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Rise of U Bots

Rise of U Bots
Rajdeep Basu - Solution Architect | March 29, 2017
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The utility industry has been slow in accepting change primarily because the industry has moved in linear fashion for decades. The advent of smart meters, stringent carbon emission targets and falling price of wholesale electricity have forced energy providers to look for disruptive technologies to offer differentiated offerings and services to customers and thereby stay competitive.

Utility providers have taken cues from Telecom and Retail industries which have historically shown a higher appetite for cognitive technology and robotic adoption – 35% and 19% respectively and have started to partner with tech firms to build rule-based ‘u-bots’ or ‘utility robots'. 

Process-related bots for contact centers help deliver self-service across the non-voice channels. Rule-based u-bots are the first-generation bots that can chat directly with customers and answer their standard or first-level queries. These bots are programmed with pre-defined rules and logic. However, they lack the ability to think and learn from customer interactions by themselves, although this is the preamble to cognitive technology and cognitive computing, especially in the utilities space.

The next step in the evolution of u bots is cognitive computing with an aim to create automated IT systems that can solve user issues without the need for human intervention. Cognition is the set of all mental abilities and processes related to knowledge, attention, memory, judgment, reasoning and computation. It also consists of decision making based on the comprehension of natural human language.

Nevertheless, ‘robofication’ of service delivery must be applied with some caution. In our experience of managing over 150 service desks of various Fortune 500/ Global 1000 accounts, we have carried out a SWOT analysis for the implementation of bots for utility providers:

Strength
  • Infinite number of chats
  • Lower staff size
  • Lower cost to serve
  • Lower effort or training downtime
  • Easy alignment with Analytics Engine
  • Reduced wait time
  • Improved customer experience
  • 24x7 capability
Weakness
  • Potential revenue impact in an FTE based delivery model
  • Dissent among staff as they might be realigned to different work requiring higher skillset
  • Potential attrition and brain-drain due to automation
  • Cost of development and incremental IT investments
Opportunity
  • Improved Customer Experience (CX)
  • Futuristic AI based solution
  • Higher profit margin and lower cost to serve
  • easy integration with Analytics engine to drive key customer insight
  • Ability to provide tailored solution to customer; this could provide the competitive edge to the company
  • Faster response time
  • Improve accuracy
Threat
  • Quality assurance – must be tested rigorously in a controlled environment first; Beta testing is time consuming and scenarios must be thoroughly tested before roll out
  • Integration with existing IT and enterprise applications the provider is currently using
  • Re-training and upskilling of agents to resolve higher complexity issues; change management and weighing of long-term automation benefits as against short-term revenue cannibalization  

Perspective for Utilities:

Robofication of customer contact via cognitive computing is a strategic move, and there are some important factors which must be adhered to optimize business outcomes:

Strategic AlignmentIncremental InvestmentRight Tech PartnerImprove CX
Identify objectives of robofication and ensure that they are aligned with the strategic goals of the business:
  • Cost savings
  • Business process automation
  • Customer experience solutions and enhancements
  • Increase self-serve
  • Reduce TAT of queries
  • Reduce open complaints etc.
  • Robofication – i.e. cognitive computing, machine learning, assisted automation, etc. require time and exhaustive beta testing
  • It is, therefore, prudent to invest in an incremental fashion and have a outcome based pricing strategy.
Utilities should select the right tech partner who has similar strategic objectives as theirs. Some evaluation criterions could be:
  • Domain knowledge and business expertise.
  • Previous automation case studies and POCs
  • Consulting and Due Diligence capabilities etc.
  • Automation is not a standalone solution and utilities should look at it as a platform to upskill both technology and agents.
  • The role of CSRs would change to consultative agents providing energy efficiency services and helping customers with complex issues.

Conclusion

The future for customer contact is evident and providing a differentiated service will be the key to winning over the millennial customers. U bots are going to bring a paradigm shift in delivering superior customer experience. It would impact everything from the delivery model, business processes, business KPIs (like focus on CES over NPS or CSAT), existing talent pool (i.e. tenured staff with domain knowledge), new talent acquisition (i.e. niche skills like managing complex technical issues, better troubleshooting skills, etc.) to the overall value proposition of customer engagements.

Evolution of cognitive computing and advancements in machine learning will enable u-bots to replace human agents in the utility service desk of the future. Therefore, u-bots would become the next battleground for providing superior CX. Hence, it is time for utilities to re-evaluate their business strategies to remain competitive in this unavoidable disruptive environment and integrate with cognitive computing companies for improved customer experience solutions.

HCL Technologies (HCL) a leading global IT services company that help global enterprises re–imagine and transform their businesses through Digital technology transformation is bringing out the first Cognitive Service Desk, LUCY in partnership with IBM.


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