Digital Execution Roadmap: Digital and Analytics Social Eminence 2.0

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

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?

The AI frontier: driving reliable and stable IT operations

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 HCLTech’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 HCLTech, 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.

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

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 HCLTech, 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.

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

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.

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

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.

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

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.

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

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.

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

Reinventing for the digital age via the fenix 2.0 framework

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.

HCLTech 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:

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.

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.

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, HCLTech’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. HCLTech 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.

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

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.

Human-centered design: a people-first innovation mindset

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, HCLTech’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: HCLTech’s Innovation Credibility

With HCLTech’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 HCLTech 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.

HCLTech 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, HCLTech created a roadmap to create a one-billion fan base and media reach. HCLTech also deployed a single digital platform to connect various channels like merchandising, ticket booking, player stats, social media, etc.

HCLTech 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, HCLTech 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 HCLTech is doing it better than its competitors. A New York-based environmental group stated that HCLTech’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. HCLTech 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.

Reimagining the enterprise culture for digital adoption

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 HCLTech-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 HCLTech-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 HCLTech 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 HCLTech, 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 HCLTech, 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.

Human intervention critical to futuristic and sustainable digital transformation

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 HCLTech, our digital transformation capabilities are in line with this principle.

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

Infusing cultural intelligence in analytics to drive customer centricity

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 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, 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:

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 21^st 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?

How to successfully scale agile and devops - part 1

June 11, 2021

I began my journey into scaled digital and DevOps 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 HCLTech. 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 digital journey. 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 agile and DevOps 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!

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

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 HCLTech 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 HCLTech 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. HCLTech 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.

HCLTech 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 HCLTech’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.

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

HCLTech’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, HCLTech’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.

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

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.

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

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”.

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

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.

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

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.

4 things Cios must consider on their digital journey

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.

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

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!

Towards a responsible, digital future

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 HCLTech’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!