of data generated by customers, a number of global corporations find themselves wanting when it comes to drawing meaningful insights from this data. This clear gap in gathering vs. leveraging data is almost synonymous with legacy technology stacks and outdated processes that continue to haunt large modern enterprises today. Unfortunately though, these organization have traditionally suffered from a higher churn rate of CIOs and CTOs thanks to the lack of buy-ins from internal stakeholders and IT product failures.

Rethink, reimagine, reengineer

A lot has changed over the last decade but the fundamental challenges and aspirations of businesses aren’t all that different from the past. While digitization gives us access to newer and more effective tools, its deployment is far from being a perfect science or having a proven approach. What’s clear is that while technologies like IoT, AR/VR and AI are redefining the bedrocks of operations, marketing, and computing, the business of the future is expected to either imbibe these into their business models or run the risk of losing relevance in the present technology landscape.

The 3R Approach is a means of driving digitization in a way that addresses every growth dimension for modern enterprises. Each of its three aspects – rethinking products and services, reimagining customer experience, and reengineering the value chain will be elaborated individually in this four-part blog series. Watch out for the next post, where we’ll dive straight into rethinking products and services as a means to digitization.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

4 things Cios must consider on their digital journey

Social eminence June 11, 2021

There seems to be more hype than clear understanding about digital transformation globally - about what it takes to rewire and realign core tenets such as organizational culture, leveraging digital technologies, changing operations and processes to achieve business objectives, and to drive rapid revenue growth in this digital age. But despite the hype surrounding ‘digital’, enterprises are fast recognizing its strategic importance and impact across their respective industries. Most have already begun their digital transformation journeys, some are experiencing early gains, and some have been left behind due to lack of speedy adoption by the more agile digital competitor.

It is certainly challenging to harness the power of digital footprint across today’s large and complex enterprises, both in terms of stakeholder buy-in and lack of clear execution roadmaps. ‘Getting digital done’, so to speak, requires new rules of engagement, from ways of thinking to ways of doing, and is contingent upon purposeful yet measured orchestration of various critical elements. It is, therefore, imperative for organizations to introspect and answer a few important questions to gauge their maturity and also the path of journey to achieving holistic digital impact. Do they have the right digital strategy? Do they have a comprehensive execution plan? How can they better serve the user? How can they need to rethink business processes constantly and react to market shifts? How can they secure and improve their asset life-cycle? The answers to these questions are critical to the journey of digitalization.

Only around a quarter (26%) of respondents describe their organization as digitally mature and already reaping the benefits of digital transformation

To answer these questions better and to understand the underlying factors that determine the success and failure of digital goals, we commissioned an independent global survey with 340 senior business and digital technology decision-makers from organizations with annual revenues of more than $2 billion. This first-of-its-kind study delves into the digital journeys of these organizations by looking at the factors that might increase or decrease the chances of successful digital outcomes - from strategic priorities to barriers in execution; from digital technology investments and deficiencies to the role of the eco-system and many more. For business leaders looking to start their own journey of digital transformation, I would advise going through the findings in our report on bringing digital to life. In addition, I have also listed below a few of the many thought-provoking insights from the survey that will resonate with CIOs and digital leaders while helping them understand their own digital state and course of action.

Digital goals are focused on experience and efficiency: Seven out of ten (70%) respondents report that their organizations are currently utilizing their digital capabilities and technologies to improve customer experiences. Other common use is to improve operational efficiency (69%). This is not surprising or counter-intuitive as enterprises now strive to achieve greater engagement with their stakeholders and, at the same time, become leaner and more agile.

Process transformation lies at the core of digital consulting success: When asked about the key drivers of organizations’ future digital transformation success, close to 60% respondents chose a ‘well-defined digital process’ as their top driver. It is a clear sign that enterprises have realized the importance of gaining visibility into existing processes and then reimagining them by keeping user at the center to enable fundamental business transformation. In fact, this is why a key focus of our digital consulting practice is the transformation of traditional business processes through the digital lens to create an agile and experience-centric organization.

Organizations lack proper mechanism to assess digital maturity: In our study, only around a quarter (26%) of respondents describe their organizations as digitally mature and already reaping the benefits of digital transformation. Unsurprisingly, only a minority (39%) report that their organizations always use tools and frameworks to assess their digital maturity. This is where, I feel, a comprehensive framework like the Digital Technology Footprint (DTF) is required, which helps assess where you stand currently and what is required to be able to realize the true potential of digital footprint.

Just a quarter (25%) believe that their organization is ‘Cloud Native’ in terms of its cloud maturity

Enterprises yet to realize the full potential of cloud: Despite more than half of respondents (60%) citing that ‘a well-managed cloud infrastructure’ is critical for digital transformation success, just a quarter (25%) believe that their organization is Cloud Native in terms of its cloud maturity. It clearly points to the fact that majority of the organizations still have a partial view of what cloud and digital technologies can do for them in terms of executing their strategy.

Stay tuned for many more insights as we continue to engage with global enterprises on their digital journeys.


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Gamification & artificial intelligence: is there a blue ocean for insurance providers?

Social eminence June 11, 2021

I recently bought a Fitbit to motivate myself to walk everyday as advised by my doctor. My wife got enticed by the look of the wearable and she ordered one for herself. Within a week, we were a part of a group, competing with each other and with others in the group. In a month’s time, I was part of at least two or three more groups and so was my wife. We challenged each other to walk the most and had our winning moments every week. My health improved, my doctor’s revenue came down, though he being my well-wisher, was happy with this outcome. However, there was one more stakeholder who immensely benefitted from this exercise – my health insurance provider.. It was not just my health that improved I’m sure, but the health of at least forty more individuals who were a part of the various Fitbit groups. Now that’s the blue ocean I’m talking about, one that I feel insurance providers have not harnessed to its potential.

Similar to the APIs exposed by Facebook and Google, most of the wearable OMCs (original Manufacturing Companies) have their own apps and sites. All the key data from the wearable is available for consumption through APIs (Application Programmable Interfaces) or web services if the user agrees for such exposure. A lot of these OMCs have built their own collaboration platforms among their user community. This user community and the data on their health is extremely valuable to health insurance providers. The buzzword in insurance is always “prevention”. What if insurance companies can indirectly influence the health of its users in a positive way? This would bring down their claims and thereby increase profitability.

Basic collaboration platform

The insurance provider can create a collaboration platform and get all its users on-board. Users with wearables can choose to register, making their data or a subset of their data available. For instance, users may not prefer to post their cholesterol or heartbeat data but would be fine with sharing the number of kilometers they have walked or the number of steps they take every day. The collaboration platform will use the APIs exposed by the wearable OMCs at a competitive price and automatically make the data available in the platform for use.

The insurance provider can create a collaboration platform and get all its users on-board.

Creating user communities

Once the users are registered, the next step is to create the user communities. A team is required to play the game and the communities/teams can be formed based on their physical location, hospital visits, doctor’s visits, relationship, and common ailment, among others. Every community would elect a moderator through online voting and it is the moderator who will administer the games. The moderator will also be responsible for marketing their community, thereby encouraging other users to join in as long as they meet the criteria for joining.

Play time

Once a community attains a critical mass, its play time. Gaming ideas can range from determining the person who walked the most in a week and the longest walk in a day to counting the highest calories burnt and awarding the most consistent walker. Games could become more and more interesting if we combine Virtual Reality with the games. For instance, there could be a hidden treasure at a location where the walkers in a community would have to walk to and find out. The person who unearths the treasure would be awarded points. The more data the users in a community expose, the more number of games could be formulated. On regular intervals, inter-community games could also be played and this can go on and on. The number of possible permutations are endless.

Leverage the power of a community

Once we have the communities engaged in the collaboration platform, the options to engage them further and make money through these engagements are immense for an insurance provider. Community-specific events could be organized. This could be fun, providing an opportunity for community members to meet each other and socialize while getting their health checked in the process. With the user’s health improving, the claim rates are prone to come down and even if they don’t, the information available is so valuable that it can be used to take corrective action and improve each user’s health.

Power of Natural Language Processing (NLP)

A collaboration platform will involve a lot of communication and knowledge-sharing among users. This information is a gold mine from which insights can be derived on what is working for users and what is not. This is where we can leverage the power of NLP to obtain insights from certain key words and keep building on this dictionary as the usage increases through the implementation of a machine learning algorithm. Insights could be as simple as the brand of a medicine that works, the best shoes to wear for a walk, the best wearable, and the co-relation between BMI index and health, among others.

Digital Marketing

Now that a collaboration platform is built, user communities are created, games are formulated to drive better health, and artificial intelligence is deployed to gain actionable insights – the focus should be on turning the platform into an ideal advertising space for all providers, directly or indirectly related to healthcare. The providers in question could be a pharma company, a sportswear company, a health drink company or a firm selling healthcare products – a set of like-minded people who influence each other extensively because it’s ideal to sell related products. The uptake in such advertisements could be quite high and hence the insurance company can demand a higher advertisement premium. The insurance firm can use this platform for their own cross-selling and up-selling of products as well. Again, the opportunities are immense.

The world is now a global marketplace where companies such as Facebook, Uber, and eBay thrive and flourish. With insurance companies having a large user base and the mandate on health insurance in most of the developed countries, it is a user base that can readily be harnessed for the above gains. The insurance companies have to be cautious on ensuring that privacy is not breached and other data which is already made available by wearable OMCs are optimally leveraged to drive better health. The insurance companies can have their cake and eat it too!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Digital transformation: perspectives from the frontline

Social eminence June 11, 2021

Insights from HCL Tech’s Customer Experience Survey

Much like any other broad-based “revolution” that impacts large sections of the global economy and touches every business – big or small – the Digital revolution that started a few years back, is generating excitement and confusion in equal parts.

Most business and I.T. leaders will convincingly elaborate on the benefits of Digital technology, and confirm their commitment to a digitalized future. But in many cases these same leaders are confronted with real life challenges relating to organizational alignment, the burden of legacy technology and processes, and budgets.

At the Digital & Analytics practice in HCL Technologies, we wanted to find out if CXOs are able to sustain momentum on their digital journey, and where the real challenges are. There are of course many reports that hint at the allocation of “healthy percentages” of money and effort to Digital initiatives, we wanted to measure the pulse of the market, in a unique way. We deployed an iPad and paper-based survey at multiple industry gatherings and events such as the Adobe Summit, MuleSoft Connect, and others – and collected responses to carefully crafted questions from an audience representing a rich cross-section of the industry.

An analysis of this multi-part survey throws up interesting insights on digital transformation journeys across industries - key drivers, challenges, expectations and opportunities. Here are some insights that stand out for me.

When asked about the top drivers for investing in Digital transformation, more than a third of our respondents chose “higher customer expectations” as their number one driver; while about a quarter of them chose “cost pressures” as the secondary imperative. It is interesting for me that one in four respondents are investing in Digital technology to reduce cost of operations. But this is not surprising or counter-intuitive at all! In fact, this is why a key focus of our Digital Consulting practice is transformation of traditional Business Processes through the digital lens. With innovative digital technology employed at key process points, effort streamlining and cost efficiencies are gained very quickly, besides better coordination, collaboration and increased automation.

Therefore your next logical question will be, do we spend more to drive cost efficiency and experience? In our many engagements where we have deployed modern application operations with Agile, Low-code and DevOps at the core, we can confirm that Digital applications are not necessarily more expensive to maintain than traditional applications. In fact, in many cases it is the opposite. For business and IT leaders looking at Digital as a “spend element” only, this provides another perspective, one where Digital technology can lead to a leaner enterprise.

Enterprise-Level Drivers for Digital Transformation

Digital Transformation

Source: HCL Technologies Customer Experience Survey, 2017

What else strikes as an important insight here? One in five respondents named “simplifying the complex technological landscape” as a key driver. 20% of respondents are trying to simplify their complex technological landscape through the application of digital technology. This is aligned to what we have noticed in our long-term customer relationships, and leads us to believe that Digital is not a ready-to-deploy vision or an overnight revolution.It is an approach that has evolved over time by accelerating the inclusion of the larger organization beyond IT, due to development of key digital technologies. 

Many large organizations that now have integrated systems have grown on the back of a patchwork of applications and I.T. systems, many of which served a pressing need from the time they were commissioned – and some acquired as a result of a merger or acquisition. These applications then stayed on, integrating with other applications and systems and resulting in a complex and expensive heterogeneous Enterprise I.T. landscape. Forward-looking businesses soon realized that this is not sustainable, nor scalable.

This is where digital technology has provided them with a “way out” – giving them new tools to reimagine their businesses and customer experiences from the ground up. This is the fundamental digital transformation that HCL is excited to be a key part of, for many of our customers.

I will talk about one more insight from the survey that I found interesting. When asked about “the biggest roadblocks on the journey to Customer Experience Transformation” – 25% respondents cited “lack of funding” as the number one challenge. I interpret this not as a waning of the influence of Digital, but a sign of maturity in the market. Business leaders are taking a longer, harder look at resources spent on Digital technologies and applying much-required discretion to ensure that the spend is aligned to the larger business vision.

We are applying this insight in HCL Technologies and focussing on the “real world impact” of Digital on our customers’ businesses, however our belief is that this can only be achieved by integrating Consulting, Modern Application Development and Data Analytics together to offer a uniquely powerful service offering that will make digital real. 

The time for experimentation and point projects is over. The era of real holistic digital impact is here. Stay tuned for many more insights from our upcoming HCL Digital Transformation Survey. 


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Towards a responsible, digital future

Social eminence June 11, 2021

Few trends have received more hype and attention, in the past couple of years, than this broad-based phenomenon termed as “Digitalization”. If one were to do a simple cause-and-effect analysis, then it would be easy to arrive at a definition which would attribute Digitalization to Digital Technologies such as Mobile, Social, Analytics, Cloud, IoT and others like robotics, cognitive intelligence and augmented reality. In all my experience in spearheading HCL’s digital engagements with our customers, I can safely say that a technology-centric definition would be a radical over-simplification. I firmly believe that Digital Transformation much like The Fourth Industrial Revolution might be technology led; but the change itself is much deeper. The change has the potential to disrupt societies and organizations. Organizations on the road to true Digital Transformation have to plot their course across 4 major themes:

Leadership Culture: Digital Transformation is less about one brilliant idea or one smart individual - but more about integration and teamwork. The impact of Digital Technologies is so universal that the opportunities for transformation lie across teams, functional silos and even organizations. Leaders similarly have to step up, and focus on the larger picture, play the role that is more Integrator and Orchestrator; and less Manager. Effective Digital Transformation leaders will have to invest in building these skills.

Digital Leaders have to focus on the larger picture and be more of the orchestrator and less of a Manager

Business Process: This is an obvious one – but has a new dimension to it. BPM (Business Process Management) is not only enabling Organizations to re-imagine existing business processes to make them faster and more efficient, they are opening new vistas for imagining entirely new services. This can be a game changer in terms of entirely new ways of running businesses or engaging with customers.

Customer Engagement: This again is an obvious outcome of Digital Transformation; but the impact is beyond just providing “new ways” to engage/sell to customers. Digital Transformation is an opportunity to re-imaginei the Enterprise-Customer relationship. Organizations with successful Digital strategies have converted point-of-sale interactions to continuing relationship journeys and a one-dimensional view of the customer to a 360-degree view. This changes the positioning of an Enterprise from “seller” to “trusted partner”.

Digital is not only a technology initiative but an opportunity to re-imagine the Enterprise-Customer relationship

Ecosystems: If Digital Transformation is about creative integration of people, process and technologies; its impact can be multiplied many times over if organizations integrate across ecosystems of partners, vendors, customers and even competition. Successful digital-native companies such as Uber or Airbnb are transforming entire industries and showing stupendous growth by creating a unified experience across ecosystems. Digital aspirants need to look beyond their boundaries and integrate the best of the world has to offer and create unique products and services.

I believe, as Enterprises chart their own course towards a “Digital future”; they will have to create a strong business strategy first and look at the “business” aspects of Digital Transformation; rather than dive headlong into implementing Digital Technology. I have been fortunate to have been a part of many such well-thought out Digital Technology implementation journeys. Admittedly, in my daily corporate life, I am more exposed to the implications of this Fourth Industrial Revolution in business enterprises. Hence, I am delighted this year to be attending the World Economic Forum that draws leaders across the social, business and political spectrum. This year’s theme is Responsible Leadership – a truly relevant theme considering the implications of the Fourth Industrial Revolution on societies and businesses alike.

See you at Davos and stay tuned for an exciting post-Davos update!


abirje's picture Anand Birje January 13
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Senior Corporate Vice President and Global Head, Digital Business (Digital Consulting, Applications & Platforms, and Data & Analytics)

Pandemic analytics: how data is helping us combat covid-19

Social eminence June 11, 2021

As society grapples with the public health and economic challenges manifesting in COVID-19’s wake, businesses rushing to realign themselves to this new reality are looking to technology to help. Data analytics in particular is proving to be an ally for epidemiologists, as they join forces with data scientists to address the scale of the crisis.

The spread of COVID-19 and the public’s desire for information has sparked the creation of open-source data sets and visualizations, paving the way for a discipline we’ll introduce as pandemic analytics. Analytics is the aggregation and examination of data from many sources to derive insights, and when used to study and fight global outbreaks, pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease.

Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease.

Here are three ways pandemic analytics are helping us get through the COVID-19 crisis:

1 – To Craft the Right Response

In the early 1850s, as London battled a rampant rise in the number of cholera cases, John Snow – the founder of modern epidemiology – noticed cluster patterns of cholera cases around water pumps. This discovery allowed scientists to leverage data to combat pandemics for the first time, driving their efforts towards quantifying the risk, identifying the enemy, and devising an appropriate response strategy.

That early flash of genius has since advanced, and 170 years of cumulative intelligence has proven that early interventions disrupt the spread of disease. However analysis, decisioning and its subsequent intervention can only be effective when it first takes into consideration all accessible/meaningful data points.

At Sheba Medical Center in Israel, healthcare administrators are using data-driven forecasting to optimize allocation of personnel and resources in advance of potential local outbreaks. These solutions are powered by machine learning algorithms that offer predictive insights based on all accessible data about the spread of the disease, such as confirmed cases, deaths, test results, contact tracing, population density, demographics, migration flow, availability of medical resources, and pharma stockpiles.

Viral spread has a small silver lining: the exponential creation of new data which we can learn from and act upon. With the right analytics capabilities, healthcare professionals can answer questions such as where the next cluster is most likely to arise, which demographic is most susceptible, and how the virus may mutate over time.

2 – To See the Unseeable

The accessibility of data from trusted sources has led to unprecedented sharing of visualizations and messages to educate the public. Take for example the dynamic world map created by Johns Hopkins’ Center for Systems Science and Engineering, and these brilliantly simple yet enlightening animations from the Washington Post. Such visualizations are quickly teaching the public about how viruses spread, and which individual actions can help or hinder that spread. The democratization of data and analytics tools, combined with mass ability to share information via the internet, has allowed us to witness the impressive power of data used for good.

In recent months, companies have brought pandemic data gathering in-house to develop their own proprietary intelligence. Some of the more enterprising companies have even set up internal Track & Respond Command Centers to guide their employees, customers and broader partner ecosystem through the current crisis.

HCL realized early in the outbreak that it would need its own command center dedicated to COVID-19 response. Coordinated by senior leadership, it gives HCL data scientists the autonomy to develop creative and pragmatic insights for more informed decisioning. For example, developing predictive analytics on potential impact to HCL’s customers, as well as the markets where HCL services them.

With the goal of enabling leadership to respond quickly throughout the development of the COVID situation, we employed techniques such as statistics, control theory, simulation modeling and Natural Language Processing (NLP). For simplicity, we’ll categorize our approach under the Track & Respond umbrella:

  1. TRACK the situation quantitatively and qualitatively to understand its magnitude.
    • Perform topic modeling in real-time across thousands of publications from international health agencies and credible news outlets; automate the extraction of quantifiable trends (alerts) and actionable information relevant to a manager’s role & responsibility.
    • Create forecasting which will directionally track and predict when regions critical to HCL and its customers will reach peak infection, and conversely, a rise in recovery rate.
  2. RESPOND using a mathematical model of the situation as a proxy for the actual pandemic.
    • Create a multi-dimensional simulation model using robust and contextual variables to produce a meaningful prediction customized to the leader using it.

3 – To Diagnose, Treat, and Cure

On December 21, 2019, an AI system operated by a Toronto-based startup called BlueDot detected the earliest anomalies relating to what was then considered a mysterious pneumonia strain in Wuhan. The AI system accessed over one million articles in 65 languages to detect a similarity to the 2003 SARS outbreak. It was only nine days later that the WHO alerted the wider public about the emergence of this new danger.

Developing healthcare solutions is a challenge of solving data at scale, and this is where AI can play a crucial role. AI technology has already been deployed to help diagnose the Coronavirus through imaging analysis, decreasing the diagnosis time from CT scan results from about 5 minutes to 20 seconds. Through automation, AI can not only help cope with the rising diagnostics workloads but also free up valuable resources to focus on treating patients.

AI and ML can also be used to speed up the pharmaceutical development process. So far, only one AI-developed drug has reached human clinical trials. But even that solitary success is extremely impressive as the technology was able to expedite a process that typically takes years.

It’s quite possible that AI in conjunction with medical researchers can help reduce drug development timelines to mere months or weeks. With the world still in urgent need of a COVID-19 vaccine months after the first reported death, this human-machine synergy in the pharmaceutical space is the need of the hour.

Where We Go from Here

As the world braces itself for the impact of the COVID-19 outbreak, it is important to remember that technology is nothing but the cumulative innovation of humanity over time, and in technology we have the tools necessary to help us survive and protect ourselves. We do not know what lies in store for us in the coming weeks and months, but we will face it together, and our greatest strength will be in how we share, analyze, and derive insights from our shared knowledge.

With the right technology applied in the right direction, we have the potential to contain and minimize impact of disease today and in the future.

This blog was also published in ETHealthworld.com.


david.sogn_319532's picture David Sogn October 18
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Associate Vice President – Digital & Analytics

Cognitive solutions powering data marketplaces

Social eminence June 11, 2021

My previous blog touched upon the paradigm shift taking place in today’s increasingly distributed data landscape. As a natural extension of this transformation, I would now like to share some thoughts on how cognitive technologies are poised to power data marketplaces which have arisen in recent years. More so due to the integral role knowledge management now plays in the cognitive world with respect to training machines for business and data processes.

I believe that most 21st century enterprises have yet to fully tap the potential of cognitive technologies and have much more left to accomplish in the field. These technologies are far more powerful than the day-to-day data processes automation tools most organizations are aware of, and involve numerous innovations in machine-to-human or machine-to-machine interactions that can transform business outcomes.

Rise of Data Marketplaces

Just as oil was the most valuable fuel of the 20th century, many industry leaders believe that Data is the most valuable fuel for 21st century enterprises – but while oil may have its limits, data does not. Many organizations are already exploring ways to unify and speed up the way they use data in various business scenarios. As a result, we’ve seen the rapid emergence of Data Marketplace tools and platforms that seek to address this business requirement.

Essentially, data marketplaces are a “one stop shop” that businesses use for business requests, reports, and insights in an easy and direct manner. Within an enterprise, data marketplaces offer a simplified architecture that can easily collect, collate, organize and integrate, data from various sources to become a Unified Data platform. An effective Data Marketplace is able to structure the unstructured data across the organization, by creating a compatible data model across silos that standardizes data formats. This data is further emboldened through various enhancements such as data search interface and data visualization which allow for up-to-date, fast and easy projections and estimations of business scenario simulations, making it a valuable business tool.

This approach to accessing data allows businesses to utilize their company-wide data from anywhere through a single point of interaction. This saves time and effort, as data no longer needs to be sourced, selected, and interpreted for each business case. As a result, businesses are able to achieve cost savings and quick turnover timelines as issues of data replication and data movement are solved. However, as we continue to look at the changing digital data ecosystem, we can see that the potential of data marketplaces can be significantly enhanced when we leverage cognitive solutions to further extend their functionality.

For example, in one of my recent projects, I had the opportunity to work with one of the world’s leading market research companies to help realize their need for automated data delivery and processing. Together, we were able to truly unleash the business value of data by consolidating all their requirements into a graph database with a machine learning powered cognitive interface that could enhance search prioritization and quality matching. In this manner, cognitive solutions were leveraged to enhance quality requirements with the critical goal of ensuring that there was no mismatch in customer expectations vis-à-vis delivery.

Traditionally, most data operations have been done through traditional manual interventions that requires enterprises to spend an immense amount of workforce resources. However, cognitive solutions changes this as it can speed up the outcomes by simplifying tasks such as driving data governance, continuously updating metadata, handling knowledge management and most importantly, monitoring data operations.

Data Marketplaces in the Enterprise

Let’s consider for a moment the needs of the next-generation enterprise – speed, accuracy, and excellent customer experience. All these goals require companies to be quick to respond to changes, and develop well thought out business scenarios to leverage emerging opportunities.

Take for instance a major global retailer we work with who operates over 410 stores in 49 countries. The company has over 800 million annual customers, over 2 billion annual visitors to their stores, nearly 150 million app users, nearly 150,000 employees, and over USD 40 billion in sales. For such a company, the ability to integrate data from across diverse nations, customers, and people, doesn’t just end in the front-end but also extends across their value chain.

For them, ensuring a harmonious data ecosystem across geographies and sources is critical to being responsive, fast, and efficient in serving their customers across geographies with a high level of quality. Moreover, given their leading position in the industry, they also have access to data from numerous vendors, suppliers, and manufacturers that are part of the production value chain. Therefore, having active access to these disparate data sources, such as inventory data, finance data, supplier data, and customer data creates the ideal data pool needed to track lead times and efficiently manage their business plans over seasons, cycles, and different business scenarios.

In such a case, having access to a Data Marketplace is not only beneficial but also critical for sustained business growth and success. However, the challenge to being responsive at such a scale can prove daunting. While Data Marketplaces are useful in bringing data together, the final bottleneck remains invariably human. This is where AI and other cognitive technologies have played a big role and helped ensure rapid access to insights and intelligence.

Potential of AI in Data Marketplaces

Data Marketplaces in a cognitive world don’t have to simply be “one stop shops” but instead can act as deployed agents. These cognitive agents function like an engine that continues to handle data operations and governance including all administrative tasks to support daily needs such as information regarding consumers, business analysts, power users, executive leadership, casual users and most importantly, business process owners whose endeavor is to simplify processes to enable quick outcomes in a business agile world that is freed from a human worker’s knowledge and ability to make decisions.

Data Marketplaces in a cognitive world don’t have to simply be “one stop shops”, but instead, can act as deployed agents.

Over the last few years, I’ve worked with my team to develop this form of cognitive tool that takes a modern approach to data exploration. We simply call it the HCL Data Bot that is integrated to our data fabric ecosystem in our solution to help enterprises as they scale digitally. This cognitive tool was designed to help organizations manage data operations, processes, and system performance in order to help contextualize business needs and enable monitoring of business KPIs. Consequently, the integration of this bot within data marketplaces has been able to help enterprises easily discover actionable business insights and help users sift through the hundreds of data variables and fields, while also being able to locate data and link it to the appropriate metadata for a more comprehensive dataset.

This type of holistic integration can help users acquire the most optimum data selection that is suited to their business scenario and leaves the need for manual searching in the past. In fact, with advanced AI and NLP based tools, data bots can assess a user’s data requirement history and proactively offer a more specific dimension of selections, saving time and effort. Users can also easily discover the data’s availability, and the bot can share various useful details such as the previous use-cases of a particular dataset, as well as the feedback surrounding its previous uses.

AI Behind the Platform

Throughout my career, I’ve always placed an immense importance on design thinking and knowledge management, both of which have been core pillars of digital transformation. This approach is essential as it is more capable of understanding user personas and their value journey, thereby enriching the value of the end solution. HCL’s Data bot can provide prescriptive suggestions for orchestrating new data sets as they become available on the platform, thereby making the process more proactive while also being reactive.

Cognitive intelligence tools can also be used to assess the core effectiveness of the data provided. By evaluating the degrees of success of past deployments, cognitive intelligence tools can help businesses quantify the data KPIs and assess its value in achieving business goals. This process enables businesses to effectively plan the correct data for the correct business problems, by knowing which scenarios offer the greatest ROI, and whether it leads to better business outcomes.

Cognitive intelligence tools can also be used to assess the core effectiveness of the data provided.

Moreover, cognitive intelligence can play a valuable role in assisting in the management of data processes at their very fundamental level. Similar to virtual personal assistants, advanced cognitive intelligence tools can help in the processes that surround data administration by monitoring data flows on the platform. These solutions can also ensure an automated performance and quality check of the data marketplace platform.

Constant Transformation

As I’ve said before – digital data ecosystems are undergoing a paradigm shift where we need to adopt a Data Fabric approach to make data more accessible and actionable across the enterprise. Moreover, as more and more organizations begin to adopt a fully digital approach, the challenges of digital at scale can only be tackled with the benefits of cognitive technologies. I’ve already had the opportunity to work on numerous implementations of this kind and am convinced that cognitive solutions offer all enterprises the correct combination of tools with which to unleash their business intelligence potential and blaze into the 21st century.


venkatakrishna_c's picture Venkata Krishna C September 26
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Global Solutions Lead - Data and Analytics

Infusing cultural intelligence in analytics to drive customer centricity

Social eminence June 11, 2021

Perhaps the best way to describe cultural intelligence is to first state what it is not.  Typically, cultural intelligence is defined as “the capability to relate and work effectively across cultures”. This isn’t necessarily what I’m talking about. In the context of this article, cultural intelligence is the discipline that helps enterprises understand what is happening in culture as it relates to a brand, its products, its employees and most importantly its customers.

Cultural intelligenceCultural intelligence helps us find the human signal through all the market noise. It allows us to gain a deeper understanding of the customer, their communities, and their base-level drives which are integral in shaping their values, beliefs, and motivations. This information is discerned through a careful analysis of the cultural moments, trends, and fads which differ between cultures, and are critical in helping organizations shape their relationships with customers.

Case Studies in Cultural Intelligence

Let’s take the recent case of the Pepsi-Protest commercial that shows what happens when firms are not aligned with the cultural zeitgeist. The commercial, from Pepsi’s Content Creators League ad agency, shows reality celebrity Kendall Jenner magically settling a standoff between protestors and police by offering an officer a can of Pepsi. Immediately after its release, it sparked outrage and controversy, being rebuked on social media, and even being parodied on Saturday Night Live.

It’s no surprise then that it was promptly pulled from the air.

The mistake Pepsi made was one of cultural intelligence. The brand knew that political protests were on their core demographics’ radar. They knew that young people, more than any other segment, were activated and engaged with this nation-wide social phenomenon. And they thought they could tap into that vein to connect with them. Unfortunately, they made the mistake of stopping at “protest”, instead of delving deeper and understanding the reasons behind it. As a result, they ended up telling a story that offended, rather than inspired all potential consumers.

In contrast to Pepsi, there are many other brands who we can cite as positive examples that have executed such acts of marketing with elegant and sensitive cultural intelligence.

Nike sales Nike, which has a history of provocative marketing campaigns – from the “What will they say about you?” campaign for Middle-Eastern women to sponsoring Chris Mosier - the first Team USA transgender athlete. In the most recent case, Nike decided to capitalize on a very tangible cultural tension which exists in the US today by unveiling NFL quarterback Colin Kaepernick as the face of its brand during the League’s season kick-off game over Labor Day Sunday. The ad was met with overwhelming polarization but within two days Nike sales surged 31% and polls showed that the ad resonated positively with Nike’s core demographic.

So while companies have much to lose when attempting to connect across cultures and mindsets, it is more than worth it if it’s done with sincerity and sensitivity. Through a unified understanding of business, consumer and market a company can extract actionable insights and make sustainable plans for improving sales. Generally speaking, this thoughtful approach to cultural intelligence can help companies discern the following critical insights:

  • understand the customers’ demographics, location, opinion, relationship, and social network surrounding their brand.
  • understand how people are speaking about their brand and the shifts in perception of the equities that really matter to their audience.
  • understand how customers differentiate their products against a competitors and why
  • understand and anticipate the viability of an established sales strategy based on the marketplace demand (pre-lead) and whether the company is poised to capture existing demand relative to the competition.

Cultural Intelligence – A Business Imperative

Cultural intelligence helps us find the human signal through all the market noise..

Cultural intelligence isn’t simply about understanding the customer in a more meaningful way.  Companies and Brands must innately know who they are and confidently stand for more than just their product. Ideally this is drafted as an easily articulated and understood statement of what the company or brand believes in. Rather than being a piece of aimless motivational garbage, what I’m referring to expresses something that tends to resonate deeply and employees would not feel awkward discussing it over coffee or with their partners across the industry. 

Companies and brands must innately know who they are and confidently stand for more than just their product.

Most agree that this concept is very much different from the typical enterprise vision, goal or mission statement they’re used to. For example, most mission statements simply attempt to announce in one way or another that their brand is about more than simply making more profit for their shareholders.  However, as valuable as mission statements are, great brands tend to be built on underpinning values that give guidance to all aspects of brand and company activity.  They project a certain point of view on the world that engages people, both within and beyond the organization, as they radiate the values and commitment needed to bring their vision to fruition. 

For instance, Microsoft aim’s to make the planet smarter and improve lives by harnessing the power of artificial intelligence. Another such example is Nestle Japan and their commitment to act on the principles of “Creating Shared Value”, as a way to engage with socially relevant fields like nutrition, health & healthcare, rural development, environmental sustainability, and human rights in their local value chain.

I call this concept an “exemplary commitment”. It gets at something authentic and real, and as a consequence helps brands tap into what matters to their customers the most, as they take a market leading position.

Creating an “exemplary commitment” is not a silver bullet for driving brand growth or doing great communications, however it can be extremely helpful when it’s deployed correctly, and is useful in such situations:

  • when an organization needs its purpose articulated
  • when the company’s market lacks a thought leader
  • when a brand or company needs greater cultural connection

Brands need an extremely practical tool that can help them realize the power of their purpose, and use it as a means to guide the overall direction of their marketing and communications issues. This starts by staffing the right talent and integrating 3 seemingly separate disciplines into one team with a shared mission of better connecting their brand at a deeper level with their customer’s values. These three disciplines are:

  • Anthropology: a team of experience designers focused on exposing what connects consumers, critics, and culture to content and media.
  • Economics: a team of economists focused on understanding the relationships between those connections and valuable behavior indicators.
  • Analytics: a team of data scientists focused on establishing the calculations and algorithms that allow us to anticipate those behaviors.

At work when I speak with companies and help them use cultural intelligence to their advantage they usually get it right away. The concept itself is not particularly novel or ground-breaking. The challenge however is to scale their intelligence gathering in relation to what’s happening in culture (i.e. tap into the cultural zeitgeist) and act upon it in a way that authentically aligns with their brand’s purpose and commitment. In other words, how to take one successful site or campaign launch and replicate that success across multiple business units and a myriad of product lines.  What if things change with the customer base (as they invariably do) mid-rollout?

Today, companies and brands put too much effort towards rough ad hoc qualitative analysis that struggles to keep pace with the rapidly changing landscape of cultural connection and trends. This is where the power of analytics and cultural intelligence makes for an interesting thought experiment. Analytics has allowed businesses to quantify and model vast quantities of data and decipher meaning out of the chaos. It is at the intersection of cultural intelligence and analytics where we find the discipline of cultural analytics to emerge.

Cultural Analytics

Don’t get me wrong; cultural analytics is not necessarily a novel idea in the broader scheme.  It exists today, albeit still in its formative stages and has yet to be fully tapped by business. Cultural analytics is being developed to help organizations discover shared value systems from the pattern of behavior witnessed in managerial decisions, employee behavior, and companywide operational procedures.

By quantifying these data sets and applying analytic modeling solutions, we can understand and predict the organizational decisions and behaviors for the future. Or at the very least, shed light on currently existing problems and devise the means to solve them.

This is exactly what German company Multigence claims to do – use technology solutions to measure and evaluate individuals and groups – to better establish a cultural fit. Another example is the ad agency Sparks & Honey that evangelizes cultural intelligence and its infusion with technology with their in-house proprietary tool “Q” – an active learning system that deciphers signals and patterns within unstructured data to generate insights.

Currently, each of these solutions only targets a very specific and relatively controlled domain within culture and business. The Multigence Cultural Profile tool is able to measure, evaluate, and match a company’s culture with employees, candidates, and even other organizations, while Sparks & Honey observes consumer markets for cultural shifts and trends for marketing campaigns.

And while much of this may seem like science-fiction, we have only to look around at the significant progress being made in the field to realize that the era of cultural analytics is nearly upon us. Consider the groundbreaking work being done by Michel and Aiden, Harvard-Google data scientists in the development of Culturonomics, a field of study that deciphers human behavior and cultural connection and trends through the quantitative analysis of digitized texts thanks to computational lexicology.

This method of analyzing culture via language has tremendous potential on the social web where the overwhelming exchange of publically shared communication is via text. And while, culturonomics is far from a perfect system, it has proven successful in retroactive predictive studies that covered the Arab Spring, demonstrating its rigor and validity in the real world.

Cultural Intelligence in Analytics and Customer Centricity

I imagine a cultural analytics system that is able to untangle the much larger web of human interactions in an automated and user-friendly manner, across dimensions and use cases. With next-generation cultural analytics, we will be armed with an unprecedented, deep-rooted understanding of organizations and people like never before.

We can imagine a simple framework that demonstrates how scalable cultural intelligence would work in an organization by referring to the illustration below:

illustration

With this degree of cultural nuance factored into strategic business simulations, organizations will be able to offer their customers an empathetic and human connection unlike ever before. Businesses will be able to simulate how business decisions and strategic operations will play themselves out in the real world and take steps to engage them.

In the not so distant future, pioneering 21st century enterprises will lead the way in cultural analytics, using it as an essential tool in the creation of a truly customer-centric experience. The only question that will remain then is – will you be one of them?


david.sogn_319532's picture David Sogn October 18
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Associate Vice President – Digital & Analytics

Transform your digital data eco-system with a data fabric approach

Social eminence June 11, 2021

Organizations that were innovators and early adopters or had previous implementations began with a focus on incubating new technologies. This led to use case-based deployments that were built from scratch, primarily in the greenfield mode. However, the situation has begun to change.

Enterprises are becoming more distributed even as they continue to remain even more connected. By leveraging cloud-based data driven analytics, these organizations are tapping into new dimensions through which they can leverage data for better insights. In fact, we at HCL have used these principles for many of our customers across a number of varied industries, to drive maximum business value from data transformation platforms. Among many others, we are proud to count for a US-based telecommunications giant, a leading market research company, and a Europe based financial services enterprise as satisfied customers.

Today, most enterprises are either in the process of moving or have already moved towards scaling digital across all lines of businesses. This is particularly true in scenarios where analytics and data scaling initiatives need to align to new business models. Organizations are now working overtime to ensure this sync by modernizing their legacy systems by adopting new system architectures and principles.

Clearly, the time has come for organizations with heavy investments in cloud and big data ecosystems to reimagine their traditional architecture. Rather than continuing to create monolithic platforms, companies need to focus on a connected data ecosystem where big data, cloud, hybrid and traditional can coexist in mutually-beneficial harmony.

The New Paradigm

There is little doubt in my mind that we are witnessing a paradigm shift in the digital data ecosystem. The increasing focus on ensuring that data remains federated while staying connected is one of the critical features of this change. This shift has led to the integration of advanced technologies like artificial intelligence and machine learning into data management and operations, leading to increased business value from data.

At first, businesses were simply incubating big data capabilities in dug-in silos for use primarily in their point-use cases. Over time, businesses began to experience the benefits of distributed and connected systems and moved towards cloud data ecosystems offered by players like Azure and AWS. But the overall approach remained siloed and modern cloud-based implementations typically occurred in isolated pockets across the enterprise. Now, however, organizations no longer want to be constrained to a point-use case solution. They want to deploy these ecosystems across the enterprise level.

Our own big data and cloud analytics customers are now asking us to help them scale-up these pocket ecosystems. Today they want to leverage digital across every line of business in their organizations. This is no surprise. After all, data ecosystems connected across digital platforms enable businesses to execute multiple use-cases and potentially generate exponential value from their data assets. In addition to scaling up their digital data ecosystems, future-facing organizations also seek to leverage Agile and DevOps processes across their data ecosystem. And this is what makes this new paradigm such an interesting challenge.

So how do we bring all these potential capabilities together and connect this distributed ecosystem in such a way that it helps companies drive digital innovation & business outcomes?

Data Fabric: Taking Data to Scale

I like to think of this new seamless ecosystem as a Data Fabric, where each thread is a data set with its own capability. Together, these multiple threads are woven together to create a new functionality. This is the entire crux of this paradigm shift. The key goal is to make data more accessible, faster, and actionable. And we can accomplish this through automation, simplicity, repeatability, and discovery.

Adhering to these four tenets can ensure that a large data ecosystem remains stable as it is scaled up and out. From our perspective, a modern Data Fabric architecture pattern is the key to connecting application performance with application functionalities. Businesses can reduce data ingestion and preparation time in one go by utilizing a rapid pattern-based development approach. Thereby, a Data Fabric approach can be used to encompass any scale of data and origin while honoring its unique sensitivity.

A Data Fabric approach can be used to encompass any scale of data and origin while honoring its unique sensitivity.

In real terms, the Data Fabric approach can allow businesses to speed up their data warehousing processes and allow for a single harmonized visualization of their operations across the enterprise. Additionally, they can also reduce overall costs in the immediate term and benefit from minimal incremental expense as the organization continues to grow.

Case Study: Wireless Operator Deploys Data Fabric to Gain a Single View of Customer

The benefits of this approach are best explained through a real-world example. A leading wireless network operator in the US, with over 70 million customers, was looking for any way to gain an edge on their competition. They partnered with HCL to help them achieve this goal.  We were well aware that the market was fierce and mature, and that the client needed a data-driven strategy that would allow them to offer unique, customized and tailored offers & promotions to their customers, leading to market disruption.

For this they would need to consolidate over 80 distributed data sources, with over 1.7 petabytes of data, while also managing the daily incremental load of ten billion records. HCL helped them establish a next generation solution that wasn’t just another monolithic silo. So, we developed a data lake designed for business intent that was drawn from a number of distributed data lakes within the enterprise.

We employed a Data Fabric approach, like the one described earlier, that connected these disparate sources. Through it, the client was able to ingest, harmonize, and create visualizations of the raw data from across a centralized platform for sharper business insights.

HCL also helped the client establish a Transformation Library. This library consisted of reusable data transformation functions, as well as a Data Catalogue that enabled business users across departments and functions to centrally access data sets. A key value addition in this project was HCL’s creation of a sand box environment that allowed our client to perform data discovery and execute preliminary advanced analytics.

The results of these transformations were remarkable. The client was able to rapidly compile numerous and disparate data sources and use them to analyze new business models for marketing and operations. Further, the use of an Agile Analytics approach enabled the rapid execution of new promotions from inception to delivery as well as monitoring within a short period. Overall, the client was able to gain a single unified view of their customer, which enabled them to make processes like billing, plans, promotions, and devices a pain-free experience, leaving both customers and the business, delighted.

Scaling New Heights

In an increasingly competitive and cutthroat marketplace organizations need be able to leverage data to make lightning-fast decisions. With petabytes of information amassing over time, companies need this data to become more easily available, accessible, consumable, and actionable - centrally. The complexity of data adoption at scale needs solutions not just within certain pockets but on an enterprise level.

Only through an effective data scaling strategy can organizations gain the right insights and solutions which will allow them to learn fast and act faster. From using social data to gauge the effectiveness of a new product launch campaign, to assessing real-time data generated from devices in clinical trials for testing and proof, and even in providing well-defined and prompt responses to queries for regulatory mandates, fast and accurate data is key.

HCL’s digital at scale propositions have already enabled a number of organizations to successfully execute such transformations.

HCL’s digital at scale propositions have already enabled a number of organizations to successfully execute such transformations. With our DevOps based operating model, and our Data Fabric approach, HCL’s solutions are aimed towards engineering a large data transformation landscape that also modernizes legacy and traditional data ecosystems. This is the summit of digital transformation that modern enterprises need to conquer.


venkatakrishna_c's picture Venkata Krishna C September 26
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Global Solutions Lead - Data and Analytics

The AI frontier: driving reliable and stable IT operations

Social eminence June 11, 2021

In 2020, I came across an article that talked about how Artificial Intelligence (AI) is expected to be the new catalyst for software development. The article stated that artificial intelligence-powered software development tool providers had raised more than USD 700 million in just 12 months. And this was before COVID-19 compelled enterprises to undertake rapid digital transformation.

Of course, this move forward has been accompanied by an accelerated growth in artificial intelligence adoption. According to HCL’s Digital Acceleration report, artificial intelligence has catapulted to become one of the biggest drivers of technology investment for business and IT leaders globally.

AI’s Role in IT Operations

With the increasing adoption of the concepts of Site Reliability Engineering (SRE) in mainstream enterprises, automation is becoming more intrusive in IT operations. In this blog post, we shall explore the prevalence of AI and Machine Learning (ML) in application IT support, rather than in infrastructure support. I believe application IT support is a more complex problem to solve.

Let’s look at the three types of tickets such as service requests, incidents, and alerts that typically get created in IT operations and consider how AI and machine learning is used to handle each type.

Service Requests

Service requests handling has the most common use of AI/ML because Standard Operating Procedures (SOPs) can be created easily for such tickets. Once we have an SOP, Natural Language Processing (NLP)-based understanding and classification models with Robotic Process Automation (RPA) can enable automated resolution of these tickets unless authentication is required. In such cases, opsbots (chatbots) could be an alternative for self-service portals. Chatbots also bring an added advantage of helping visually challenged people.

Incidents

Incident handling can be categorized into three use cases: Recovery, resolution, and prevention. Let’s start with the first; where we look at AI and ML as it is used to facilitate rapid recovery in the aftermath of an incident.

Recovery

Today infrastructure as code, service mesh, containerization, and micro-services architecture are becoming the norm. Automated recovery using AI/ML ensures HA (high availability) in these applications or platforms. This might include, but is not limited to, autoscaling of applications based on model rules, automated mission control operations such as segmentation, backpressure, and bulkhead creation among others. These remediation techniques can be applied automatically through AI/ML. These are achieved by integrating simple pattern recognition models with relevant actions that are automatically executed.

Resolution

Incident resolution involves routing, triaging, and remediating the incident.

Routing: For any conventional incident resolution cycle, identifying and routing the ticket to the right person or resource to resolve the problem is a typical waste. This is when lean management principles are applied on IT operations value stream

AI optimizes the ticket allocation process by referencing data from all previous ticket allocations – from the service desk to the various operations teams. It also takes into consideration existing information of ticket hops that have taken place previously. With the ability to automatically categorize a ticket using natural language processing and ticket type, allocation to appropriate teams is seamless and fast. In certain cases, these tickets are assigned to the exact engineer whose code base was problematic. This was possible using AI/ML and, the ability to trace an error back to the actual engineers based on backward traceability established by matured CI/CD practices

I recall my experience of working with a global retail giant struggling with a very high number of rerouted tickets. They needed to reduce the number of rerouted tickets and cut back on the resolution time. We approached the rerouting issue by using previous rerouting data to train the AI/ML models. These learnings were then fed into a vectorization model to classify subsequent requests. This proved to be an effective solution. Through continuous learning, the AI model increased the first-time successful allocation rate from an initial 30-35% to 91% of total cases within three months.

Triaging: This step in the resolution process takes the maximum time and effort in IT operations. AI/ML is helping operators triage incidents faster through the use of conversational UI-driven intelligent KeDBs. This enable semantic searches, advances in observability which provide 360-degree view of the state of dependent systems or actors during the incident, and suggestions of possible remediations based on semantic patterns.

Remediating: Notification in triaging would most likely lead to suggestions on remediation as elicited above. In matured cases, such prescribed remediations agreed by the operator are also monitored to eventually enable straight-through-remediation or self-healing. This is still quite rare in application operations space where SOPs are hard to come by for incidents.

Prevention

So far, we have been exploring how AI models and ML can help in the resolution of an incident. But how do we prevent incidents before they can even occur?

Preemptive resolution of possible incidents is perhaps one of the most ambitious applications of AI models in IT operations. Achieving something like this depends on learning models that can identify the strongest indicators, causes of an incident risk and the degree of threat. When it comes to preventing incidents, AI and ML can be used to model and predict systems behavior based on a range of parameters that we can analyze.

AI and ML can be used to model and predict systems behavior based on a range of parameters that we can analyze.

Preemptive resolution is perhaps one of the most ambitious applications of AI in IT operations.

At HCL, we use three distinct models to predict systems behavior depending on the level of maturity of the available data. These are:

  • Probability distribution which focuses on internal two-dimensional data
  • Topological data analysis which focuses on internal multi-dimensional data
  • Game theory which focuses on both internal as well as external multi-dimensional data

These systems’ behavior models leverage historical data to predict if a problem could occur in a particular system. This prediction, in turn, can alert teams to take proactive measures or corrective actions in a dynamic scenario. These actions could include scaling infrastructure, changing the load balancing configuration, or simply introducing added layers of monitoring to prevent issues from even occurring.

When it comes to changes to an existing system, the operations team use AI/ML to assess system behavior objectively before signing-off for release — all done in an automated way. Two such recently used techniques were mutation testing and resilience engineering (chaos engineering).

Alerts

In contrast to traditional IT systems monitoring, AI and ML can be used to observe a system from a business-down perspective. AI/ML is used to correlate events from various monitoring tools and make an inference of business capability/sub-process behavior. Intelligent alert aggregation reduces the number of alert tickets. It also helps in identifying the real source of an alert and thereby reducing discovery, triage, and remediation time for such alerts. Another outcome of this approach is eliminating any unforced errors in ticket prioritization and allocation. This in turn, saves costs and allows the operations teams to focus on areas that need more immediate attention.

Conclusion

From detecting anomalies to suggesting ways to remediate them, AI and machine learning models that analyze data patterns in systems have shown the potential to streamline every phase of operations and development. They find their place in most of DevOps and SRE implementations. But as it has become evident in my experience, the value of any technology is only as good as its implementation. That will continue to be the key differentiator for effective AI and ML adoption in an enterprise.

By understanding the underlying datasets and adopting appropriate AI/ML models, we can realize benefits of at least 55% reduction in tickets, 45% reduction in operators, and 70% improvement in NPS scores for IT operations team.


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

How to successfully scale agile and devops - part 4: driving success with process

Social eminence June 11, 2021

Welcome to my fourth and final blog in the series “How to Successfully Scale Agile and DevOps”. Earlier, we had discussed the importance of scaling Digital/Agile, and the major propositions of the “People” and the “Technology” dimension of driving agile at scale.

In this post, we wrap up this series by taking a deeper look at the third element of this equation, the one that brings everything together – the “Process” dimension. It’s only fitting that this dimension is placed at the conclusion of the series, since it’s the overarching framework within which the People and Technology dimensions operate. As a result, it is perhaps the most vital element when it comes to generating actual business results.

Motivation – The Foundation of Change

We begin with the simple question – how do you bring about agile processes in an enterprise?

As we would all agree, Agile model is more a philosophy and a way-of-life than a methodology with a bunch of steps. Philosophies and ways-of-life can only be adopted by humans and not machines. So, the process aspect is more about driving the change in people than anything else. Hence, the key foundation of a process change at scale is all about motivating people at scale to adopt the defined process.

I’m reminded of the ideas put forth by Daniel Pink in his masterful book “Drive” which perfectly illustrates the gaps in how we motivate and inspire people and offers meaningful solutions to these problems. I’m particularly interested in the three core aspects of the book that have proven invaluable in my own experience. Namely, the idea of autonomy, mastery, and purpose, as the real foundation necessary to drive motivation in any process reform. At HCL, our foundations of the “Process” dimension have been based on these same pillars. My work in implementing these process changes across large organizations have yielded substantive results; whether for one of the banks in the Netherlands, a large car manufacturer in Sweden, or the leading digital bank in South Asia.

Foundations of the Process dimension in DevOps has been based on the pillars of autonomy, craftsmanship, and purpose.

Driving Motivation Across Organizations

While many frameworks have proven useful in terms of driving enterprise transformation roadmaps, many of them do not address some key fundamentals relevant to an enterprise journey. Some organizations have adopted models such as Holocracy or Sociocracy in recent years. But we believe that these models are very nascent in their structure and unsuitable for true enterprise-level needs. And more importantly, they haven’t been tested enough in the crucible of the real-world market to prove themselves worthy.

It’s worth remembering that the most effective agile framework doesn’t only tell us what changes need to be implemented but also provides a roadmap and indicators of how to achieve these changes. Therefore, when it comes to implementing changes in Process, the tenets of autonomy, mastery, and purpose, are far more prescient. The methods involved in enacting each of these elements can be surmised as follows:

Autonomy

As Daniel Pink says in his book, “Control leads to compliance; autonomy leads to engagement”. Therefore, to truly make lasting changes, autonomy needs to be rooted in the DNA of any organization and team. This entails a complete redesign of the underlying structures to help empower people. It offers them the freedom necessary in making their own decisions, especially if scaling agility and DevOps is the goal.

While there are various ways for organizations to redesign themselves, in our experience, a combination of organization design constructs from Scaled Agile Framework (SAFe) and the Spotify agile model to elaborate on Team level redesign have proven to be effective mainly due to their simplicity, which is essential when driving change at scale. A key aspect of this simplicity that works in Spotify’s favor is its clean and simple messaging, which manifests as easy terms of the four organizational units – squads, tribes, chapters, and guilds.

By reorganizing people into these groups, we can drive greater efficiency and productivity during the entire development cycle. Squads operate like scrum teams with about 6-9 people dedicated to one feature/capability, operating in an autonomous and self-organized manner. Though it sounds easy, it is by far the most critical and toughest journey in the Agile scaling journey. How do we break large enterprises into a cluster of hundreds or thousands of squads? Two recent experiences from customers in Germany and Switzerland proved that getting an incorrect team structure could prove disastrous where the organization found their velocity slower than traditional models with the additional burden of harnessing a demotivated team after the redesign. Incorrect structures will result in driving high dependencies between squads which will eventually slower the rate of deployment of new features to business. There are two critical learnings to ponder when we redesign organization:

  • Use of business architecture to redesign teams where typically squads are aligned to L4/L5 capabilities in the enterprise business architecture model.
  • Designs and structures need to be agile by themselves. It is critical to continuously measure dependency affinity between squads and redesign Tribes if found necessary.

For one of our customers who were struggling with showcasing improvement in feature velocity post taking an Agile journey even after having set up the organization into squads, just a redesign of the squads enabled us to reduce the release cycle times from 12 weeks to 3 weeks.

The final key learning on Autonomy we had is the notion of “Aligned Autonomy”. Autonomy does not mean that squads can choose their own Agile methodologies, tools and sprint cycles to deliver features. We have seen chaos engulf when large organization drove autonomy literally. Aligned Autonomy would ensure:

  • Common cadence: Squads follow the same Agile methodology across the enterprise or at the minimum MUST align to a common cadence. Common cadence ensures that squads are aligned, ceremonies like Program Increment planning become meaningful, understanding and aligning metrics across squads becomes easier and driving Agility at enterprise level becomes measurable and seamless.
  • Aligned roles and team structures: Standardizing roles across the organization and minimizing them greatly helps in driving autonomy faster. Also, having standard squad sizes help. I know of a customer who drove standardization of squad sizes by designing team tables that could exactly seat only teams that adhered to standard size.
  • Common Tools: If not others, I would advise to have a common tool to track both user stories and tickets when we restructure to squads. As much as possible the CI/CD or DevOps pipelines across squads must be alike to  enable faster collaboration and seamless tracking.

The concept of Aligned Autonomy might be against the core principles of Agile but if we want to drive agility at an enterprise level, we have found this to be a must.

Mastery

Mastery as a concept within our framework is something that we’ve already had the opportunity to explore in our earlier discussions especially on the People dimension. It has to do with the process of identifying and nurturing people and teams to be good craftsmen/women in the job they do. It’s all about getting full-stack engineers and creating high-performing squads that I had discussed earlier.

Though this area started-off with big challenges, this is an area where we can leverage engineering toolsets to make the exercise objective and thus adoptable. Since the time I published the People part of this blog series and now, we have had tremendous success in driving mastery at scale across many of our customers. This validated our faith in the approach. Since I had elaborated at length on this in the People part of this series, I will skip it here.

Purpose

The third and perhaps most important aspect of the three pillars to drive agile at scale is the enforcement of a personal purpose at every level of the organization. Once more I’m reminded of Daniel Pink’s words – “While complying can be an effective strategy for physical survival, it's a lousy one for personal fulfillment. Living a satisfying life requires more than simply meeting the demands of those in control. Yet in our offices and our classrooms, we have way too much compliance and way too little engagement. The former might get you through the day, but only the latter will get you through the night.”

How can a CEO ensure that the engineer in a squad understands the purpose of their existence in the organization and are able to relate their contribution to the roadmap drawn out in the Portfolio layer? How can we continuously measure the alignment of squad output to organization objective?

We have seen the following practices enable answers to the above questions:

  • Communication from the top: Organizations who managed to successfully transform themselves always had a direct channel of communication from the board or CxO layer to the larger organization. This communication is open and live and should clearly articulate the objectives of the organization for next quarter, year and 5 years.
  • Urgency: Unless there is a sense of urgency for change driven from the top, transformations fail. We have been through multiple such experiences.
  • Bottom-up business case: In the new team structure, once the organization objectives are advertised from the top, business cases must be created by the squads themselves and aggregated at each level. This gives a sense of purpose and accountability from all squads.
  • Open feedback: In the new redesigned Agile organization, it is extremely important for teams to have a view into each other’s business cases so that dependencies are managed between themselves and objectives are pre-aligned. It is a good practice to have all business cases available for everyone to see and critic in a collaborative tool.
  • Obeya: We can then leverage Obeya as a concept to continuously measure the progress of a squad or tribe to the business cases they have signed-up to and solve impediments if any.

The above is not a complete list but we have found organization adopt all or some of it and reap benefits in being able to drive purpose within each squad and thereby achieve meaningful velocity.

Thus, my view on the process dimension of scaling Agile model is not about advising which Enterprise Agile framework an organization must adopt or what Agile methodology they should adopt. I had briefly spoken about the latter in one of my earlier blogs and the State of Agile report gives enough indication that SAFe, SCRUM and Kanban are the most preferred. My view is that an organization that successfully manages to drive Autonomy, Mastery and Purpose at an enterprise level, would be an “Elite” organization as defined in the State of DevOps report. Adoption of these attributes is never big bang and it always follows the bubble-effect of starting small and scaling out.

Conclusion

This brings us to the conclusion of this blog post and the series “How to Successfully Scale Agile and DevOps”. As we’ve observed, the true challenge of scaling agile and dev-ops requires us to take an approach that addresses People, Process, and Technology in equal measure. It’s not only about creating a cross-functional, autonomous team consisting of full-stack engineers who are masters in their craft who come together to deliver business value with purpose than code, it is about transforming an entire organization into such teams.

I hope this series of blogs has offered you an insightful glimpse into the immense possibilities that scaling agile and DevOps has to offer and given you some useful information that can help drive decisions that make your scaling journey one filled with success. I wish you happy learnings, and please find time to post your comments, experiences and queries so that we can learn from each other.


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Building nimble and efficient platforms with modern microservices

Social eminence June 11, 2021

The world of enterprise software development came of age with the inception of ‘single purpose’ software applications aligned to a specific business function. Accounting programs in the finance domain were a common example. But with time, more applications arrived to spread the benefit of enterprise technology across multiple business functions such as manufacturing, supply chain and inventory management.

ERPs were designed to foster process efficiencies by transmitting information across business functions and collating the same on a central system for actionable decision making. Unfortunately, however, problems started creeping in when businesses customized these applications to cater to their own unique requirements. More often than not, increased customization rendered these applications slow and clunky, since they were too rigid to scale and were not created on open standards. Frequent iterations were a challenge due to the bulky nature of these applications. The IT department that was supposed to incite productivity became the reason for slowness.

Of course, ERPs are just one of many such systems. Other applications such as customer relationship management (CRM) systems also fit the description perfectly and are equally cumbersome. This class of applications are commonly referred to as monoliths.

From a software lifecycle management perspective, monoliths carry larger risk than smaller applications. Implementation, update, and maintenance of these applications can be a daunting task since there are too many moving parts that require simultaneous attention.

The Shift toward Microservices – Rewiring Software Architectures

Today, businesses mostly revolve around consumers. And it is customer experience that dictates business outcomes. Given this scenario, leading companies have set the standards for instantaneously responsive, personalized, and increasingly predictive real-time services across all customer touchpoints. At the locus of personalized service delivery lies smartphones which have made customers used to continuous improvements in applications instead of long upgrade cycles.

Technologies such as the cloud allows on-demand delivery of application functionalities, database storage, and other IT resources through the web rather than costly on-premise hardware solutions. However, simply shifting a monolith application to the cloud means relocating the same clunky software architecture on a separate system – along with all the shortfalls. So, companies need to focus on building nimble and agile applications that can accurately uphold the differentiation the business provides while continuously enhancing the capabilities they offer. This will allow them to engage customers quickly and meet demands as soon as they appear.

For instance, as Netflix made the switch into an online ‘only’ source, they had to focus on customer experience while ensuring that customers were getting access to personalized selection of content rather than browsing by genre. They must adjust personalized content and how it appears on millions of devices they support. Additionally, they also had to scale the application and content delivery rapidly. Especially with the release of a new show when viewership is expected to spike (take the instance of Orange is the New Black).

So, how did the streaming giant manage to achieve all this? The answer - microservices framework. Slowly but surely, enterprises across industries are adopting microservices which allow software. to be more agile and independently scalable. The pattern allows developers to localize change and reduce impact that might lead to lower availability.

With this architectural style companies have the liberty to deploy application functionalities as discreet lightweight services. These functionalities interact with businesses through a set of well-defined application program interfaces (APIs). This approach works well for most businesses since it allows them to deliver small application changes incrementally, while speeding up delivery and reducing service disruptions. Considering that mobile and other digital applications are extremely dynamic and require frequent updates, microservices prove to be extremely effective there too.

A recent survey reveals that 63% of companies are currently using microservices architecture, out of which 60% are doing so to attain faster turn-around times for new service and product deployments. with another 54% to foster digital transformation and, in the process, drive next-gen applications. It is important to understand that Microservices architecture does not essentially entail cobbling up several software components together. Rather, it involves the seamless functioning of independently deployable application functionalities that can communicate with each other through Application Programming Iinterfaces (APIs). These interfaces allow enterprises to escape monoliths, as they serve as a ´contract’ between microservices.

In order to simplify their transition from a monolith architecture to a micro services framework. , enterprises need to create a strategic transition roadmap right at the start itself. The ideal starting point for the adoption of microservices architecture would be to take an ‘A-B-C’ approach.

  • First Abstract: Create a layer of abstraction to access capabilities required to service the customers, employees, partners, and machines – API layer
  • Next Build: Align capabilities to leverage the APIs to improve user experience. Untangle the experience from how systems are architected
  • Finally Change: Break the back-end services to more manageable microservices

Simplifying the Transition – Overcoming Challenges that Come with Adoption

There’s no denying, microservices are poised to become the default model of software lifecycle management going forward. However, according to a survey from Lightstepa whopping 99% of the organizations have reported that they face challenges when leveraging microservices in software development.

Microservices are poised to become the default model of software lifecycle management going forward.

To maintain business agility, each component of a microservices-based architecture should be easy to develop, test, deploy, and release. Automating the entire software development lifecycle includes continuous integration, testing, and delivery (CI/CD) process in microservices. This helps the architecture to perform at full potential in terms of speed and consistency.

The trouble increases manifold when there’s a need to test hundreds of services, their integration, and interdependencies. One way to solve this would be to deploy service virtualization strategy for microservices. It can help provide developers and testers with tools to quickly simulate testing environments of a complex production environment, reduce dependencies and allow ease of integration. IT teams need to take on the responsibility to define the right capabilities (domains) that enable the functionality of a system.

With a microservices architecture that’s driven by APIs an organization might have to keeps track of hundreds of services running simultaneously. In such circumstances, keeping track of even the smallest of the incremental changes in an application is tough. As services are deployed, developers need to embed telemetry and analytics into the platform to simplify operations and change management.

Finally, every team involved in the microservices value chain needs to take responsibility for securing the services since it’s a distributed responsibility. Ensuring that calls are always routed through a secure service API gateway helps in establishing consistent security policies.

In short, teams developing microservices should care about ensuring quality, operating, and securing the service as much as they care about developing it.

Rounding Up

While software architecture design might not appeal to all decision-makers across the board, one can’t help but agree that software applications now lie at the core of how a business operates. Their nimbleness, overall performance, and resiliency directly impacts business agility and ultimately revenue.

Microservices represent a radical shift in the way how organizations approach application development while moving to a software-centric model. It’s time that businesses start exploring its potential to redefine the services that they deliver to their customers.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

How to successfully scale agile and devops – part 3: driving success with technology

Social eminence June 11, 2021

Welcome to my third blog post in the “How to Successfully Scale Agile and DevOps” series. In my previous blog post, I covered key propositions of the “People” dimension of driving agile at scale. In this blog post, we will deep dive and look at the critical “Technology” dimension and discover important elements that I believe can be leveraged to implement process automation and strengthen the digital strategy from a technology perspective.

The technology dimension of scaling Agile hinges on two ‘prerequisites’ and two ‘continuums’.

Prerequisites

There is a common pattern of two prerequisites in the technology area that successful organizations have driven:

  1. Technology Standardization

One of the prerequisites for the continuums to be successful is to reduce the number of technologies that enterprises must manage. In a large bank, I noticed that they had around 5 business process management (BPM) tools for process automation and case management and were evaluating a sixth one to be onboarded. This is a recipe for disaster as the more technologies such as BPM tools are utilized, more will be the need to have DevOps pipelines and more difficult will it become to drive continuous delivery.

One standard technology, say one BPM tool if we take the above instance into account, for each area in the simplified reference architecture given below would be ideal:

embarking

My suggestion while embarking on this journey would be to standardize on scaling Agile and DevOps tools and technologies that provide the ability to code rather than configure because the future is about running “everything as a code”.

  1. Legacy Modernization

Legacy modernization has become mainstream because of the advent of agile methodology, DevOps tools, and more importantly, micro-services architecture which demands monoliths to be broken. There are many digital strategies that pundits profess for legacy modernization but the ones I have found to yield benefit are:

  • Wraparound strategy where we wrap the legacy architecture with a modern layer which could be a microfocus layer, an application programming interface (API) layer, or a data lake layer.
  • Rebuild strategy where we identify digital use cases in the legacy applications and rebuild them in a modern way or rebuild the whole legacy infrastructure in a modern way.

Whatever be the digital strategy that works for you, please embark on a legacy modernization drive. Value is not realized just by changing things at the front-end layer, value can only be realized if it trickles down to the lowest layer of the reference architecture.

Continuums

Now that we have seen the prerequisites that can define your overall digital strategy, let’s come to the interesting part of ‘continuums’. I termed these ‘continuums’ because I don’t believe there is an end to these tenets. I am seeing them evolve rapidly and taking different forms and shapes.

Enterprise DevOps

According to the State of DevOps report by DORA, there is a direct co-relation between driving high maturity in DevOps and organizational performance, which thereby, creates better business value. The report found that enterprises that are performing well on the two key DevOps metrics of ‘throughput’ and ‘stability’; including faster lead times from commit-to-deploy, lower change failure rates, and faster incident recovery times; have a significant edge over low performing businesses.

To drive improvements in the above metrics, the most effective way of implementation that I have come across is to adopt the strategy of waste elimination from lean management. What is waste in software development lifecycles? Handoffs. Every handoff is a waste as it reduces throughput, increases the risk of quality, and creates differences. Given below are the different hand-offs that happen in a typical software development lifecycle (SDLC) and the DevOps tools and techniques that can be adopted to eliminate these handoffs.

embarking

H = Handoffs

Problems

  • People-dependent
  • Information leakage
  • Competency leakage
  • Accountability issues
  • Too many touchpoints for business
  • Cultural issues
  • Higher cost
  • Longer go-to-market (loss of competitive advantage and opportunity)

embarking

embarking

Each of the tools and techniques to reduce handoffs can be categorized into following areas of DevOps: Continuous planning, continuous integration, continuous deployment, continuous inspection, continuous provisioning, and continuous monitoring. Some of these areas are evolving, for instance, continuous monitoring is evolving into observability as a code. If you have not commenced your DevOps journey, then the best place to start would be in an area closer to production.

Since we are talking scale here, the key point to note on DevOps is to drive it at enterprise level and not at a project or program level. I strongly believe that enterprise DevOps definition available as a platform should be centrally driven while its realization can be done by the feature teams or squads. Though the initial few months (max. 6 months) can be driven through allowing closely monitored experiments across the enterprise, the learning of these experiments should be brought in to the central enterprise DevOps platform. Apart from implementing the tools and techniques called out earlier at an enterprise level, the enterprise DevOps team would also look at improving developer experience through developer portals which can be one-stop-shops to educate on the tools and pipelines in the platform.

I don’t think any enterprise can realize the true value of scaling Agile if they do not mature on their DevOps practices at an enterprise level and across all DevOps areas.

Platform as a Marketplace

Interestingly, as we speak of feature teams and squads, platforms are also becoming one of the key needs to drive Agile at scale. Though I will focus here on technology platforms, the same applies to business platforms like pricing, contact centers, and KYC platforms, among others. At an enterprise level, there are always redundant things that teams end up implementing.  Reducing this waste of redundant code is important to drive reusability, leading to standardization, higher efficiency, and improved governance and control. This can be achieved through enterprise platforms.

Below is a summary snapshot of possible platforms that I envision in an enterprise:

embarking

In a digitally mature enterprise, enterprise platforms need to be subservient to feature teams/squads. Platforms should exist to make the life of feature teams easier and simpler to add value to business. Thereby, platform backlogs must be filled by feature teams (specifically chapter leads) and platforms must be rated by feature teams for their ease of use and ability to add value. This inverts the pyramid of a platform setup which is important to drive digital at scale. Likewise, to setup a platform, a platform team must be equipped with the following squads (2-4 people per squad):

  • Onboarding and governance squad: The mandate of this squad is to onboard new tenants into the platform and define standards and guidelines that tenants must adhere to. In its matured state, this squad develops a developer portal with a predefined DevOps pipeline.
  • Business acceleration squad: This squad can be directed toward developing reusable business components by continuously looking at new components introduced into the platform.
  • Technology acceleration squad: The purpose of this squad will be to develop reusable business components by continuously looking at new components introduced into the platform and happenings in the industry.
  • DevOps squad: End-to-end DevOps pipeline to take any code introduced into the platform from the time of check-in all the way deployment and then monitor continuously.
  • Operations squad: This squad supports the platform and ensures that all environments (development, testing, preproduction, production) of the platform are running per the defined SLAs. This team is also responsible for upgrades, patches, SRE, and chaos engineering.
  • Innovation squad (Optional): This squad keeps experimenting to discover new things for the platform.

Finally, enterprise platforms should not be content with just driving reusability and standardization across the enterprise. In its mature form, I have seen them work as marketplaces— marketplaces where anyone in the world can contribute code to the platform. It derives its ability from the open source world but there is no reason why this cannot be repeated in an enterprise provided the platform squads called above can reach a high state of process automation maturity. I have seen at least three instances of platform marketplaces in large enterprises namely an enterprise DevOps platform as a marketplace, an API platform marketplace, and a digital component library platform marketplace.

embarking

Measuring effectiveness

As we embark on the two continuums, it is imperative that we baseline certain primary and secondary metrics at the beginning of the exercise and keep measuring them at regular intervals.

Primary metrics

I would lean heavily on the State of DevOps report on the primary metrics to measure. They would be:

  • Deployment frequency
  • Lead time for changes
  • Time to restore service
  • Change failure rate
  • Availability

I would suggest a useful, sixth metric:

  • Lead time to quality:
    Time taken by a team or a developer to pass a quality threshold set in the DevOps pipeline. This metric allows us to measure the time taken to pass each quality gate which, in turn, helps us to take corrective action and improve the gating policies themselves.

Secondary metrics

These metrics can be many though I have called out a few basic ones to start with. These metrics give us further insights on where exactly the problem is which is impacting a primary metric, and thereby, helps us to take the suitable corrective action:

  • Code churn rate
  • Build rate
  • Number of pull requests
  • Number of code merges
  • Code smells and warnings
  • Low level design analysis – CAST, JDepend

It is important to note that none of the above metrics (both primary and secondary) are derived or calculated manually. All are derived automatically through data available in the DevOps pipeline across the different areas. This will be a key implementation objective of driving continuous planning area of DevOps maturity. At HCL, we have a tool named Application360 that seamlessly integrates with most of the industry standard DevOps tools and thereby makes it easier to generate the above metrics.

To conclude the blog post with a quote from the continuous delivery book, “Hope is not a strategy”, and unless we drive the people, process, and technology aspects together, scaling Agile and DevOps and achieving digital maturity will prove to be an uphill task. However, while achieving this state may prove to be complicated, difficult, and resource intensive, the journey is well worth the effort and the rewards along the journey are immense. In the next and final edition of this series, I will be discussing the “Process” dimension of scaling digital successfully. See you then!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Scaling the digital execution model

Social eminence June 11, 2021

Companies achieving digital progression have developed a distinct structure that enables them to digitize their customer experiences at scale and at speed. Enterprises are also coming to terms with the fact that technology has shifted from being an enabler, to the key differentiator. This transition has made them realize the necessity of re-orienting themselves to operate like a hi-tech engineering company, irrespective of their business domain.

However, most companies find themselves facing a set of crucial questions while on this journey. What is the right operating model to optimize digital? How to scale Agile and DevOps initiatives? How to do things differently from the competition?

It is paramount for companies to identify their differentiators and choose the right execution model in alignment with the target areas. We know that customer centricity has so far driven agile programs, but it is also worth understanding if the processes and programs in place are conducive to agile execution. Hence, it is important for organizations to adopt a holistic approach that involves working on their strengths while mitigating their weaknesses when changing to the digital execution model. What’s more, with technology adopting a more front and center role for businesses, the agile model has expanded beyond customer-centricity concerns and today, is relevant to processes across the IT landscape.

Scaling and Pacing

In today’s digitally inclusive ecosystem, the agile model has become more mainstream and is being used in various programs across enterprises. For example, more and more back-office functions are seeing the application of agile in order to improve speed, bring efficiency to operations, and resolve issues.

In view of the agile model seeing increased enterprise-wide application, talent also needs to be scaled and optimized. While organizations focus primarily on process, for the agile model to bear dividends, the same importance has to be shown to people. Organizations must build and invest in their people, fine-tune their talent, and create an encompassing culture of engineering in order to get the best out of an agile environment.

Organizations must create an encompassing culture of engineering to get the best out of an agile environment.

The Key Tenets of the Agile Execution Model

Just like Rome wasn’t built overnight, the people-centric process must be allowed time to thrive. The changes will be incremental, and with right planning, successful execution will achieve the desired results. The execution model to scale agile programs involves:

People-centric processes require time, planning, and an agile execution model to change progressively.

  • Organizing: The product engineering team plays one of the most crucial roles in driving the agile program. They are responsible for building, running, and maintaining platforms that integrate the existing processes with the modernized tools and applications in order to make the product ecosystem responsive to Agile. A ‘discover-design-deliver’ model involves a thorough understanding of the product and the process that the team intends to build, develop it in alignment with the plan, and finally, deploy it successfully. It is worth understanding that the agile model requires product teams to live in perpetuity. Organizations need to migrate from project-based teams to product-oriented teams. These teams must have complete ownership of the products they develop. As a result, the team sizes will shrink, but they will live longer and be responsible for the products they develop.
  • Training: As team sizes get smaller, every resource must do the heavy lifting. This mandates team reskilling for organizations moving into the agile spectrum. The Agile principle will shrink the team size, but the cumulative value of the team will go up due to the higher value of the individual resources. Another factor, which will contribute to the increase in the team value, has to do with the increasing focus on hiring and retaining competent resources as opposed to senior resources. In terms of team building, this translates into a shift from experience-focused team building to expertise-focused team building. With all these changes in mind, it becomes crucial to train resources with the aim of increasing the value-per-person and make them take end-to-end responsibility of products. This significant shift in philosophy may be painful at first, but it offers greater collaborative scope and much-needed flexibility to optimize operations.
  • Operating: Agile and DevOps models are run on cutting-edge tools, but the process is run by humans. With team sizes shrinking, the overheads need to be reduced as well - since the teams won’t have the bandwidth for increased cycle times. This makes DevOps a key proposition. Additionally, with specific training, the teams can do significant automation upfront in order to manage their limited bandwidth better, and more importantly, increase the scope of validation. By facilitating It is, therefore, important for companies to realize that Agile can be optimized only when the resources take to the change proactively and utilize their improved skillset to achieve the best result. A smart enterprise can use the culture and tools in synergy, in a manner such that the latter augments the former, to accomplish its short as well as long-term digital goals.
  • Automating: A reskilled team’s capabilities can only be fully leveraged with appropriate levels of automation. It will not only standardize the output but also make the process cost-effective and reduce the time-to-market. The coding-testing-releasing-maintaining lifecycle of the product is critical to the sustainability of the overall operation, and automation provides the consistency that agile initiatives rely on. What’s more, automation also makes product scaling across the enterprise, what with its multiple teams at different levels of technical expertise, easier, lowering variability and improving consistency.
  • Measuring: A company that doesn’t measure its initiatives seldom improves. In the agile environment, enterprises also need to rethink their measurement processes, to ensure that they are capturing the business value created, instead of merely going by the volume of work.

Having access to the metrics alone won’t make a significant difference though. What is more important is to use these metrics to bring about a change in organizational behavior and philosophy. Story points on features will help paint an accurate picture of an organization’s operations and where it requires improvement and allow you to drive greater business value. The metrics are thus critical to improving operations and scaling initiatives by knowing which holes to plug.

While the agile model has been disruptive to industry mainstreams for some time now, it is rapidly becoming the new norm that is finding new applications every day. In view of this, organizations need to be steadfast with agile adoption to ensure that they don’t miss the digital bus. As a key service provider to some of the largest enterprises across the globe, HCL recognizes the opportunities of tomorrow and creates its services with an eye on the future. We identify with our clients, partners, and the ecosystem, and develop our service suite in line with the ever-evolving business landscape. Our vision is to create a sustainable future for the world through agile environment and innovative businesses.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

Reimagining the enterprise culture for digital adoption

Social eminence June 11, 2021

Industries across geographies are fast digitalizing operations in order to optimize output and elevate customer experience while creating a sustainable and safe ecosystem. In such an evolved business landscape that is perpetually innovating, the digital endeavors are multi-faceted and organizations need to be considerate of a quantum of crucial aspects. Cultural change in perspectives is one of them. While the industry leadership is waking up to the merits of digital transformation and adopting technological innovations, the organizational culture is often found wanting, causing roadblocks for the process of digitalization. It is, therefore, paramount to an organization’s well-being that an all-encompassing digital strategy is put in place that synergizes with a progressive organizational culture.

A HCL-StraightTalk collaborative study found that while 70% of the organizations already have a digital strategy in place, only 10% of the organizations have a definitive deployment plan. This reflects dourly on how organizations are getting more steadfast in developing digital plans, but are being unable to make a headway with their execution. The cultural challenges are the foremost reasons why most organizations are failing to see their visions turn into executable practices. For digitalization to be seamless, successful, and holistic, a cultural change is required across sales, marketing, IT, and operations.

For digitalization to be seamless and holistic, a cultural change is required across sales, marketing, IT, and operations.

Need for Change

The HCL-StraightTalk study found that 69% of the organizations feel that customer experience is at the center of digital transformation initiatives, but almost 90% of organizational leaders lack visibility into existing business processes. This does not reflect favorably on a business model that must tick the right boxes for sustainable business operations. In order to keep customers in the center of business operations and elevate their experience, organizations need to identify the areas needing change in alignment with its digital strategy. Three critical criteria that should be fulfilled before embarking on the digital journey are business viability, technological feasibility, and customer desirability. The digital strategy must revolve around these three aspects, thereby clearly emphasizing the changes required across spectrum.

The study found 92% organizational leaders find it exceedingly difficult to keep pace with the technological changes and only 64% are investing in digital innovations to leverage latest technologies. It is, therefore, our prerogative at HCL to add value to our partners’ operations by understanding their ambitions and driving their digital strategy and digital innovations to achieve scalable digital engineering. As trusted knowledge partners, we bring to the table the vision of a holistic ecosystem that vitalizes organizations’ ability of keeping pace with technological innovations.

Adaptability is the Key

Transformation, of any kind, needs time and resolve. However, seamless change is only successful in the end by adapting to the needs of time. It is therefore no surprise that the key doctrine of cultural change aligned to digitalization is a gradual acceptance of the changed status. Employees are the key drivers of any organizational change. Their involvement will strengthen the process and system to the point where digital is not just a tool anymore; it becomes the inherent modus operandi.

Clarity of purpose coupled with a fitting organizational strategy is paramount to optimizing digital engineering, and adapting to innovations perpetually is key to sustained growth. Human perceptions and behaviors must be more forthcoming towards the changing technological landscape. This will invariably lead to breaking down the silos that are omnipresent between business and IT, making digital innovations and transformation a seamless and an inclusive process. At HCL, while most of our clients have different objectives, the challenges they face follow a basic theme: culture and mindset. So, while the end objectives may vary, the challenges are common.

Incremental Change, Exponential Growth

As I mentioned, transformation demands patience and process. Digital is ubiquitous, and while organizations identify the pain points, and ambitions, and devise their digital strategies, the execution is stifled by the cultural challenges. Transformation is expected to hit such pockets of resistance and slow traffic. However, a robust digital strategy considers those as a part of the process and factors it in at the very start. At the heart of a successful digital strategy should be striking the right balance between desirability, feasibility, and viability. And, it can only be fueled by cultural change and engineering discipline.

While changing culture around digitalization, it is important to develop digital execution expertise internally by ramping up the available skills in the company. It is also equally important to be able to measure the digital transformation over frequent time periods in order to understand if expected results are being achieved or certain aspects of the transformation initiative is lagging. Agility is therefore another key cog in the digital wheel.

At HCL, we believe in valuing every aspect and pay meticulous attention to every component involved in the digital transformation process. This, keeps us ahead of the curve.


vsananth's picture Ananth Subramanya October 13
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Senior Vice President, Digital Platform Solutions, Digital & Analytics

How to successfully scale agile and devops – part 2: driving success with people

Social eminence June 11, 2021

Welcome back to the blog series on “How to Successfully Scale Agile and DevOps”. In my first blog post, I outlined the challenges faced by organizations as they attempt to scale up digitally and how the remedy lies in enacting change across multiple dimensions. The three key dimensions that require transformation for a successful outcome are People, Process, and Technology. I also mentioned the importance of Organization Change Management (OCM) in helping organizations fully enable the holistic changes needed to truly achieve successful outcomes from their scaling initiatives.

In this second part of the series, I will be discussing the People dimension and demonstrating how organizations can reboot and upgrade the “people element” within their Agile and DevOps teams to achieve agile transformation. So, let’s get started!

Cross-functional and Self-Organized Teams

Any organization that wants to scale Agile and Digital needs to orient its workforce to be self-organized and cross-functional. Self-organized teams possess unique skills and attributes brought together by a motivated group of people who possess the ability to make decisions and adapt to changing scenarios. Self-organized teams are able to take greater accountability of a feature or capability on any project and are constantly innovating. Cross functional teams are constituted of a group of people who are able to bring in all the skills required to collectively own a business feature or capability.

The best examples for self-organized teams can be found in the operating model of virtual teams who come together to play virtual games over the web. The best teams in this context are self-organized with no single leader. Each participant adapts to a servant or leadership role based on the skills needed to achieve the objective at any given point in time during the game. The switch-over of leadership is voluntary and it happens every few minutes.

Let’s assume a typical feature is being realized in a project through a simple three-tier architecture, the bare minimum roles that would be essential to create a cross-functional team are as follows:

  • Product Owner: Business representative who is the Product Manager for the feature
  • Analyst: Fulcrum between a Product Owner and the larger implementation team. In matured Agile teams, this role will cease to exist as the Product Owner matures to perform the duty of Analyst.
  • Scrum Master: Self-organized Agile teams do not need one. But let’s take a typical scenario in today’s world where Scrum Master are still required. A good scrum master needs to cannibalize his/her role but that’s a topic for another blog.
  • Developers: At least three developers, assuming we are working on a three-tier architecture.
  • Support engineer: Since we are talking about a cross-functional team, this team is expected to support the business feature as well.

Now this is only a 7-member team - small and nimble and I am even suggesting that two of the roles (Analyst and Scrum Master) must eventually vanish for an even more agile transformation.

Do your Agile teams look like this?

A common complaint by enterprises in the Agile world is the potential risk of chaos that overwhelm an organization comprised of self-organized teams that want to do things on their own. So, while it is important to be self-organized to drive agility, it is equally important to drive Aligned Autonomy to prevent chaos while driving Digital and Agile at scale. The subject of Aligned Autonomy is a critical component of the Process dimension of scaling digital and we will discuss it at length in a later blog post in this series.

While it is important to be self-organized to drive agility, it is equally important to drive Aligned Autonomy to prevent chaos while driving Digital and Agile at scale.

But coming back to the importance of having a truly agile team, let me share a brief story. Not too long ago, I was asked to assess and analyze the problems being faced by a team, let’s call them Team Trooper, that claimed to be working on Agile for nearly two years, but were struggling to see any results. Their cycle times had stalled at a minimum of 12 weeks with no further progress on the ground. Naturally, business leaders had started questioning the effectiveness of Agile and were considering remedial measures. So I took on the ask and went in to meet the team. Walking into the room I was stunned to see nearly 25 people. According to the program manager this constituted a “cross-functional” team since they needed many people to deliver the feature. While there were multiple problems with the team, my first step was to get each team member’s competency evaluated to be a full-stack developer or T-shaped engineer

The Elite - Full Stack Developers

Full-stack has become the buzzword in the industry. Everyone prides in calling themselves a full-stack engineer. In a recent interview I conducted of a “full-stack engineer”, I asked him how he would create a web service in the language of his choice. His reply was: “In the Eclipse project you are working on, you need to go to Options Create Web Services, give a web service name with the parameters being asked for and click OK”. I am not an Eclipse expert and I don’t know if the Menu option he cited is correct but one thing I knew for sure is that this person cannot be a full-stack engineer.

My wife and I both come from a coding heritage, so it wasn’t uncommon for this topic to turn up in our dinner table conversations. Are we full-stack engineers or have we lost the sheen of being full-stack? Knowing the full extent of this term makes me feel that the software world has come full circle. When I used to code in C and later in JDK 1.2/1.3, I used to write front-end code (sometimes HTML or Javascript, and sometimes in GWT/Swing), middle layer code in Java, design the database, and write the queries or ORM mappings to interface with the data layer.

I used to be good at query optimization and could look at Oracle’s query plans and optimize my queries and table/index definitions for better performance. I used to write the build scripts, test my code, and get it deployed across all environments. Me and my friends in the team used to have our own internal competitions on whose code compiles first, number of first-time compilation errors, the code with zero defects etc. We took complete accountability for the feature we were working on.

However, over the past decade or more, the industry has begun focusing on creating specializations and made developers myopic in their focus. We now have Angular 4 developers who don’t know anything about middleware code, APIs, data handling mechanisms, simple SQL queries, build and deployment, testing and more importantly not even other UI frameworks. This has resulted in the need for more and more developers to realize a feature and has been the biggest obstacle in creating truly cross-functional Agile team. That was one of the problem with Team Troopers. So, what is a full-stack developer or what makes a T-shaped engineer? For me, a T-Shaped engineer is one who depicts three types of skills: Technical, Engineering and Behavioral.

Technical skill: This skill is like a “T” which depicts the intersection between depth of knowledge in an area of expertise and the breadth of understanding across all adjacent technologies. This person has the ability to test their code and is also capable of being able to build and deploy their own code. For example, a full-stack UI engineer is one who brings in the depth of knowledge in JavaScript frameworks like Angular/React/Backbone etc., while also understanding and being capable of intermediate coding skills in all adjacent technologies namely Java/.NET, APIs, NoSQL databases or relational databases. They also have the ability to write not only unit tests but also functional tests in Selenium or another equivalent tool, possess the knowledge of static analyzers like JSLint/SONAR, and also have the ability to build and deploy the code leveraging GIT, CI tool and a deployment tool.

Engineering skill: This skill is often overlooked these days and is one of the major reasons for Agile teams not being able to drive velocity and faster release cycle times. It is the ability of a developer to bring in appropriate engineering practices during the implementation lifecycle. Working through a distributed version control system by following the Boy Scout’s rule, Pull Request rules, branching rules and discipline, daily code merges, daily builds, continuous deployment, following SOLID principles, writing code that passes the minimum checks in static analysis in the first run, following Clean Code principles, appropriate comments in GIT, regular updates in the asynchronous collaboration tools like Slack/MatterMost, and also making good use of Confluence/Wiki for project documentation etc. All these skills are critical to achieve velocity. In the book “Drive”, David Pink calls this attribute as Mastery and I have seen many organizations call this Craftsmanship. This skill cannot be learnt, it has to be practiced and practice makes a developer perfect to master the craft of engineering.

Behavioral skills: Cross-functional and self-organized teams are realized only if every person in an Agile team exhibits the appropriate behavioral skills. It is tough to define these traits as it depends on the culture within each team. Empathy towards others, servant-leadership, collaboration, trust and transparency are the basic necessary attributes. Many in the industry misconstrue this to be a bunch of outspoken developers. If you have listened to Susan Cain’s Power of Introverts TED talk, it becomes evident that 2/3rd of the population is comprised of introverts. Thus, by having an incorrect expectation on the behavioral trait, enterprises end up losing the good full-stack engineers. Get the teams to decide if an individual is depicting the appropriate behavioral traits rather than an interview with a manager or an architect to make that decision. But to get an in-depth definition of behavioral skills, I have found the definition of skill competency levels in the Dreyfus Skill Acquisition model to be useful and appropriate.

Framework for Scaling People: Dreyfus in a Diamond model and Team Configurations

Scaling Digital and Agile requires common team structures and configuration to achieve Aligned Autonomy and common cadence. Common structures need a common skill competency model on which people can be evaluated and mapped. If we do not manage to do this, we will end up having teams looking different and producing different velocities which does not augur well for an enterprise that endeavors to drive agility at scale.

It’s been a struggle in the industry to objectively define and adopt a skill competency model for the software world. The technical skills are easy to categorize. It’s always the mapping of behavioral competencies that have been a problem and that’s where we have found Dreyfus model to be useful. You may read about this model in Wikipedia where it is well-explained. Some organizations have chosen to adopt the SFIA model which is also good.

We at HCL utilize the Dreyfus model as the lens through which we can objectively define people’s competencies across the three skills of technical, engineering and behavioral. And in line with the Dreyfus model, we map people to five levels of competency – Novice, Advanced Beginner, Competent, Proficient and Expert.

We at HCL utilize the Dreyfus model as the lens through which we can objectively define people’s competencies across the three skills of technical, engineering and behavioral.

We are also moving away from the traditional pyramid model of structures of team competency mix to a more Diamond shaped model. There is enough research in the industry that states that Diamond models are productive and cost effective when we measure cost per unit of work (story points or functional points or complexity points). Does the Diamond model look alike across the organization? No. Based on our experience, we have realized that every application/product/platform goes through a 4-step evolution process namely: Ideation & Prototyping, Minimum Viable Product, Built at Scale, and Retire. The configuration of the diamond, we believe changes through this lifecycle as depicted in the diagram shared here.

Derfus

Realizing the People Dimension for Driving Digital @ Scale

At HCL, we make use of a number of techniques to evaluate, on-board and upskill our engineers by evaluating them on the three skills of Technology, Engineering and Behavioral. Technology skill evaluation is mostly automated through the use of industry tools with some amount of pair programming thrown in for Competent or Proficient or Expert engineers. Engineering skill evaluation is also automated through our own proprietary home-grown tool. And behavioral skills are evaluated by getting engineers to participate in hackathons and through the constant evaluation of their ability to work in a team effectively.

One of the key benefits of having an institutionalized common competency model across the enterprise alongside an evaluation mechanism is that it can naturally become a career progression roadmap for people, helping them to take ownership of their own competency development. In this scenario, people are encouraged to upskill themselves by going through the evaluation cycle and proving themselves to have achieved the next competency level.

At HCL, we make use of a number of techniques to evaluate, on-board and upskill our engineers by evaluating them on the three skills of Technology, Engineering and Behavioral.

With the overall view of the above topics, any organization that wants to transform its people to drive digital at scale needs to take the following steps:

  1. You need to define your own Dreyfus model framework, across technical skill, engineering skill, and behavioral traits that is contextual to your business.
  2. You need to redefine your entire HR systems and their skill models to adapt to the Dreyfus model.
  3. You need to adopt an objective evaluation methodology that is congruent to your model/framework.
  4. You need to subject the entire enterprise to this evaluation process so as to reconfigure it to the standards of the new model you’ve defined.
  5. Reconfigure people into skill levels.
  6. Reconfigure teams into a specific diamond model based on the lifecycle of the feature

The process for transforming the People dimension within the organization can be a daunting exercise. But it is fast becoming an essential one that cannot be ignored. As every aspect of the enterprise becomes more digital, the challenges that come with it require the lifeblood of the organization i.e. its people to be prepared for the next generation of challenges and opportunities.

Organizations need to consider the above said models and define their framework based on their specific needs. They need to create the tools and mechanisms necessary to drive the evaluation of these models and examine their own enterprises against their chosen model. And finally, organizations need to take on the process of reconfiguring their structures and teams to follow the Diamond model of configuration for optimized velocity, growth and innovation.

By taking these steps, companies are guaranteed to benefit as they experience a more consistent structure across the organization and create a more consistent culture, where people exhibit the same behaviors and share the same engineering ethics and technology traits. This enables the organization to drive Autonomy, Craftsmanship, and Purpose among their cross-functional and self-organized teams.

So, all the very best in your endeavor to reconfigure the People dimension of Digital at Scale. In the next edition of this series, I will be discussing the Technology/Process dimension of scaling digital successfully. See you then!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

How to successfully scale agile and devops - part 1

Social eminence June 11, 2021

I began my journey into scaled digital and transformation nearly a decade ago. My first encounter with Agile at Scale was at one of the world’s largest global aircraft manufacturers. On day one, the task before us looked impossible to achieve, however the results of following the Agile way allowed us to deliver on-time. It was in that moment that I knew that the world of the future was going to run on Agile models.

And my belief has been validated because today, over 97% of organizations practice agile development methods in some manner or another, while the number of people working in DevOps teams has risen from 16% in 2014 to 27% in 2017. Agile DevOps have truly become mainstream. However, in the last couple of years we’ve also seen many organizations struggle to scale up operations with these methods.

Today, over 97% of organizations practice agile development methods in some manner or another

With that context, I invite you to join me on this blog series as I share my experiences and learnings on addressing the challenges of scaling agile and DevOps in this series on “Scaled Digital”.

Challenges in Scaling

About three years ago, I served as a subject matter expert and advisor on agile development for one of the world’s largest banks. The client had built a state-of-the-art, business critical trade settlement platform with a small co-located, team. The client CIO had mandated them to make this a global platform and sunset regional specific platforms for the purpose of cost optimization and to harness cross-selling opportunities. To achieve this mandate, the client needed to accomplish a number of goals – to scale their team, to distribute them across the globe, and to maintain the speed and quality with which the development pipeline was already running. The client had tried this with their own captive in India, as well as with many other vendors, however, they could not manage to on-board even a single agile development squad successfully.

It was a grim situation. They relied on this platform as a critical revenue generator since it managed high volume transactions for their investors. As a business-critical tool, uptime and stability was integral, considering that gaps of milliseconds could leads to millions in potential losses. The client had already spent over two years on failed ventures with other technology partners before they approached HCL. Our team spent some time on their problem and came to understand this as a “people problem” issue and within six weeks, we had managed to on-board a team that satisfied the customer’s expectation.

As a business-critical tool, uptime and stability was integral, considering that gaps of milliseconds could leads to millions in potential losses

This experience was a seminal one for me. In the next 3 months, I got into many such conversations where customers were struggling to scale their . It highlighted what would soon become established fact – agile and DevOps solutions faced unique challenges when they were scaled up. These challenges in scaling, as it turns out, are far too many and as varied as the organizations implementing them. However, the common truth among all was that while methodologies improved outcomes within teams and projects, they failed when aggregated across the enterprise at scale.

Unsurprisingly, the problem areas were usually the same - from a discordance in organizational culture to issues with different agile development models adopted to geographically distributed teams utilizing varied delivery methodologies to monolithic architecture in legacy technologies which are rigid to change to sourcing models which hampered collaboration resulting in disjointed performance management systems, I’ve seen them all in my career. And having worked on solving such problems for companies around the globe, time and time again, it has become clear to me that the issue in the industry is not about ‘adopting’ Agile or DevOps, it is about ‘scaling’ digital, both Agile and DevOps methodology included, and getting the entire enterprise to run at speed.

Enacting Change Across Dimensions

The simple fact is that agile and DevOps methods can’t work in isolation. Organizations cannot hope to reap any benefits unless they take a holistic view of their businesses. Sure, it’s certainly easier for specific divisions and projects to leverage these methods for themselves. But the positive outcomes will be diluted if the rest of the overall organization remains rigid and resistant to change and cannot run at the speed of the digital corner.

I firmly believe that this scale digital problem has to be driven in parallel across the three dimensions of People, Process and Technology enabled by a strong Organization Change Management (OCM) drive. OCM needs to be able to engage and transform all levels of the organization both top-down and bottom-up.

OCM needs to be able to engage and transform all levels of the organization both top-down and bottom-up

The top-down approach is about mandates and strategy definition and leading by example. I have been through examples where CIOs have run their townhalls in sprints, contracting was done in Agile sprints with autonomous and empowered contracting squads, and KPI definition across partners in a customer enterprise was done leveraging SCRUM. It begins with creating focus groups who are mandated to drive this change. Focus groups need to have representation from all parts of the organization where this change needs to be done, especially representation from business, as Agile done in silo within IT would not yield the value that we would expect from its adoption. Marketing and communication management is equally important especially from senior management whose communication is essential in order to drive the journey faster. This change journey needs to be directed by both Agile and DevOps coaches who are also part of the focus groups.

In the bottom-up approach, People, Process, and Technology - each of these three dimensions play an integral role in ensuring a successful, ground up, and sustainable transformation for any organization. If you want to get your teams to be Agile, have the ability to deploy code into production daily, follow lean budgeting and have a squad with zero scrum masters and zero testers, and have an enterprise with zero support, then hang-on for the next set of blogs where we will get in to the really exciting part of this series.

In the next blog post, I will focus on the People dimension to detail out how to evaluate, identify and train people with the appropriate technical and behavioral competencies to drive Digital at scale.

I look forward to seeing you soon!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Gamification & artificial intelligence: is there a blue ocean for insurance providers?

Social eminence June 11, 2021

I recently bought a Fitbit to motivate myself to walk everyday as advised by my doctor. My wife got enticed by the look of the wearable and she ordered one for herself. Within a week, we were a part of a group, competing with each other and with others in the group. In a month’s time, I was part of at least two or three more groups and so was my wife. We challenged each other to walk the most and had our winning moments every week. My health improved, my doctor’s revenue came down, though he being my well-wisher, was happy with this outcome. However, there was one more stakeholder who immensely benefitted from this exercise – my health insurance provider.. It was not just my health that improved I’m sure, but the health of at least forty more individuals who were a part of the various Fitbit groups. Now that’s the blue ocean I’m talking about, one that I feel insurance providers have not harnessed to its potential.

Similar to the APIs exposed by Facebook and Google, most of the wearable OMCs (original Manufacturing Companies) have their own apps and sites. All the key data from the wearable is available for consumption through APIs (Application Programmable Interfaces) or web services if the user agrees for such exposure. A lot of these OMCs have built their own collaboration platforms among their user community. This user community and the data on their health is extremely valuable to health insurance providers. The buzzword in insurance is always “prevention”. What if insurance companies can indirectly influence the health of its users in a positive way? This would bring down their claims and thereby increase profitability.

Basic collaboration platform

The insurance provider can create a collaboration platform and get all its users on-board. Users with wearables can choose to register, making their data or a subset of their data available. For instance, users may not prefer to post their cholesterol or heartbeat data but would be fine with sharing the number of kilometers they have walked or the number of steps they take every day. The collaboration platform will use the APIs exposed by the wearable OMCs at a competitive price and automatically make the data available in the platform for use.

The insurance provider can create a collaboration platform and get all its users on-board.

Creating user communities

Once the users are registered, the next step is to create the user communities. A team is required to play the game and the communities/teams can be formed based on their physical location, hospital visits, doctor’s visits, relationship, and common ailment, among others. Every community would elect a moderator through online voting and it is the moderator who will administer the games. The moderator will also be responsible for marketing their community, thereby encouraging other users to join in as long as they meet the criteria for joining.

Play time

Once a community attains a critical mass, its play time. Gaming ideas can range from determining the person who walked the most in a week and the longest walk in a day to counting the highest calories burnt and awarding the most consistent walker. Games could become more and more interesting if we combine Virtual Reality with the games. For instance, there could be a hidden treasure at a location where the walkers in a community would have to walk to and find out. The person who unearths the treasure would be awarded points. The more data the users in a community expose, the more number of games could be formulated. On regular intervals, inter-community games could also be played and this can go on and on. The number of possible permutations are endless.

Leverage the power of a community

Once we have the communities engaged in the collaboration platform, the options to engage them further and make money through these engagements are immense for an insurance provider. Community-specific events could be organized. This could be fun, providing an opportunity for community members to meet each other and socialize while getting their health checked in the process. With the user’s health improving, the claim rates are prone to come down and even if they don’t, the information available is so valuable that it can be used to take corrective action and improve each user’s health.

Power of Natural Language Processing (NLP)

A collaboration platform will involve a lot of communication and knowledge-sharing among users. This information is a gold mine from which insights can be derived on what is working for users and what is not. This is where we can leverage the power of NLP to obtain insights from certain key words and keep building on this dictionary as the usage increases through the implementation of a machine learning algorithm. Insights could be as simple as the brand of a medicine that works, the best shoes to wear for a walk, the best wearable, and the co-relation between BMI index and health, among others.

Digital Marketing

Now that a collaboration platform is built, user communities are created, games are formulated to drive better health, and artificial intelligence is deployed to gain actionable insights – the focus should be on turning the platform into an ideal advertising space for all providers, directly or indirectly related to healthcare. The providers in question could be a pharma company, a sportswear company, a health drink company or a firm selling healthcare products – a set of like-minded people who influence each other extensively because it’s ideal to sell related products. The uptake in such advertisements could be quite high and hence the insurance company can demand a higher advertisement premium. The insurance firm can use this platform for their own cross-selling and up-selling of products as well. Again, the opportunities are immense.

The world is now a global marketplace where companies such as Facebook, Uber, and eBay thrive and flourish. With insurance companies having a large user base and the mandate on health insurance in most of the developed countries, it is a user base that can readily be harnessed for the above gains. The insurance companies have to be cautious on ensuring that privacy is not breached and other data which is already made available by wearable OMCs are optimally leveraged to drive better health. The insurance companies can have their cake and eat it too!


Meshach.Samuel's picture Meshach Samuel October 26
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Europe Solution Head, Digital & Analytics Practice

Digital transformation is upending talent expectations

Social eminence June 11, 2021

Introduction

2020 has forced many organizations to take on faster, iterative, and more aggressive approaches to digital transformation. They did this to accommodate new market rules, take advantage of new opportunities, and offer enhanced customer experiences.

With these efforts, leaders are also realizing that bringing along their talent, and addressing talent challenges, has never been more critical to the success of their transformation efforts. According to HCL’s Digital Acceleration report  that surveyed 400+ business and IT decision-makers across the globe, lack of skills within the organization is one of the top three challenges in furthering digital transformation. Leaders are increasingly paying more attention to this aspect in their attempts of digital acceleration.

Digital transformation initiatives reveal growing talent gaps

Organization-wide digital transformation initiatives typically address challenges related to four key areas:

  • Disconnected parts: Siloed divisions and multiple instances of software systems and inconsistent data prevent financial visibility and transparency and delay business decisions
  • Lack of end-to-end execution: Fragmented and cumbersome business processes that prevent efficiencies and collaboration
  • Lack of agility: Difficult to integrate new acquisitions and pivot quickly toward new sources of revenue
  • Need/desire to reinvent customer experiences: Provide a unique, faster, and engaging customer experience across their products and services.

These operational challenges are typically reflected in the workforce and how employees perform. With time, companies may have attracted and rewarded employees that know how to adapt to the inefficiencies, develop workarounds, and optimize how to function in complex environments. As a result, employees may be less likely to want to reinvent, or challenge the current model, because they’ve learned to succeed and survive in it.

In addition, companies may not have invested over time in evolving skillsets and behaviors, blending in new approaches/perspectives through new hires, or recognized the growing gaps in their workforce. These different forces compound the workforce gaps and make digital transformation harder to plan, initiate, and execute successfully, leading to non-optimized customer experiences as well.

Finding and engaging the existing talent potential

But in these gaps, leaders can also recognize the talent promise and potential that lie in their organization. The same adaptability and flexibility that employees have demonstrated in adjusting to complex, convoluted processes, and interactions in their organization, demonstrate their potential for reimagining, reinventing, simplifying, or automating the work.

To engage the workforce in the transformation process, leaders can focus on three key actions:

  • Show early commitment and authenticity
    • Leaders must be willing to demonstrate early support and commitment to the upcoming digital transformation
    • Being inclusive, inviting people to early planning discussions, encouraging them to reimagine what the future could look like, with visible support, are techniques that can be used
    • Leaders must do so with authenticity and candor, outlining the boundaries of the exercise, and sharing with selected employees how long and arduous the journey may be
    • Often, early workshops to discuss current challenges and how to address them provide a great opportunity for employees to lean in and demonstrate their interest and potential; this is a great chance to find employees with the courage and mindset to create the future, and not protect the existing turfs, power, or status quo
  • Give an opportunity
    • While assembling their core team for the transformation, leaders have a crucial responsibility to provide both a shot and a challenge to selected employees
    • The role must be both a real chance to design the solution and a personal challenge to learn new skills or levels of responsibility
    • Challenging people positively (not threatening them) can help them stretch and contribute in the most compelling way
  • Surround the team with expertise and encouragement:
    • Employees want to be successful and empowered; they also want support and access to expertise when they need it
    • To complement the knowledge about the company’s ways of working, leaders must recognize where external expertise is needed and find ways to provide it in a way that makes the core team more powerful (not inadequate)
    • Choosing the right consulting partner, providing the right training, connecting with others who can share past transformation experiences are ways to empower the core team
    • Finally, leaders must remain engaged, present, and supportive to help their core teams hit their stride

Understanding and managing talent expectations

Throughout the digital acceleration life cycle, the entire company landscape may evolve, including talent and its expectations. Most organizations will experience attrition at key roles during the transformation.

Throughout the digital acceleration life cycle, the entire landscape of an organization may evolve, including talent and its expectations.

Leaders need to actively manage their team’s evolving expectations by:

  • Letting them experiment
    • Experimenting is an essential part of learning and also aligning as a team; successful core teams learn to trust each other and constantly evaluate how to get the work done
  • Creating situations where it’s okay to say “I need help”
    • If employees are challenged in their transformation roles, they’re bound to experience situations where they don’t have the answer
    • Allowing them to partner with others, sharing where they are struggling, and getting them the help, greatly maximizes their chances of success (and for the core team too)
  • Using the core team’s motivation for a better solution to drive the change
    • Core team members can imagine the new world/solution together and keep each other accountable on their commitments
    • It’s often the sum of the individual drives of wanting to build something better that generates the organizational momentum at scale
  • Rewarding and recognizing through bonuses, promotions, or role expansions
    • Digital transformations are long, arduous journeys, and careers don’t take a break through them
    • Leaders can work with their HR counterparts to reward, recognize, and help advance the careers of those who are contributing and demonstrating strong value
    • Mid-transformation promotions or expansion of roles are often great motivators and opportunities to celebrate accomplishments
  • Staying connected to the mission, purpose, and ambition of the transformation
    • One essential role of a leader is to continuously reconnect the core team and stakeholders to what the transformation is really about, thereby improving the business and customer experience
    • It provides a chance for each employee to reconnect their own expectations with the broader purpose of the transformation, and a way to re-energize for upcoming milestones
  • Finally, how you run the digital transformation program is a reflection of what you’ll achieve in the actual transformation 
    • If the objective is to drive toward a more simplified, connected, and agile way of working, practicing those behaviors during the transformation itself is crucial
    • It’s a great way to experiment/pilot and learn as we go
    • It’s also a powerful testimonial to a leader’s commitment to actual and sustainable change

Conclusion: The no-going back rule

Recognizing talent gaps, engaging and unleashing talent potential, and managing talent expectations are key factors in successfully executing digital transformation and offering better customer experiences.

There is one more lesson that is really important. Once employees have tasted empowerment, independence, and experimentation, this is how they will want to continue to work going forward. The challenges, trials, and hardships that they’ve gone through also make them tremendous, credible champions for future change. As leaders, you may have created a new generation of contributors, and they need to stay engaged to continue to help the company evolve.

The digital transformation will also likely have completely changed expectations and norms on managing talent, sometimes forcing other groups to look at their own talent in more proactive and engaging ways. That’s a great outcome, and a great opportunity to engage your talent to stay ahead in the digital transformation game.


Associate Vice President, Digital & Analytics

From stakeholders to transformers: engaging executives to drive success - part 2

Social eminence June 11, 2021

“From Stakeholders to Transformers: Engaging Executives to Drive Success” is a two-part article series that first explores and identifies what makes a transformer, and then provides actionable advice on how to create your own transformers to drive business transformation and establish an inspirational vision. In the first article of this series, the five key traits of a transformer were defined and explained.

Make transformation initiatives impactful enough to compel a stakeholder to step up into the role of a transformer.

So how do you get to transforming leaders? As I emphasized previously, transformers are MADE, not born.

Even if someone doesn’t match the exact skillset outlined in the previous article, there is still potential for them to become a powerful transformer for driving transformation. You can play a vital role in creating stakeholders to transformers by following this advice along your journey.

The five rules to follow when creating your own transformers:

  1. Develop a relationship before you need something

    Depending on a workplace’s culture, relationships can often be transactional and based on task completion rather than genuine connection. Instead of simply picking someone who you think would be a good change-maker and assigning them this role as a task or deliverable, invest in the relationship first. Share information with this individual, reach out to them regularly, and take the time to get to know them.

  2. Find what drives your transformer

    Everyone has different things that motivate them. Find what fuels your transformer and run with it. Is it information about your project? Do they care more about recognition and access to future opportunities? Analyze the landscape and invite them to key events, if that’s the case. Is it to see your project as a way to accomplish their own objective? Is it more about playing their role to achieve a larger purpose? Or is their key motivator something else entirely? Find out what drives them, what they care about, what resonates with them, and invest in that.

  3. Learn how to set and tell the story

    Keep in mind that every transformation is a story waiting to be told, and good stories have the following components:

    • A challenge to address- What business problem are you trying to fix?
    • A vision for something better- What is the successful outcome you’re trying to reach?
    • Key contributors for and against- Who is in your coalition of the willing? Who’s not and do you need to win them over?
    • A roadmap- What are the three to four key milestones?
    • A little bit of magic- What makes your project special? What will compel people to contribute?

    How are you going to make this business transformation initiative impactful enough to compel a stakeholder to step up into the role of transformer? Tell the story.

  4. Continue to make progress and provide value

    No matter what, an initiative needs to be making progress. Think of progress as your fuel; it’s what establishes your credibility and makes people pay attention.

  5. Create the opportunity for the transformer to step up

    The final, and arguably most important rule for this business transformation journey, is creating an opportunity for your transformer to step up into their role and have a clear inspirational vision. You’ve invested in the relationship, you’ve set the story, you’ve made progress, it’s time to step back and give your transformer the space they need to excel. This may involve additional efforts to prepare them and provide guidance, insight, and clarity.

Build a composite transformer.

Even if you follow all these rules and execute the journey with few flaws, it’s unlikely that you will find all the traits of a transformer in one single person. That’s okay! Find what you need and who can deliver it. Some stakeholders are better at vision, others at energy or coalition building. It helps to look for these traits, but oftentimes, different people will bring different things to a project.

Look around at work, who’s displaying the traits you need, who could be a transformer if you helped them?


Associate Vice President, Digital & Analytics

A distinct line between tech adoption and digital transformation

Social eminence June 11, 2021

Over the last few months, many organizations found themselves forced to make the switch to remote operations and adopt a slew of digital technologies across the business, as they attempted to navigate the sudden, COVID-19-induced reality of social-distancing and lockdowns. Amidst all these paradigm shifts and the overall digital revolution, it is important to understand that there is a distinct line between tech adoption and digital transformation in this digital economy.

At its core, digital transformation refers to the process of placing the end customer, and subsequently all the stakeholders across the value chain, at the center of a business process experience. It is an inclusive process where all the stakeholders across verticals are in alignment within a business model that delivers value by leveraging the latest advancements in digital technologies like AI, machine learning, cloud computing, and IoT, in tandem with the people that make up the organization, to create and drive customer-centric experiences.

Merely purchasing and implementing a software suite in response to a localized issue does not equate to digital transformation. Organizations must therefore consider two key points— recognizing and responding to the shifting trends in consumer behavior and avoiding siloed initiatives that target specific issues.

Organizations must recognize and respond to the shifting trends in consumer behaviour and avoiding siloed initiatives that target specific issues.

Are your strategies adapting to changing trends in consumer behavior and expectations?

If there is one place where COVID-19 has placed us ahead of ourselves, it is the rate at which people are adopting digital channels to various ends. The post-COVID-19 world has led to unexpectedly increased customer readiness toward trying new digital channels for interacting with businesses. In most sectors, at least a 50% increase in digital adoption is coming from new users, and this trend leading to increased digital operations is visible across geographies and industries.

Some sectors such as retail and entertainment are performing better than others, and newer models of AI and machine learning in emerging fields of telemedicine and online fitness programs are gaining traction too. Traditional sectors such as banks, which typically have a relatively higher resistance to digital technologies such as IoT and machine learning, are showing an increased rate of adoption as well. Top players in banking are going paperless across their business processes by using smart solutions that leverage the latest developments in tech to deliver frictionless experiences to their end customers. As a result, banks are reporting higher satisfaction, greater revenues, and capabilities for dynamic expansion with agility for a digital revolution. The trend is clear with both neo-banks like Chime, and established global players like Citigroup, who are reducing their physical footprint and focusing on digital channels, improving efficiency while simultaneously driving better customer experience. Such overarching strategic moves are good examples of digital transformation done right.

To take a second example from a different industry, automotive insurance offerings can be enhanced by building auto-crash detection capabilities, and the towing, assessments, and claims processes can be taken digital. This will not only lead to highly optimal operations but will also help drive higher customer satisfaction and improve returns.

Digital transformation helps companies drive changes strategically through an ongoing process where being receptive to changing consumer trends helps in the formulation of effective roadmaps. These roadmaps can then be used to build better value propositions by leveraging the right technological advancements, leading to all-round benefits.

Are your products in sync with the new reality?

When big organizations shift to the latest architectures and deploy cutting-edge solutions, they often anticipate that these changes will help create better value propositions. According to a report, 62% organizations are struggling to define the objectives and outcomes of digital transformation. While digital transformation does optimize existing processes, real transformation places the customer at the heart of this change. How is the shift to cloud enhancing the value proposition of your existing service and client management processes? Are your product offerings in line with the latest trends in consumer behavior, and is the marketing team leveraging the right channels? To be able to give the right answers to these questions, it is crucial to avoid siloed initiatives that solve singular challenges and correspond to teams or departments rather than the organization as a whole.

To leverage these questions to drive positive change, senior leadership must not only embed true ownership in product roles but also ensure that the product strategy is fine-tuned to tasks that negotiate portfolio offerings with concrete features in alignment with the current organizational strategy. For example, by leveraging cloud infrastructures with IoT and simple protocols for intelligent devices, companies operating in the home goods and services industry can realign their strategy to deliver products that add value to the customer in an increasingly home-based digital economy. The key here is to recognize the links that bridge the biggest gaps between the organizational strategy and its execution.

While digital adoption and remote work are enabling companies to function in a mildly coagulated COVID-19 economy, top players are differentiating themselves by transforming the core of their business models. For example, global fashion giant ZARA which led the digital revolution in the fast fashion industry recently announced its plans to invest another $1bn to enhance its digital operations by integrating their online store with physical stores. As a result, the company reported a 90% increase in online sales during the global lockdown. Business models might differ across industries, but the ability to deliver value digitally is rapidly becoming a hot ticket to claim a chunk of the digital economy.

In the coming months, an increasing number of companies will succeed in optimizing their businesses through the adoption of digital technologies. However, being shocked into tech adoption is a far cry from true digital transformation. Enterprises that wish to come out of the current situation stronger, and with long-lasting competitive advantages, will need to take a more thoughtful, cohesive approach. This should involve leveraging all-round digital transformation to deliver offerings that respond to the needs of today’s digital travelers, and build truly digital, forward-looking experiences for their employees and customers.


darren.doyle_324386's picture Darren Doyle June 02
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Associate Vice President - Digital Consulting, Digital & Analytics

From stakeholders to transformers: engaging executives to drive success - part 1

Social eminence June 11, 2021

“From Stakeholders to Transformers: Engaging Executives to Drive Success” is a two-part article series that first explores and identifies what makes a transformer, and then provides actionable advice on how to create your own transformers.

Research has found that the top driver of project success is having actively engaged executive sponsors, people I like to call “transformers.” Surprisingly, research also shows that less than two-thirds of projects have these executive sponsors. So why the disconnect?

Because too many executives aren’t taking the leap from stakeholder to transformer.

Whether they have assigned power or not, anyone who has a defined stake in the outcome of an initiative is considered a stakeholder. This individual has the opportunity to influence, advocate, or resist change, and they ultimately may determine whether a change will stick. Think of Rosa Parks refusing to leave her seat on the bus, for example; she had no explicit power other than to stay seated. Parks simply had a stake and by advocating for change, she influenced civil rights in America in a dramatic way.

Being a great stakeholder doesn’t require intimate knowledge of the solution or a lot of time, but it does require curiosity, perspective, and a willingness to trust. Put action to those characteristics, expand your skill set, hone in on those around you, and you’re on your way to becoming a transformer.

Transformers often are the catalysts, accelerators, and drivers of business transformation. They step up beyond what’s expected of a good stakeholder and make business transformation happen.

THE FIVE KEY TRAITS OF A TRANSFORMER

  1. Vision that inspires and engages others

    Oftentimes in a complex initiative, the end-goal may seem out of reach or even impossible. Transformers make the connection between the vision and the reality of what needs to happen to make it possible, and they communicate that in engaging ways. Without an inspirational vision, it can be incredibly difficult to motivate and compel others to do their part for the change. However, unless you can ground your vision into actionable steps and roles, the final product will remain only a figment of your imagination. Finding someone who can articulate and support an inspirational vision is essential to project success.

  2. Energy to work through obstacles

    Think of transformers as catalysts that provide the energy for the transformation to happen. Transformers do this in different ways: they can motivate the team, they can create urgency for a resolution, they can focus the light on a key aspect of the initiative, etc.

    I work with a CFO on an 80-million-dollar program who is excellent at finding energy in different situations. He sometimes refers to himself as the “flight attendant during a turbulent flight,” because he can calm people down, he understands that people take cues from him, and he also helps to guide the moment with his enthusiasm.

  3. Ability to walk in other people’s shoes

    The best transformers step out of their own role and live the change through the eyes of a different stakeholder. This is often simply referred to as empathy, but I think of it more so as “empathy-forward.” These transformers anticipate what the change will do from the point of view of the recipient, they force discussions early, they show by example, they know when to pull back and wait, and most importantly, they listen and appreciate other perspectives.

    There is a CIO at an insurance company I’ve worked with who is particularly adept at this. She asks questions about personal impact, asks about plans, and brings up the difficult questions early, not to force the resolution, but to create the conversation.

    The best transformers step out of their own role and live the change through the eyes of a different stakeholder

  4. Power to reinvent where needed

    The ability to know when to start over or find a workaround is essential when it comes to being a problem solver. Transformers understand that things might not always work out according to their plan, so they create the conditions for a meaningful discussion of the issues, and they give themselves and others permission to reinvent when it’s the best option.

  5. Coalition builder

    Throughout a project, transformers must set the stage for different stakeholders to align on a common set of facts and perceptions surrounding the change. This trait also involves knowing when to ask, to hold, or to push. Great coalition builders find the common threads between stakeholders to unite them and drive the business transformation.

So what is key to driving transformation ? Keep in mind, transformers are made, not born. Everyone has an initiative has an opportunity to go from being a stakeholder to a transformer. In the second article of this series, I will walk through five rules to guide you through the journey of building your own transformers.

Stay tuned for Part 2: Your Road to Creating Your Own Transformers.


Associate Vice President, Digital & Analytics

Unleashing "No-touch" asset integrity management for the upstream oil and gas industry

Social eminence June 11, 2021

Unmanned production platforms can help O&G companies boost efficiency, safety, and cost-effectiveness and prepare for the new normal. 

Ever since the world's first completely automated, unmanned, and remotely operated oil and gas platform became operational in 2019, digitalization has emerged as a strategic priority across industry boardrooms. The Oseberg Vestflanken H platform comes with the promise of driving significant business outcomes in terms of cost, productivity, and employee health and safety, signaling the beginning of an era of digitalization and digital transformation and the end of an era of large crews working on offshore platforms. The paradigm shift to digital solutions and cognitive technologies such as augmented reality is especially relevant in the current, pandemic-struck reality, where social distancing, contactless operations, and automation comprise the new strategic mandate.

Digitalization is essential to enable actionable intelligence and a proactive operations approach.

How does this new reality affect asset integrity management (AIM)? Assets on offshore rigs and vessels such as pipes and tanks require thorough inspection, maintenance, and repairs regularly to ensure they continue to perform as per expectations. Oil and gas majors also rely on AIM programs to track asset deterioration due to corrosion and structural damage. Traditionally, human intervention has been key to the success of any AIM program. However, with the proliferation of IIoT, augmented reality, cognitive technologies, and advancements in sensor and communication technology, is the oil and gas industry ready for digital transformation through a 'no-touch' approach to AIM? The answer is: Slowly. But it's coming.

Why change?

The current situation with global lockdown in place has put the oil and gas industry in a tight spot. The U.S. diesel margins are currently at USD 11 a barrel, the lowest seasonally in the last decade. As margins shrink and demand tapers, the most obvious way forward to ensure profitability would be to cut unnecessary costs. The launch of Oseberg H hammers that point home as the platform cost 20 percent less than expected and has been built to ensure that oil production costs stay below USD 20 a barrel over the next 22 years. The idea was to build a platform with simplification at its core, minimizing capital expenditure, and leveraging smart automation to reduce operating expenses over time.

The U.S. diesel margins are currently at USD 11 a barrel, the lowest seasonally in the last decade.

Profitability is also closely linked with asset uptime. However, asset operators in the petrochemical industry are faced with aging assets that may lead to unprecedented downtime as a result of unnoticed material cracks and corrosion. The problem is compounded when incremental changes are made to the asset design, making it difficult to keep track of its structural integrity. There is also a lack of skilled resources in the space due to technology upgrades over the years and scarcity of new talent. With oil and gas companies relying heavily on human resources, a retiring workforce could result in business continuity challenges necessitates the adoption of a holistic, digital-first solution for AIM.  

From an organizational productivity point of view as well, paper-based processes, excel-based spreadsheets, and monthly reporting cycles are no longer sustainable. With thousands of physical assets – pipelines, plants, facilities, and equipment – getting connected to the internet, these legacy workflows cannot keep up with the amount of operational data being generated and are not conducive to providing real-time visibility into critical production processes. The need of the hour is to enable intelligent analytics and enterprise mobility to empower the operator, and in turn, reduce maintenance effort and cost by having a data-driven preventive maintenance strategy in place.

Further, there has been a call for bolstering employee health and safety measures in the upstream oil and gas industry. And the implementation of automated, remote AIM solutions will be a step in the right direction, allowing operators to monitor assets safely from onshore facilities.

Digital solutions for asset integrity management

Assets in the upstream oil and gas industry, such as storage tanks, pumping stations, filter skids, emergency shutdown devices, and wellheads are a part of a complex network of equipment. Moreover, not all equipment is fixed. Some parts are regularly moved from one location to another, making inspection planning an arduous task. That means there are too many moving parts and having a centralized view of asset performance is key to ensuring smooth production operations. That considered, digitalization via digital solutions and cognitive technologies such as augmented reality, are a prerequisite to enable actionable intelligence and transition to a proactive approach to maintenance operations. Oil and gas companies looking to drive production in a cost-effective need to minimize the possibility of unplanned outages, and there isn't an alternative other than predictive maintenance. Time-based inspection planning is dated and needs to be replaced with risk-based inspection planning, which is impossible without being able to analyze real-time, accurate asset data.

Oil and gas companies can leverage a range of technology solutions to usher in holistic digitalization and enhance their AIM capabilities, starting with:

  • Mobile technology: Streamline maintenance operations by providing operators with access to real-time data from oilfield sensor networks and Supervisory Control and Data Acquisition (SCADA) systems. Boost collaboration and communication among operators and field workers and reduce manual effort spent on data entry. Using augmented reality, guide field workers through the oilfield and assist with inspection and overhaul, reducing mean time to repair. 
  • Inspection data management (IDM): Migrate all legacy data to a digital and reliable IDM database and put in place standard processes to collect, populate, and analyze new asset data digitally within the IDM software. The software will serve as a single platform to manage all equipment types owned by the organization and provide up-to-date data for powering risk-based inspection.
  • Global Positioning System (GPS): Know where all your fixed and rotating assets are at all times, and save time and effort spent on tracking their movement or locating the equipment at the time of inspection.
  • Integrity Operating Windows (IOWs): Keep track of operating conditions in near real-time with early alert notification and take immediate corrective action to mitigate downtime risk.
  • Risk-Based Inspection (RBI): Build risk models that consume real-time asset data to help produce smart inspection schedules and allocate resources accordingly while delivering maximum efficiency, efficacy, and safety.

By accelerating digital transformation and ensuring the digital robustness of their AIM environment, oil and gas companies would be able to redeploy scarce financial and human resources effectively, helping them achieve their business objectives and thrive in today's VUCA world.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Customer engagement will drive travel & hospitality renaissance in a post-covid world

Social eminence June 11, 2021

Travel & Hospitality is arguably one of the worst hit industries by the COVID-19 pandemic. According to the World Travel and Tourism Council (WTTC), the pandemic has put around 75 million jobs at risk, while the loss in GDP for the sector is expected to surpass USD 2.1 trillion. At one point, nearly 96% of global destinations had imposed some form of travel restrictions, shutting off the influx of travelers. Sub-sectors have also been impacted severely: Airlines with capacity reductions of 70-80%, hotels with vacancy rates of 80%, and cruise lines, which became hotspots for infections, halting their services across the globe.

When seen from a value-chain perspective, the crisis appears to be even more devastating. The demand side has witnessed a significant drop in both new and advanced bookings, thanks to travel restrictions and the general environment of caution and anxiety around travel. This has also led to a high number of cancellations and refund requests, further leaching revenue. On the supply side, business owners now find themselves with a substantial amount of unused inventory, leading to dramatic schedule reductions and removal of service capacity. Downstream suppliers have been privy to the cascading effects of these losses and find their revenue streams choked off as well.

With the pandemic showing no signs of slowing down, the near future is going to be tough for the industry. Even if scientists miraculously find a cure within the next few months, public paranoia around travel and public venues will be at an all-time high.

To its credit, this isn’t the first time the industry has been delivered a harsh blow and survived to tell the tale. After the attacks of 9/11 and during the 2008 financial meltdown, consumers aggressively pulled back on discretionary spending, cancelation of planned travel, and businesses tightened their grip on corporate travel expense accounts. But the industry found ways to pull a renaissance of sorts by rethinking their operating models to emerge stronger.

The key to this resurgence lies in customer engagement, customer experience management, and process and business model reinvention in a manner that considers the ground realities of the post-COVID world. In the months, and maybe even years, that follow, the travel and hospitality sector will have to fight to win back their customers’ confidence and assure them that it is perfectly safe to leave their homes.

The Evolution of Customer Engagement:

According to a research by Preferred Hotels and Resorts, more than 50% of respondents worldwide stated that they will book a trip in 2020 as soon as the travel restrictions and lockdowns are lifted. The research further revealed that 75% of the respondents intend to travel with family. If things go well, most experts predict that the travel and hospitality sector will start gradual recuperation by the end of 2020.

However, organizations that would survive and thrive must consider the temporary and permanent behavioral changes among customers brought about by the current crises. These changes will play a major role and possibly define customer behavior and customer expectations in the days to come. Consumers will have two priorities when they travel post-COVID:cost-effectiveness, and health and safety. In a sentence, low-cost travel that assures a certain quality of hygiene, and promotes social distancing practices and norms, will do well.

For brands, building the two-fold image of being safe and economical will require innovations in the areas of self-service, social distancing, touchless interactions, and expanded digital content. Simultaneously, travel and hospitality players will also need to focus on building adaptable, flexible, and resilient processes and platforms that underpin effective customer experience management. This will also include providing customers with a means to interact with the brand from anywhere at any time, and facilitating a human experience, without necessitating close contact with humans.

For brands, building the twofold image of being safe and economical will require many innovations

Technology as a Customer Engagement and CX-enabler:

The travel and hospitality ecosystem is changing irreversibly. The industry, today, should look at this crisis as an opportunity to reassess their digital strategy. In the wake of the COVID-19 chaos, it is quite evident that consumers' perception of experience and engagement will have been molded by the current crisis. However, digital transformation around the key tenets of CX and customer engagement will be a key differentiator in this highly competitive market.

We are likely to see significant investments in the short/medium term on analytics that will enable the industry to conduct travel routes analysis and optimization for cost elements, and marry this information with external inputs such as route specific trends, competitive data, etc., to intelligently predict and fulfil demand. This will be complemented with a focus in the short- and long-term on business restoration planning by managing the constraints around demand, costs, staffing, and financial considerations. Journey maps of different segments of travelers will also need to be reexamined and reimagined, to drive maximum business value.

Going forward, contactless intelligent operations, large-scale automation, and initiatives related to customer safety and care, such as contact tracing, will all be part of the key digital themes dominating the travel and hospital industry.

Here are just some of the ways in which technology can enable them:

  • Analytics to map end-to-end customer journeys

    The travel and hospitality industry generates a massive amount of data across multiple channels and platforms. These include customer research, planning, price comparisons, actual bookings and reservations, itineraries, fare charts, enquiries, and customer feedback. Incumbents and new entrants alike can explore the use of big data analytics to harness this information about the customer journey and draw insights that can help them deliver more targeted services, better pricing strategies, and personalized travel experiences. Of course, data analytics tools will only serve the purpose if users are assured that their data is secure.

  • Facial recognition for touchless operations

    In a post-COVID-19 scenario, travel companies can leverage high-end technology such as facial recognition to build touchless operations. Instead of having customers wait in a long queue at check-in desks at hotels or airports, companies can use facial recognition software to scan guests and shorten lead times as well as ensure adherence to social-distancing practices. In 2018, a joint venture between the Alibaba Group and Marriott International announced that it was testing facial check-in technology, so, clearly, the technology is already being explored.

  • Artificial Intelligence and chat bots for smart rooms

    For the last few years, AI in the travel and hospitality sector is directly responsible for how people search and book accommodation and transport. Today, it is poised to drive even greater change. One great example of this is an AI smart-room solution developed by a leading hotel chain. Unlike conventional guest rooms, the AI-enabled rooms come with state-of-the-art voice control technology that delivers a more natural human-computer interactive experience. Such technology, when integrated with IoT, can open endless possibilities in hygiene management and personalized service delivery.

  • Robots as the new housekeeping staff

    Robots can ensure service continuity for hotels struggling with staff shortages caused by COVID-19. From cleaning rooms and managing guest luggage, to handling front-desk bookings and customer queries, robots can do it all. In the coming days, robots could well become an increasingly important part of the travel and hospitality value chain in a world where consumers will prefer touchless travel.

The Road to a New Normal is Paved with Digital:

As organizations in the travel and hospitality sector plan a recovery, they will need to tread carefully. Customers moving out of their homes or cities for the first time in months are likely to be overly cautious and have exacting standards. Old brand loyalties and affiliations will take a back seat to companies than can prove themselves fully equipped to tackle the challenges of COVID-19, and a misstep can have far-reaching consequences.

Planned application of digital technologies can help brands optimize costs, forecast and fulfill demand, plan for contingencies, and deliver exceptional experiences that are above and beyond customer expectations. Brands that manage this will find themselves retaining, as well as winning new customers and brand ambassadors.

In these dark days, I often recollect the words of Barbara Brown Taylor. "I have learned things in the dark that I could never have learned in the light, things that have saved my life over and over again, so that there is really only one logical conclusion. I need darkness as much as I need light." As the industry moves ahead, incumbents and new entrant in the T&H industry must heed the lessons from the current situation and prepare themselves for the possibilities, challenges, and necessary innovations demanded by the brave new world.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Are you resilient? Four pandemic-driven take-aways on managing change

Social eminence June 11, 2021

Like most, my life and universe have been directly disrupted by the COVID-19 pandemic. The impact on families, jobs, teams, roles, finances, and the economy are immense, and the fallout from the crisis has only just started making its effects felt. In real time, COVID-19 has transformed human behavior, interactions, and the rules of engagement at the workplace, making remote work and change management paramount.

This crisis is also providing brand new insights into how people can adapt at scale and speed, and with remarkable efficiency and resilience, especially with remote work. That, incidentally, is also my holy grail as a change management professional.

Resilience is typically defined as “the capacity to recover quickly from difficulties, or to spring back into shape.” In the field of change management, resilience is the ability of an individual or a workforce to seamlessly shift and adapt to a challenging new environment, job, or set of circumstances. Creating and engaging resilience is essential in driving change management efforts. But resilience is also incredibly hard to engage. From my observations of the past few weeks, I have captured four key lessons on what the current crisis is teaching us about resilience.

Lesson 1: Resilience is experience-based

Our ability to deal with the new rules or the “new normal” is directly connected to how we are experiencing the impact of the virus. If we or a close family member is sick, our emotional and rational experiences will be dramatically different from someone with no direct “exposure” to the impact of the virus. And the more this happens, the harder it would be to find a common ground to discuss how we can sustain change through astute change management. The more we push one opinion, the more the other side would reject it.

The takeaway for organizations is that they need to establish a foundational understanding of the current pains/issues and a course of action that will address them, before they can ask their workforce to adjust and change.

Organizations need to establish a common ground of current issues and a course of action to address them.

Lesson 2: Crises provide short windows to engage resilience at scale

Early on, when the pandemic was growing dramatically by the day, most people accepted or even embraced new rules for quarantining, shopping, and social distancing. Global companies shifted hundreds of thousands of employees to remote work to continue serving their clients. Small businesses adjusted too, creating new revenue workstreams when traditional ones were no longer feasible or available. What I found most telling was the willingness and speed at which most of us adjusted. The mobilization around a common goal (“flatten the curve,” for example) created a giant wave of immediate change.

Most organizations have thus shown that they can dynamically adjust, at speed and quite effectively, when the mobilization is taking place around a common rationale/story that is compelling and strong enough. While the window for collective mobilization is limited, organizations who rally around a common, collective urgency can change incredibly quickly.

Lesson 3: Collective engagement and commitment drive better individual resilience

Resilience is a very personal and individual trait. But today’s crisis also shows how people are using collective engagement and commitment to sustain their own resilience and fortitude. Think of the workers in healthcare, food/delivery services, education, public services, and many other sectors who find the strength to continue forward. For some, the motivation may be money-related, but it also comes from the value that they deliver to the community and to their families, and because of the commitments they’ve made. They are encouraged and supported by others to continue to push through and deliver essential services to the rest of us. Every day, we see new tributes to the “frontline workers,” and to those that have had to adjust to cancelled graduations, weddings, sports competitions, and so many more events. As a community, our recognition of the hardship and sacrifices becomes fuel for resilience.

The key takeaway here is that while change is inherently an individual process, the collective engagement of peers, managers, colleagues, and leaders can dramatically raise one’s own ability to change and one’s capacity for resilience.

Lesson 4: Sustaining resilience is both about necessity and compelling goals

Early on in a crisis, compliance can take center stage—we adjust to what authorities tell us to do, we modify our own behaviors because we’re either told, or strongly encouraged in the face of limited information. But sustained change and resilience ultimately need to be connected to a compelling, ambitious goal that can keep us going—flatten the curve, reduce deaths, find a vaccine, etc.

Ultimately, our resilience comes from our ability to translate a macro goal into a personal, meaningful one—protect our close ones, help our community, support others. If that connection between the bigger goal and the more personal one doesn’t exist, resilience falters.

For organizations, the lesson is that compliance is not fuel for real change and is often a dangerous illusion that leaders can misinterpret for engagement. Successfully mobilizing workforces for change requires a connection between the ambitious, collective objective and the personal, meaningful one. Resilience is about continuously answering the question “Why or for what/whom am I doing this?”

As I write this, our way out of the crisis remains unclear—how long will it take, how many more people will be affected, what radically different behaviors may become the new normal? But what is becoming more and more evident is that our collective and individual resilience, and how we engage it, will dramatically impact our ultimate success and what we learn from this crisis. As a change management practitioner, I remain unabashedly optimistic. By raising self-awareness and engaging our own resilience, we’re much more likely to succeed in creating and driving the sustainable change that we need.


Associate Vice President, Digital & Analytics

The tale of retail: preparing for a post-covid world

Social eminence June 11, 2021

The COVID-19 outbreak has forced enterprises to revisit, and relook at, their existing operational and business models. The rapid spread of the novel coronavirus (SARS-CoV-2) has prompted national and international regulatory authorities to restrict transportation and enforce nation-wide, lockdown measures. As a result, much like the Chinese city of Wuhan, many major global manufacturing hubs have either been completely shut down or have had their operations significantly reduced.

As expected, these restrictions have had a significant impact on supply chains. While every business relies on supply chains in one form or the other, the degree of reliance differs. As we tread steadily into a future of contingencies, some industries need a closer look in terms of the impact and adjustments. In this article, I will be focusing on retail as an industry segment will examine the impact and implications of COVID-19 for businesses operating in this domain.

Retail’s Challenges in a COVID-19 World

The World Trade Organization (WTO) expects global merchandise trade to decline by as much as 32% in 2020 due to the direct impact and fallouts from COVID-19. With the epicenter shifting toward major economies such as Europe and the US, the chances of a full recovery in 2021 are uncertain. The shifting dynamics of socio-economic interactions have also created an unexpected rift in supply and demand patterns, one of the many retail challenges in this scenario. As a result, there have been simultaneous supply and demand shocks across the retail sector. These shocks are expected to slow down the economy further.

Global merchandise trade is expected to fall by 32% in 2020 due to COVID-19.

In regions most affected by the spread of the virus, dubbed as ‘red zones,’ almost every retail outlet, barring grocery stores and pharmacies, has had to cease operations. Even in areas that are moderately and lightly impacted, there has been a steep drop in purchase volume from physical outlets. Most of the world’s quintessential brands such as Macy’s, Kohl’s, Apple, Urban Outfitter, and others, have acted upon government directives or company-level mandates to protect customers and employees and have shut down their retail outlets, globally. Many of these brands have announced indefinite lockdowns until further notice. Several other brands, such as Ralph Lauren, while announcing resumption of services from their virtual stores, continue to struggle with delivery challenges.

The impact is clearly visible across retail stock as well: L Brands, the parent company of iconic brands such as Victoria's Secret and Bath & Body Works, is down almost 50% year-over-year, despite strong cash reserves of over $2 billion.

Moreover, the state of uncertainty that exists around the length of the confinement period has shifted consumer interest away from and toward certain product categories across the retail industry. For instance, while the fresh food category has witnessed a sudden drop in demand, food products with longer shelf life have recorded a spike in purchases. This trend has created a lopsided sales and demand life cycle in the retail industry, defined by a marked fluctuation in demand.

While brick-and-mortar stores have taken a hit in terms of sales and demand, the effect on e-commerce has followed a different trajectory. Self-isolation and local quarantine measures have significantly increased e-commerce sales. As a result, many e-commerce providers are struggling to meet the massive influx of traffic and demand. This has, in turn, significantly impacted product life cycle management. Of course, this increase is not distributed evenly and is focused across a few categories reflecting some of the trends witnessed in brick-and-mortar retail.

The pattern of what is in demand in e-commerce has changed with a spike in the sale of essentials such as F&B items with long shelf-life, and healthcare products. A similar increase is visible for categories such as gaming and entertainment, as consumers act upon the realization that the current status quo is likely to persist for the next few weeks or months. On the other hand, categories such as apparel and luxury items have suffered as people are less inclined to make such purchases in these turbulent times. According to a Vogue Business estimate, luxury brands may lose up to €10 billion in profits in 2020, and start back on the long path to recovery only by the beginning of next year.

However, irrespective of the category, delivery of physical products is proving to be a major challenge due to the tougher movement measures implemented by governments over the last few weeks, severely restricting courier movement.

The uncertainty around sales and demand has given rise to several other challenges in the retail sector. On the inventory side, there is a dilemma in strategy formulation at the product and service level causing dramatic understocking and overstocking situations. As a result, CDCs are stretched to their maximum capacity and retail players face financial repercussions in the form of overinvestment or loss in revenue.

With global supply chains coming to an abrupt halt, businesses have had to adopt ad hoc supplier matrices to mitigate risks. This has led to retail companies facing numerous adversities on the sourcing and ordering front such as dealing with the uncertainties of makeshift replacements, and unpredictably longer lead times. Subsequently, businesses have had to sacrifice on supply chain visibility, leading to massive inconsistencies in operational data.

These challenges, combined with the lack of effective scenario planning, have given rise to governance issues. As a result, businesses are engaged in an uphill struggle to establish a collaborative environment that promotes business continuity and unfaltering customer experience. At the same time, they need to deal with confusion and lack of direction from the top, stemming from the absence of strong contingency and business continuity plans.

Developing a Course of Responsive Action

The COVID-19 pandemic has presented retailers with a test of resilience. Even beyond the pandemic, supply chains have undergone massive changes in the last decade, becoming more complex and globalized. The need for thoroughly redesigned operational models is, therefore, not new in the retail sector. However, COVID-19 has forced businesses into fast-tracking the entire transformation, and retail, as an industry, can be expected to undergo a major paradigm shift comparable to how 2008 transformed the financial and real estate markets, or how 9/11 transformed the travel industry.

In the short term, businesses will need to prioritize developing a completely Agile operational and cultural environment. This includes implementing a SWOT team to enable quick decision-making to track the business impact of the outbreak. This will allow them to monitor and rapidly react to both macro and micro factors. Additionally, they will need to critically analyze product launches and discontinuations. Lastly, they will need to abstract and act on crucial learnings from the ongoing crisis such as prioritizing the e-commerce supply chain while putting all planned commercial activities on hold.

In the midterm, we expect a growing focus on leveraging the lessons learned from the impact of the current pandemic to tackle risk. Retailers will also need to develop models that can forecast store re-openings and planned commercial activities. As the situation evolves, businesses will need to continue monitoring market dynamics at the macro and micro levels. Finally, as the crisis starts to fade, businesses will have their work cut out as they normalize supply chain decisions, renegotiate with suppliers, revisit market and product expansion plans, and redefine budget and sales targets.

While the short- and mid-term targets will be crucial in developing the foundations for proactive resilience, it is through long-term measures that retailers can prepare for a post-COVID-19 world and build a truly pandemic-proof, resilient organization. To achieve that, organizations need to take a planned approach to address the opportunities offered by this “new normal.” This will involve a greater emphasis on strategic sourcing and network planning, including integrating and creating visibility into end-to-end supply chain functions, focusing on agility and flexibility, strengthening disaster management, and finally digitalizing the entire supply chain.

This blog was also published in ET Insights.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Next steps: revisiting global healthcare in a post-covid world

Social eminence June 11, 2021

The impact of the COVID-19 pandemic is being felt across industries, heralding the onset of clear and irreversible changes to come. While BAU activities have slowed down or stopped for many industries, healthcare services is at more strain than ever before. Despite the full backing of governments and communities, public and private healthcare systems are fighting an uphill battle against a largely unknown enemy, while also coping with lack of adequate personnel and resources. And unlike other domains, lives hang in the balance.

As dedicated healthcare professionals adapt to meet these ever-changing challenges, it is important to constantly re-evaluate the current position of global healthcare services from a technology perspective—not just to plug the gaps and discover and implement improvements right now, but also to build significantly enhanced healthcare roadmaps for the future.

Re-evaluate global healthcare services with digital technologies in the COVID1-19 era for an enhanced future roadmap

In this article, we will discuss the key steps healthcare providers and enablers such as the government, need to take and promote to enhance their preparedness for crises situations such as COVID-19, from a technology and process perspective.

An Interconnected Healthcare Network

Technology already plays a major role as far as healthcare services is concerned. In fact, one could argue that it is one of the major differentiators between today’s national and global healthcare systems, and localized systems that existed earlier—whether it is collaborative research and real-time sharing of data across the globe, or the personal interconnected devices critical to providing real-time data in densely populated areas. We are taking rapid steps to take this partnership further with advanced analytics in population health management (PHM) platforms being implemented for various demographics.

Several countries have already taken a few decisive steps in this direction, further accelerated by the COVID-19 pandemic. For instance, in Germany, lifting restrictions on remote consultations has significantly improved connection between patients and doctors. Other countries such as Australia have also invested in technology-led healthcare, through ambitious plans for blockchain adoption in the near future. Without question, building a truly digital healthcare system is going to be tough, but this change will bring benefits across the value chain.

Take the US, for example. The digital development accelerated by the COVID-19 pandemic will have far reaching effects across policies for the three major elements making up the healthcare value chain: the payer, provider, and federal and state governments.

  • For Payers:

    There will be a pressing need to reduce, simplify, or eliminate co-pay and pre-authorization (PA) for treatment as well as for re-evaluating cover charges for COVID-19 and healthcare. In effect, this will accelerate employer-led healthcare while decentralizing online operations at the same time.

  • For Providers:

    The focus is already shifting toward enabling immediate and universal secure online visits to physicians, availability of online testing, and at-home preventive healthcare (for both physical and mental needs), and ensuring the movement of vital supplies through an intact supply chain that is integrated with the help of PBMs, Pharma, and Med-Tech organizations.

  • For Federal and State Governments:

    These developments will create the need for consistent regulatory guidance for the healthcare industry, connected patient health management programs that focus on Medicare and Medicaid patients, and maintaining the overall integrity of patients’ EMR.

Implemented properly, these changes will serve to make healthcare more available, agile, and affordable, which is vital for a country like the US, where in a 2019 Gallup survey, over 33% of all the American households surveyed, admitted to delaying care for serious and moderate issues due to the prohibitive cost and complexity involved in accessing healthcare. Combined with pre-emptive action and agile policy making by federal bodies, the healthcare systems would be much more capable of tackling and containing pandemics such as COVID-19.

Along with actively leveraging technologies, Centers for Medicare and Medicaid Services (CMS) has already taken several policy-level actions in this regard. One such decision has been ensuring physician payments for telehealth services, at the same rate as with in-person visits, for all diagnosis work. This is a good sign, and clearly denotes a willingness on the part of the federal agency to leverage technology for succor in these trying times.

The Technological Roadmap for Healthcare 2020, and Beyond

Posing a major threat to global healthcare systems, COVID-19 has firmly established the need for active action, and the establishment of a robust, collaborative, scalable, and agile digital healthcare infrastructure. Comprehensive planning focus from private as well as government bodies, and a technology-led roadmap that incorporates learnings from the current situation, will pay massive dividends in terms of saved lives, crises management, and global recovery.

To come up with an effective strategy and transformation roadmap, organizations in the healthcare industry will need to consider a few key points:

  • Ensuring Regulatory Sync-up and Synergy

    With the CMS approving Medicaid Section 1135 Waiver in over 23 states (guidelines are being constantly upgraded depending on the ground situation across states), the healthcare sector can expect more intervention by federal bodies in view of the current situation and beyond. This in turn absolutely necessitates syncing of regulatory guidelines across international borders with subject matter experts deciphering the best medical practices at all levels.

  • Undertake Strategic Digital Initiatives

    There will be a greater need to develop new healthcare delivery systems through digital advancements and provisions for affordable care measures at a lower expenditure. In order to do this, the industry as a whole will need to focus on building accurate analytical models by leveraging pervasive health data, focus on using technologies to facilitate less expensive, faster alternatives to doctor visits, and enhance patient experience while also improving the bottom line and maximizing profits.

    Industry leaders will also need to leverage cognitive capabilities to drive action in areas that require immediate attention in terms of identifiable business processes, and develop affordable care models. This can be done by sustaining existing investments made in core claim administration platforms, and achieving efficiency targets at scale.

  • Urgent dismantling of Digital Adoption Barriers

    Sustaining patient engagement outside of a traditional care setting is vital toward building rapport between patients and healthcare providers, and driving population management across risk pools. With the telemedicine market valued at USD 12,446.33 million in 2018, estimated to grow to USD 60,448.47 million by 2024, overcoming these challenges toward digital adoption is not only the right thing to do from a patient care perspective, but also a profitable venture to undertake.

  • Utilizing Next-gen Adjudication Systems

    Strong growth is predicted for the health plan core administrative market. This means that all health and third-party administrator plans are potential areas where adjudication systems can be implemented for core administrative growth.

  • Establishing a new normal through PHM, AI, and Remote Monitoring

    In this paradigm shift toward a digital healthcare infrastructure, it is important to choose between developing in-house solutions or buying a pre-built market solution with a proven track record. In the case of the latter, it is critical to evaluate vendor qualification through proper selection assessments. This can be done by evaluating cognitive platforms based on product features, costs, and required customizations.

Implications across the Healthcare Value Chain

The current global situation will have severe implications across the length of healthcare value chains. Understanding this value chain is important, as it is a vital tool in gauging productivity and overall satisfaction at each stage and touchpoint. Specially since the term value holds some ambiguity when it comes to healthcare—usually being a combination of one or more factors out of quality, speed of delivery, cost of care, or even availability.

However, as with any other industry, the payer and the provider are the two key touchstones in healthcare. Furthermore, the consideration of volume vs. cost is a prominent one as well, with the resultant implications being directly tied to what measures are used to achieve this balance, with technology and remote functionality playing a significant part in this process.

For the healthcare sector, the following table highlights how certain balances on the volume vs. cost scale are achieved through specific procedures and applications on part of both the payers and providers:

Volume vs Cost Classification Payer Value-Chain Procedures Provider Value-Chain Procedures
Low Volume + Low Cost Actuarial Valuations and Navigator Advisory
  • Digital Wallet and payment systems
  • Pre-Authorization of Treatment/Care
Low Volume + High Cost
  • Exchange Operations, Predictive Analytics
  • Quality Scores and Accreditation.
  • Configuration of protocols and devices
  • Optimization of funding and costs
High Volume + Low Cost Service Delivery through either phone or mail as well as Claims Submissions
  • Real Time Diagnosis
  • Follow-Up Protocols
  • Team and Wallet Configurations
  • Provision Accessibility
High Volume + High Cost Claims Adjudication Direct Payment through Non-Digital Wallets

Conclusion

The current scenario is rife with challenges and opportunities in equal measure for the post-COVID-19 healthcare world, almost certain to witness increased investments and importance given to global healthcare, including greater scrutiny and involvement by federal bodies.

A robust, forward-looking digital healthcare system built for compliance with evolving government regulations has a lot to offer, including enhanced customer interactions and improved efficiency through bots, telemedicine platforms, VR and AR for deeper patient-doctor communications, machine learning and AI to drive research at speed and scale, and blockchain and cloud-based platforms to secure medical data and provide efficient, scalable, and rapid crisis management capabilities. The greatest value of digital-led healthcare systems will not be delivered in the form of improved bottom-lines or increased revenues, but in terms of more customized, personalized, empathetic healing experience for patients, and the lives touched, improved, and saved.

This blog was also published in ETHealthWorld


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Impact of covid-19 on global supply chains & opportunities in a post-covid world

Social eminence June 11, 2021

Several times over the last few weeks, I have heard of 2020 being referred to as a bad movie with a particularly grim storyline. The repruccussions of COVID-19 are being felt more strongly with every passing day, and despite the unprecedented steps and cumulative efforts undertaken by governments, businesses, and individuals to stem its growth, the virus continues rampaging unchecked across the globe, causing loss of life and hitting businesses across industries and verticals. The fact that the origins of the virus lie in China, the de-facto factory of the world, has only served to accentuate the damage from an economic perspective with a significant percentage of supply chains reeling in shock and crumbling with each passing day.

As per a March survey conducted by the Institute For Supply Chain Management, nearly 75 percent of companies reported global supply chain management disruptions in one form or the other due to coronavirus-related transportation restrictions, and the figure is expected to rise further over the next few weeks. Other interesting figures that emerged from the survey included the lack of any semblance of a contingency plan for almost half the companies in case of a supply chain disruption leading back to China, and well over 50% of the companies also reported experiencing sudden, unexpected delays in receiving orders, a problem compounded by supply chain information blackout from China. 

Nearly 75 percent of companies reported global supply chain management disruptions due to coronavirus-related transportation restrictions.

The figures above serve to bring out the vulnerable state of global supply chain management, the lifeblood of our towering economies in sharp relief. However, the writing had been on the wall for quite some time. Consolidation of suppliers by geos, where efficiency has historically been the key strategy driver and limited focus on de-risking procurement and supply chains over the last several years, has contributed to the current state of affairs with shortages of key items globally. Barely 3 months into COVID-19 – the very foundations of the ultra-globalized economies that we see around us and live within today, have turned into question marks.

In this article, while alluding to the larger macro-economic problems, we will focus on the impact of COVID 19 on global supply chain management. In the later part of the article, we will also talk about new opportunities that may arise in a post-COVID world, as our race puts itself back together and attempts to glean learnings that would make us stronger, should such a situation arise again in the future.

With COVID-19 pandemic exposing the vulnerabilities of the global supply chains, global businesses must leverage digital technologies to rebuild economies and deliver business value.

Key Macro-economic Challenges Associated with Global Crises

The Manufacturing Challenge

Manufacturing today is a far more complex process than say just a few decades ago, with subcomponents required to assemble a single final product sourced from several places across the globe. The raw materials required to manufacture these subcomponents could also come from different countries and continents, and the finished/semi-finished goods may then require to be transported all over the world.

This massive dependency upon logistics make import, manufacturing, and export a difficult proposition in case of disruption to the supply chains.

The Procurement Challenge

At the other side of the coin lies the procurement challenge for the sourcing organization. In a globally integrated world, a drive towards efficiency has caused an increasing consolidation of production in lower cost geos – primarily based in China, Taiwan, Vietnam, or other low-cost economies. With the pandemic starting in China and hitting countries across the globe, and the resultant fallout and shortages, the need for distributing risk has become more evident than ever.

The Distribution Challenge

  • Distribution of products is going through some unique challenges with challenges in staffing of warehouses, a need for direct distribution, and more intelligent and responsive allocation across channels.
  • Retailing has also been impacted in a peculiar way – the lockdown and curfew scenarios across the world have led to a unique situation where there is demand as far as essentials are concerned, subdued demand in some niche areas, and big challenges in the luxury items segment – and we are likely to see several retailers down their shutters while many others will be severely challenged on operating margins and models.
  • On the consumer side, hoarding/ stocking of essential commodities and OTC medicines has led to unusual stress on the supply chains. This unnatural spikes in demand and the required supply fluctuations are extremely difficult to handle and together create a bullwhip effect in the entire supply chain often leading to artificial shortages.

Post-COVID: The Brave New ‘Digital’ World

From an industrial perspective, the current situation is likely to accelerate digital transformation initiatives for businesses across the globe, as they are forced to be face-to-face with their weaknesses and vulnerabilities. Technology-led business models will emerge as more critical and important than ever and will play a key role in defining strategy as we reimagine the global supply chains of tomorrow.

Based on lessons that are being reinforced and validated in the current global crises, there are several ways in which businesses can go about creating resilient supply chains in a post-COVID world. For one, there is an urgent need to reduce dependency on physical labor across transportation, logistics, and warehousing. This can be enabled through core digital technologies for Industry 4.0 like IIOT, Blockchain, Control Towers, AI/ML enabled demand-forecasting, rule based and self-adjusting stock allocations, autonomous devices like AGVs, drones, etc.

Factories that can modularize production and shift/adapt lines due to demand changes, will be the norm of the future. They would be backed by supply networks capable of communicating intelligently with one another, compounding their effectiveness and agility. Businesses are going to pay a lot of attention to making critical systems available on the cloud so that they can be remotely accessed by employees as they work from home. Safety will also be a key factor and supplier risk management will be at the core to all planning initiatives. One of the few positives of the COVID-19 scenario has been exposing us to the possibilities of remote working across industries, domains, and businesses and if sustained in the post-COVID world, this trend will lead to a renewed focus on environment-friendly operating principles.

All this notwithstanding, the human element is the most important one that will emerge as we progress in the COVID-19, and across to the post-COVID world. Given the projections on the number of infected/ hospitalized, it will have a cascading impact on the availability of even the core services. The situation in Italy, Spain, USA, or China worsened further due to the essential services providers like medical professionals, nurses, and forces impacted by the virus. This is also visible in some of the newer impacted areas like India as well.

At HCL Tech, our Supply Chain Practice has been at the forefront of leveraging digital technologies to ease and build global resilient supply chains. We continue to be committed to continuing our focus on leveraging key technologies and offerings and to support businesses with our expertise, as they recover and use their learnings from the current crisis to bounce back stronger and more resilient.

Some key elements, that will prove crucial in the supply chains of tomorrow include: 

  • Intelligent Procurement – To help organizations understand where and when to source using advanced machine learning algorithms based on past purchases, commodity pricing, agro and industrial trends, etc.
  • Supply Chain Control Tower – A single source of truth from sourcing to delivery for all trading partners, to see and adapt to changing demand and supply scenarios across the world.
  • Supply Chain Data Management with intelligent automation and analytics – End-to-end information management, taking the form of a data vault of sorts to capture supply chain transactions accurately with high consistency and minimum redundancy. This will help supply chain organizations gather insights around supplier performance, supply chain diagnostics, market intelligence, and risk management.
  • Supplier Risk Management – N-tier risk management helping organizations model cost structures, trend performance data, and visibility into extended value chain to keep abreast of any supply disruptions and secure capacity. This could help companies avoid sudden disruptions in supply chain and deal with lack of information – something that many major global companies including Sony, are facing today.
  • Supply Chain Simulation – Modeling new supply chain strategies based on business/operating model change, current and/or future supply/demand/logistics constraints. Helps to validate and identify the best cost-efficient network to achieve the necessary service level across the value chain.

To conclude, from a purely business perspective COVID-19 presents a slew of serious and sometimes unprecedented challenges for organizations cutting across the business environment, including a possible liquidity crunch, global supply chain disruptions, increase in trade barriers, and a shifting consumer mindset. However, the post-COVID world will see digital technologies playing a critical enabling-role in delivering improvements throughout the breadth of businesses, including more resilient supply chains, significantly enhanced user-experiences, and intelligent optimized processes to deliver business outcomes.

This blog was also published in Entrepreneur India.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

Human-centered design: a people-first innovation mindset

Social eminence June 11, 2021

It all starts with changing the belief that there’s a solution waiting to be discovered for the human problem you’re trying to resolve — and for the people dealing with that problem. Human centered design (HCD) is a framework central to any innovation process. Optimistic, empathy-based, and holistic, a human centered design ensures that regardless of the tools or processes used (like design thinking) the result will be purposeful, useful ideas that solve problems for people they are intended to serve.

HCD: A Process Focused on Human Needs

HCD is purposefully nonlinear. It requires cross-functional teams to discover, explore, and resolve problems through iteration and radical collaboration.

An HCD approach can not only solve problems but also help avoid them in the first place. Grounded in a deep understanding of the user, aligning around their shared problems, HCD guides idea generation based on factors like desirability and so on.

HCD is often confused with design thinking but they are not the same thing. Design thinking (DT) is a collaborative process based on co-creation that works to identify and create desirable and adaptable products and services through iterative steps, including empathizing, defining, designing, ideating, prototyping, testing, and repeating. HCD is the litmus test which guarantees that, in the end, the product actually solves real human and business problems.

For example, we used a design thinking process to conceptualize, from scratch, a digital product solution that would disrupt breakdown management for the trucking industry. We used HCD to ensure that the end product served and solved the human needs of each player in the breakdown process – from the driver to the mechanic.

Without HCD, the idea may have worked technically but not been adopted by the end user. People tend to adopt things that they find useful.

An HCD mindset also has the power to forge alignment across organizations. It establishes a common purpose of the effort.

This is why we believe in creating value propositions on the basis of a people-first design process at an engagement’s outset and focus on using HCD throughout.

In this quest, HCL’s end-to-end HCD solutions involve:

  • Learning and understanding user needs and business goals.
  • Innovation, design, and technology enablers and accelerators.
  • Creating and considering experiences for both the customers and the business.
  • Building and deploying solutions with measurable outcomes.

The Value of Understanding the Human Perspective

Design is about solving human problems. To really understand human needs, challenges, pain-points, concerns, behaviors and what drives them, an HCD mindset is imperative for exploring potential business models.

Applying an HCD-first mindset and approach ensures value creation for businesses and their consumers. In a fast-digitalizing business ecosystem, design thinking plays a crucial role in aligning products to customer expectations.

As business models shift, HCD helps businesses forge well-rounded digital strategies to develop an array of solutions for future end users. Organizations with human centered design thinking at the core of their operations – like Apple and Google – use HCD to create cutting-edge value by understanding their users’ purposes and goals. In knowing for whom they are designing, what they want to achieve, and why, companies like Apple and Google ensure that their design teams’ future efforts lead to a continuous and desirable product evolution and improvement.

Scaling Digital with Human-centered Design

Human-centered Design (HCD) is the litmus test which guarantees that, in the end, the product actually solves real, human, and business problems.

Through constant innovation across industries and cultural touchpoint, digitalization has made our lives more technically dependent and less human reliant.

This has brought us to a crossroads where technology has to be more human-friendly and attuned to our lives as it replaces ever more spaces of human effort. It should be capable of balancing operational efficiency with an optimized customer- and human-centric experience.

HCD acts like a Greek choir in this new landscape, whispering human perspectives and needs in the ears of those making digital decisions.

Embedding HCD as a strategic perspective accelerates the transformation and also increases a design’s value. Besides, it develops a creative culture of taking risks, trusting employees, accepting the incremental failure, and learning from it to improve and innovate.

Embedding human-centered Design (HCD) as a strategic perspective accelerates an enterprises' digital transformation initiatives.

Corporations are now establishing a human-centered mindset because they understand that a brand’s credibility depends on the impression it creates on the customer experience.

Applying a human-centered design approach ensures value creation for businesses and their consumers.

Hyper-personalization of products and services and customer-centric designed experiences – all can be credited to HCD thinking. Amazon Go or Apple smartwatches may just have flooded the market but the concept of designing for human need vs. just what a business wants to sell is not new. Organizations have long realized that they need to be omnipresent among existing consumers. To do so, they must offer what people actually want and need to solve real-life problems while also looking to break new ground in new directions for as-yet unmet needs. For instance, Apple’s iPad – a product that some argued at the time was a solution in search of a problem.

The HCD approach only underlines this market dynamic, assisting the organization leadership to develop the most effective solutions, business models and digital strategies aimed to solve real-human needs and solve their problems. As technologies become more advanced, HCD will ensure that smart solutions not only meet immediate customer needs and expectations but also factor in social considerations like human needs, wants, and behaviors.

Leading the Way: HCL’s Innovation Credibility

With HCL’s expertise and advanced competencies around human-centered design, the company has partnered with organizations across industries and geographies. Among them is a European banking major that is building a co-innovation lab to drive customer experience with a fully customizable application. The lab enables collaborative concept sharing and prototype development, which enables HCL to deliver a platform that aligns risk and finance datasets while integrating business processes.

Another partner, a world-renowned football club wants to increase their supporter base and optimize the experience, before, during, and after a match. Attracting untapped swaths of their international fan base was negatively impacting the client’s digital revenue.

HCL helped reimagine the fan experience by developing a personalized digital platform that delivers meaningful multimedia content, analytics, e-commerce, social media integrations, gamification, and real-time match experience. By diving into the life of the supporter, understanding their preferences and by analyzing trends, HCL created a roadmap to create a one-billion fan base and media reach. HCL also deployed a single digital platform to connect various channels like merchandising, ticket booking, player stats, social media, etc.

HCL partnered with a major European automobile maker to identify and suggest IA/UX best practices to be adopted and integrated across product life cycle management. Based on the reliable representation of audience, HCL identified key user goals, needs, challenges, and expectations. We came up with a design thinking model that helps users optimize their KDP application. The modern interface also enables a real-time, 360-degree view of all parts, resulting in an elevated, more informative, and useful customer experience.

The HCD development space may be nascent but is rapidly growing with an increasing number of companies and agencies specializing in HCD-driven digital solutions as technology advances and user and customer-centric experience becomes ever more necessary.

Figures indicate that HCL is doing it better than its competitors. A New York-based environmental group stated that HCL’s HCD digital solutions resulted in improving quality by 86%, increasing productivity by 68%, and enhancing customer satisfaction by 76%. While this underlines our innovation efforts, it also helps serve as a differentiator. HCL is a knowledge partner in understanding the human side of the digital landscape by creating robust and holistic business ecosystems with a human-centered mindset.


Senior Vice President - Digital Consulting Practice

The 3r framework: a business first, technology second approach to digitization part 3: reimagine customer experience

Social eminence June 11, 2021

Our first post of the series introduced the 3R Approach to Digitization and its three dimensions, i.e., Rethinking products and services, Reimagining customer experience, and Re-engineering the value chain. Then we dove into the first step of how enterprises could drive digitization by rethinking products and services. In this post, I’ll be discussing the second step of the 3R approach – reimagining customer experience.

In today’s technologically disruptive world, it isn’t enough to simply provide an amazing product. Customers want more. They demand experiences that engage and amaze them. This shift in consumer expectations has already impacted business culture and strategies across industries.

If we rewind the clock a couple of decades, we can see how this shift began. Before Google was synonymous with ‘search,’ searching was an imperfect activity. Most people would target specific websites or stumble across links through other means, with no clear assurance of what they would find. Early search engines opened up the World Wide Web and made it easier to explore but the results were far from perfect.

Google radically transformed this activity. They reimagined the search engine into what we take for granted today. What differentiated Google wasn’t just its speed and effectiveness, but also its simplicity. Google showed the world that there was a better way to search — a way that was simpler, faster, and more effective.

Reimagining customer experiences has powerful outcomes and benefits for any business. It can turn users into evangelists, and products into indispensable, permanent fixtures of normal life.

Just ask Google, Apple, or Tesla.

Each of these companies designs their products and services with the customer as the sole focus. They dominate their competition by integrating the values of humanism, design thinking, and customer centricity into the technology of their products, resulting in a customer experience that is unparalleled.

As personal technology has evolved, so have the challenges for enterprises. Users have advanced from desktops to laptops to tablets and smartphones, and this intimacy of technology has given rise to a whole new generation of consumers.

Businesses who wish to win over these digital natives have to learn how they experience their products and interact with technology. Organizations that have predicted, and even directed, these user preferences have experienced immense success. The most famous example is Apple’s reimagining of the cell phone with the iPhone and music with the iPod. The result of Apple’s innovation is soaring profits from USD 38 million in Q1 2001 to USD 565 million in Q1 2006 to a staggering USD 20.1 billion in Q1 2018.

Clearly, rethinking products and services, along with reimagining customer experience can transform a company’s bottom line.

Reimagine the Power of Voice

As we’ve seen, in less than 10 years, the preferences for personal computing has transformed from desktop systems to mobile smartphones. The interface evolution with technology has been a defining attribute of customer experience and continues to evolve.

We are already witnessing the rise of one such branch of evolution — the rapid emergence of voice assistants, which have gone from our cell phones into our homes. Users can now simply ‘tell’ their machine learning and AI-powered assistants to execute a number of everyday tasks – from ordering groceries, making appointments, playing music, or simply controlling the household light and heating.

Products like Amazon’s Alexa and Google Home are the embodiment of simplicity, seamlessness, and, most importantly, a sophisticated and invisible technology doing its work unobtrusively from behind the scenes. The emphasis on delivering back-end technological sophistication via an elegant interface is what has made voice assistants an increasingly desirable product. Furthermore, the convergence of AI-powered natural language recognition with personal voice assistants has already put us well on our way to a new commercial segment — voice commerce.

Already, nearly 20 per cent of US consumers have made a purchase through voice e-commerce, while over 33 per cent are planning to do so in the next year. And as NLP technology progresses beyond the 70 per cent accent recognition, it may become a commonplace global phenomenon in less than five years. To buy something, simply ask for it.

Adapting Technologies

We’re witnessing similar technology convergence developments on the road. Take the case of personal transportation with companies like Tesla. The technology behind Tesla’s self-driving cars possible is built on the same principles as those used by SpaceX for the automated landing of their rocket boosters. Technology is being adapted across industries to reimagine customer experience and launch a new era of innovation.

In areas such as retail, we see similar examples of reimagined customer experience forging brave new paths. Today, a consumer can walk into an Amazon Go store and pick up their groceries and simply walk out.

Other companies such as Alibaba are approaching the same problem from a different angle. Alibaba’s Hema chain of supermarkets are hybrids of offline and online systems that seek to make their mobile app the heart of the shopping experience and reimagine both domains. By fusing the offline and online experience through a customer’s mobile device, Alibaba placed the power in the customer’s hand and gave them a unified yet flexible experience. For markets where the costs of large-scale technical investments are prohibitive, this hybrid approach may prove to be an innovation that serves billions.

Reimagine Leadership

Executives need to be the ‘imagineers’ of their products and services, always pushing beyond the now, and envisioning the future from a customer’s perspective.

The ability to rethink products and services and reimagine customer experience successfully opens up a world of opportunities for businesses. However, neither of these paths to driving digitization can be successful without the crucial final step.

Join me in the next and final blog post of this series, as we discuss the most important part of the 3R approach to driving digitization – reengineering the value chain.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 2: rethink products and services

Social eminence June 11, 2021

In our first post, we discussed the hurdles enterprises encounter in their efforts to address changing customer expectations and evolving technological paradigms. We introduced the 3R approach to digitization and how its three dimensions - rethinking products and services, reimagining the customer experience, and reengineering the value chain - the essential components to enable effective enterprise digital transformation.

In this article, we’ll be discussing the first step of the 3R approach - rethinking products and services.

Rethinking Products and Services

The world today, unlike a couple of decades ago, has dramatically transformed with the proliferation of the internet. A shift in consumption patterns has been witnessed. This has affected both businesses and customers in a fundamental way. Smart devices such as cellll phones allow them to interact anywhere and at any time. Several other technology advances are driving fundamental changes in these interactions.

Rethink to Adapt, Innovate to Survive

Under such circumstances, it is imperative for companies to rethink their products and services — not just for the imperceptible future, but for a present that’s already prevails.

There are several instances where enterprises have struggled to transform. Laggards like Blockbuster and Borders Books failed to rethink their value proposition beyond traditional models and were driven to oblivion.

it is necessary for companies to rethink their products and services - not just for the intangible future, but for a present that’s already here.

Today, physical books and music are a waning commodity, and renting or buying has given way to newer models like subscription. This shift is a testament to the revolutionary impact of technology on business. Companies that were unable to adapt in a timely manner lost the battle of technological evolution to upstarts such as Netflix and Amazon. These modern day behemoths are working twice as hard not to repeat the mistakes of their predecessors. Each company spends millions of dollars annually in product innovation, research and development to ensure they keep pace with the new emerging trends.

Technology lies at the core of rethinking existing products, developing new ones, and facilitating services that can address market demands —even those that haven’t been realised yet. Case in point, the digitization of music on iPods by Apple. Rethinking products and services has the potential to create new markets and fresh opportunities. The challenge is not to simply adapt quickly but to proactively define the next wave of change.

Discovering the Business Case

Earlier, running on a treadmill at the gym meant having to frequently look at your wristwatch to measure your progress. Today’s treadmills are more sophisticated, can track the time, distance covered and offer estimates of the calories burnt and your prevailing heart rate.

But how will you measure these metrics when you’re off the treadmill?

With a technology-enabled wearable device such as Fitbit, you can easily access this information throughout the day. From heart rate to quality of sleep, and the number of steps climbed, it is all readily accessible on your wrist.

We can conclude that a business’ ability to predict customer needs and rethink product development from the perspective of customer experience is the key to future survival. Companies that can rethink an ideal business case for their existing or new products and services will continue to stay ahead of the competition.

Rethinking at Every Scale

This rethinking has to be enabled at each level. Small, incremental changes throughout the process workflow can yield significant productivity and efficiency gains for the business, while giving products and services an edge they didn’t possess before. Consider how IoT-enabled smart trackers on individual products and vehicles can transform various aspects of a business.

With access to real-time information, businesses can map and monitor the movement of goods across delivery routes. This helps them accurately estimate the exact delivery date and time for their products, and manage their inventory more efficiently while optimizing customer fulfilment operations.

Organizations can save on resources with accurate inventory and logistical management. These savings translate into significant contributions to the bottom line while increasing the speed to market (STM) and driving customer satisfaction.

Revenue-growth management (RGM) plays a critical role here. Companies are increasingly investing in Big Data, advanced analytics, and other RGM technologies to ensure they stay ahead of the curve. Exploring the use of such technologies throughout operations has to become an integral part of how companies expand their capabilities and rethink their products and services.

For large global enterprises, their vast size and scale of operations can be limiting factors to such initiatives. A simpler solution for them could be to acquire or merge with firms that offer existing capabilities that complement their core competencies. This has been a commonly observed trend among companies which focus on transformation. Examples include Disney’s merger with Pixar over a decade ago, and the AT&T and Time Warner merger that is currently underway.

The Next Step

Exceptional companies have woven this idea into their DNA. Apple is actively developing self-driving cars —an area beyond its traditional domain but powered by technology which is its core strength. Similarly, Amazon, along with JP Morgan Chase and Warren Buffett's Berkshire Hathaway, is planning to make inroads into healthcare— once again leveraging Amazon’s core expertise of technology.

The future of consumer-facing industries largely depends on how they innovate. Organizations need to keep track of minor changes in customer behavior because they often foretell major shifts in business.

The impetus to rethink products and services is driven by exploring methods of making products more efficient, engaging and ultimately, human-centric. The core of any business has always rested on how well they delight their customers. The only thing that has changed is the approach to realize this objective, owing to which rethinking products and services is essential to driving digitization in any company.

In the next part of this blog series, I will be focusing on how driving digitization calls on organizations to “Reimagine Customer Experiences”.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 4: reengineer the value chain

Social eminence June 11, 2021

In my first post, I explained how the 3R Approach offers an ideal framework for organizations to orient their digitization and innovation initiatives through Rethinking products and services, Reimagining customer experience and Re-engineering the value chain. We discussed in detail the first two steps in previous posts. Today’s post is on the third and final step of the 3R approach – reengineering the value chain.

Looking Inwards to Move Forward

Businesses that have stood the test of time are built on a foundation of complex systems that come together to create value. Most modern value chains are discrete and organized into silo-styled stages around divergent operations such as market research, product development, marketing, manufacturing, distribution, and ultimately customer service and engagement. While the traditional methodology of business has given rise to these siloes, digitization is well on its way to dismantle such barriers.

While the traditional methodology of business has given rise to these siloes, digitization is well on its way to dismantling such barriers

New systems that are built on the values of digitization demand end-to-end integration across the value chain. At the end of the day, the transformative power of ‘rethink’ and ‘reimagine’ is meaningless unless they align complex business functions through standardization and automation techniques.

Enterprises now have access to cutting-edge tools and technologies that can help them execute this approach effectively and have complete clarity of their own operations. Key technologies such as the Internet of Things (IoT), machine learning, artificial intelligence (AI), analytics, automation and robotics, have utility across business operations in proven ways. These tools can transform various enterprise technologies, such as autonomous logistics, integrated planning and execution, logistics visibility, procurement, and warehousing management, into more optimized solutions.

The integration of technologies across the value chain enables organizations to greatly enhance their decision-making power and potentially even predict change. By capturing data at every node and action junction in the value chain, leaders become more prepared to manage disruptions and utilize digital modeling to prepare for potential situations and implement scenario-based action plans in real time as conditions change.

The benefits of reengineering the value chain percolate down the managerial chain to all business operations and vastly reduce time-consuming and repetitive tasks. Automation systems which use intelligent operations help enterprises drive down cycle times and increase accuracy. This process allows enterprises to detect, predict, and prevent all the pain points they may not have known existed. Machine intelligence can effectively replace intuition, saving millions in guesswork and generating millions or even billions of dollars in efficiencies over the long term.

The benefits of re-engineering the value chain percolate down the managerial chain to all business operations and vastly reduce time-consuming and repetitive tasks.

In effect, the true digitization of a consumer business, or any business for that matter, rests on reengineering our value chains through process standardization, automation, visibility, analytics, and collaboration capabilities.

Discovering the Unknown

For logistics planning, the problem has always been to ensure the availability of the right quantity of supplies at the right place and at the right time – a subset of the overall business challenge we’ve discussed earlier. With machine learning-based modeling enabling an enterprise, the inbound logistical management can factor in a number of variables such as order placement, shipping, warehousing and utilization to predict and plan for future requirements.

A real-world example is when Walmart leveraged their Retail Link machine learning system to analyze information flowing throughout their supply chain. With it they were able to discover gaps and make seamless corrections in real time. Honda, on the other hand, deployed machine learning to discover patterns in their warranty return notes and mechanic reports to backtrack quality issues beyond the assembly line. Similarly, Caterpillar was able to save its fleet customers millions of dollars by using their machine-learning based Asset Intelligence platform, powered by IoT data, to identify an optimized power generation process for ships carrying refrigerated containers.

McKinsey Global Institute’s 2017 report states that machine learning has received the largest share of internal investment. This makes perfect sense given the potential payoff that it has proven to have for the bottom line. Major players like Google and Baidu strive to lead this movement from the front and are rapidly pushing the technology forward.

As an organization takes these technological tools and applies them toward its own operations, the results can be just as effective. Consider Amazon, which, in their attempt to create a fusion between the real and digital world, launched the Amazon Go store, which was first operated internally for employee beta testing. Amazon is constantly experimenting and testing diverse technologies like voice recognition, computer vision, machine learning, and AI to integrate the convenience of the digital with the real.

Imagine a customer walking into a store to buy a shirt. What if the store could have the desired shirt, currently unavailable, delivered to the customers within hours?

Furthermore, the customer can try out shirts to know how they fit, but augmented reality tools can give the customer a clear visual of how they would look in that shirt across an assortment of colors, helping them make their decision. And, by using real-time inventory tracing, the shop knows where the desired color shirt is and how quickly it can be delivered to the customer.

In the next wave of digital transformation, this shirt would be custom-made within hours for the customer if it wasn’t already in stock. In fact, this isn’t that far from reality. Amazon has already won the patent to create an automated on-demand factory that will, one day, do exactly that, and possibly change the way retail works in the digital space.

Reinvention or Obsolescence?

As companies move forward in the age of technological disruption, they have little choice but to reinvent themselves. The volatility of business models is growing and what works will become more unexpected and surprising with each passing day. The 3R approach to digitization helps provide a concrete way to address the issues on the journey to reinvention.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

The 3r framework: a business first, technology second approach to digitization part 1: introduction

Social eminence June 11, 2021

The customer’s no longer who she used to be, so why are you the same?

A large number of businesses have found themselves struggling to cope with customer expectations in the era of digitization. The primary issue has been their inability to reimagine their offerings and rethink their digital strategy in line with this new, hyper-connected breed of end users. Although business leaders often talk about how they need to change the way they serve the customer and emphasize their vision of placing the customer at the center of the value chain, it is easier said than done. The only thing we know for certain is that there is no denying or stalling digitization. The question that remains is: how do we really get there?

Survival of the most adaptable

We are at the crossroad of a technological epoch. An avalanche of technologies, like artificial intelligence machine learning computer vision and IoT have begun to converge and mutate to form hybrid solutions. The retail industry has led from the front in terms of disrupting business by adopting a digital strategy incorporating these technological mutations in its digitization journey. For example, Walmart’s low-key acquisition of Spatialand, a specialist in VR tech, is testimony to the seriousness with which the retail behemoth takes the importance of a nascent technology. Walmart understands as part of its digital strategy that keeping up with the customer experience revolution requires cutting-edge technologies. And adopting any means of defining this transformation is a victory for traditional businesses looking for a digital makeover.

Consider Amazon Go and how this digital strategy addresses the specific pain point of long checkout queues. While the tech behind the endeavor is almost magical, it’s incredible to see how the customer experience changes completely when a single step is skipped. In fact, a survey indicated that 70 percent of buyers prefer buying from a retailer who valued their time. Amazon gave these buyers exactly what they wanted.

And the ambivalence of the retail businesses wondering if they can wait out these trends could result in shortened shelf life. Warning examples include Circuit City, an erstwhile iconic electronic seller that went out of business thanks to an inability to respond to digital disruptions and launch a digitization process.

The product gets a digital makeover

The retail business is just one part of the tech invasion. The products themselves are changing as part of the digitization process. Take the wristwatch industry for instance. Since its inception, it has barely seen one or two major disruptions that were centuries apart. Today, with wearables becoming part of the technological singularity obsession, the once-ubiquitous wristwatch faces a struggle for its very existence. Tag Heuer, the Swiss watchmaker, realized this early and has collaborated with Intel and Google to come up with smart watches. In spite of Apple’s first mover advantage in the smart watch category, Tag Heuer is likely to have takers for the brand loyalty its customers have shown over the years and its brand personality that is upmarket and fashionable. With niche players like Frederique Constant joining the race, wearable tech, already mainstream, may soon find itself the subject of fashion reviews.

The service transforms

Customer expectations from the service sector also transformed as we moved into the ‘anytime, anywhere’ ecosystem. With zero tolerance for delays and steadily diminishing attention spans, the modern, hyper-connected customer expects experiences that are seamless across channels, instant, and intuitive. And while the internet and its spin-off technologies abet and enable these behavioral patterns, sectors such as telecom find themselves scrambling to adjust their pricing and operational models to this change.

And as yesteryear giants like Kodak, HMV, and Blockbuster make way for digital prodigies like Netflix, Amazon, and Uber, Jack Welch’s words ring truer than ever: “If the rate of change on the outside exceeds the rate of change on the inside, the end is near." For the service industry, this digitalization of business brings with it worries on data security, privacy, and the need for hardware upgrades that create some serious cost pressures.

A bumpy ride for the large fish

With information at their fingertips, the modern customer is better informed than any customer has ever been in the past. And these digital natives demand not only the right product at the right time, marketed the right way, but for organizations to evolve and readjust the pace at which they change their minds and preferences.

For larger organizations, however, keeping up with this dynamic business environment can be challenging and sometimes impact the very foundations on which they were built. To adopt digital strategies that cater to a new generation of customers, established organizations need to confront internal and legacy hurdles that are a mix of human factors and technology. They may not always have a clear, holistic vision on their digital and GTM strategies for their offerings.

To adopt digital strategies that cater to a new generation of customers, established organizations need to confront internal and legacy hurdles that are a mix of human factors and technology

Despite having the right technologies to help capture the massive amounts of data generated by customers, a number of global corporations find themselves wanting when it comes to drawing meaningful insights from this data. This clear gap in gathering vs. leveraging data is almost synonymous with legacy technology stacks and outdated processes that continue to haunt large modern enterprises today. Unfortunately though, these organization have traditionally suffered from a higher churn rate of CIOs and CTOs thanks to the lack of buy-ins from internal stakeholders and IT product failures.

Rethink, reimagine, reengineer

A lot has changed over the last decade but the fundamental challenges and aspirations of businesses aren’t all that different from the past. While digitization gives us access to newer and more effective tools, its deployment is far from being a perfect science or having a proven approach. What’s clear is that while technologies like IoT, AR/VR and AI are redefining the bedrocks of operations, marketing, and computing, the business of the future is expected to either imbibe these into their business models or run the risk of losing relevance in the present technology landscape.

The 3R Approach is a means of driving digitization in a way that addresses every growth dimension for modern enterprises. Each of its three aspects – rethinking products and services, reimagining customer experience, and reengineering the value chain will be elaborated individually in this four-part blog series. Watch out for the next post, where we’ll dive straight into rethinking products and services as a means to digitization.


amitava.sengupta's picture Amitava Sengupta April 03
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Executive Vice President - Digital Consulting, Digital and Analytics

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