Converging Energy Landscape: What Business Model will Capture Customers?

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2 Converging Energy Landscape: What Business Model will Capture Customers? Rutgers University Utility of the Future Energy Innovation Workshop September 16, 2016 Kristie Deiuliis VP, Energy Markets DNV GL Ungraded 1 DNV GL 2016 SAFER, SMARTER, GREENER

3 U.S. Retail Energy Markets Context 20% of all US TWh are competitively served 75%-95% of industrial load served by third party suppliers >3,000 licensed competitive entities in U.S. highly crowded Choice markets do not own generation required to sell as part of restructuring All restructured power markets (except Texas) require utilities to procure default service power 2 DNV GL 2016

4 Retail Market Evolution Market Convergence Business Strategy Evolution Competitive Retail 1.0 Competitive Retail 2.0 Competitive Retail 3.0 ( ) ( ) ( ) The Maverick The Salesman The Strategist Competitive Retail 4.0 (2016 Forward) The Architect Utility affiliate dominance Low residential engagement Basic market design, rules set High customer education spend Commodity pricing focus Rise of nonaffiliate players, models Generation caps expired, led to switching spikes More pricing & deal structures Savings, value from choice Big 5 retailer strategy overhauls; affiliate sales Highly crowded, competitive landscape Margin compression Defaults, M&A, Partnerships Fragmented pricing & contracting Non-commodity solution integration Non-traditional energy player entrance Financing, credit challenges Increased data access & leverage Business model evolution 3 DNV GL 2016

5 Sea Change: Residential Consumers, Solution Providers Creating Meaningful Customer Value is Tough Thousands of solution providers Hundreds of similar and different options What are there priorities and why? How might their priorities change and why? How will they adopt innovation? How do they interpret options to make (or not make) decisions? Uncertainties (& Risks) Abound Regulatory and legislative enablers and barriers evolving and uncertain Customer priorities & needs Technologies applications, value, combinations Business strategies how bold or incremental? Vision and priorities short term vs. long term? 4 DNV GL 2016

6 DNV GL 2016 Market Pulse Survey #1 Business Strategy Evaluation Factor #1 factor you consider as you evaluate whether to maintain, modify, or change your current business strategies? Source: DNV GL. Respondents include regulators, wholesale operators, generators, utilities, competitive retail suppliers, DER providers, manufacturers, developers 5 DNV GL 2016

7 DNV GL 2016 Market Pulse Survey What is the most important value you provide to your customers? 49% Energy cost savings 36% 8% 8% Convenience, ease of doing business Increased reliability of electricity service 8% Management of energy market price risk 6 DNV GL 2016 Source: DNV GL. Respondents include regulators, wholesale operators, generators, utilities, competitive retail suppliers, DER providers, manufacturers, developers

8 DNV GL 2016 Market Pulse Survey The Customer Experience What word best characterizes your view of your customers experience in the evolving energy markets? 36% Source: DNV GL. Respondents include regulators, wholesale operators, generators, utilities, competitive retail suppliers, DER providers, manufacturers, developers 7 DNV GL 2016

9 DNV GL 2016 Market Pulse Survey Understanding Your Next Customer How do you get insights about what customers want? How well do you incorporate what you learn into your business strategies? 23% Extremely well 36% 38% 34% Somewhat well Mixed 2% Somewhat poorly 3% Not at all well 8 DNV GL 2016 Source: DNV GL. Respondents include regulators, wholesale operators, generators, utilities, competitive retail suppliers, DER providers, manufacturers, developers

10 What is Convergence? Convergence is a rapid collision of PLAYERS, SOLUTIONS, and FINANCING Industry sea change Signposts include M&A, investment and debt challenges, partnerships, products/services proliferation Requires a reimagined business strategy to navigate ALL sectors and players affected winners and losers emerging Downstream (customer) value and engagement critical fulcrum for business strategy evolution 9 DNV GL 2016

11 Market Convergence Drives the Need to Reimagine the Energy Future Regulators, Legislators Financiers Power Generators Technology Vendors 10 DNV GL 2016

12 Thank You! Kristie Deiuliis VP, Energy Markets Mobile: SAFER, SMARTER, GREENER 11 DNV GL 2016

13 What Do Consumers in the Future Energy Ecosystem Need? 2016 Utility of the Future and Energy Innovation Workshop September 15, 2016 Ed Brolin Director & Assistant General Manager, East

14 Can Today s Question Be Answered? The question posed: What do Consumers in the Future Energy Ecosystem Need and How do We Win Them? There is no single answer to the question as posed The reasons for this are varied and include: o o o Uncertainty around future innovation Consumers desire and ability to understand the energy industry Our industry s ability to properly engage mass markets consumers The path to winning consumers in the future energy ecosystem can be found through the combining the question asked with that of What do they want? 2

15 The Current Ecosystem: Overview Mass Markets Choice has undergone substantial change over the past decade, with steady (if slow) growth in consumer awareness and the implementation of enabling technologies (e.g., AMI, smart stats, DER, etc.) While market maturity varies from state to state, in general there is a belief that markets will evolve similarly over time along these lines: Stage 1: Compete on Price Stage 2: Compete on Service Stage 3: Compete through Innovation Likewise, many stakeholders believe that we are in the early stages of an evolution in the types of Products and Services that consumers will want: Inform Me Empower Me Do It For Me 3

16 The Current Ecosystem: Products Source: DEFG 2015 ABACCUS Report 4

17 itunes Decline & Apple Music s Growth 5

18 Spotify s Role in itunes Decline 6

19 Talking to Consumers About Energy Today When talking to consumers, we could. 7

20 Talking to Consumers About Energy Today unless THIS is how we would like them to feel 8

21 Talking to Consumers About Energy Today Here s how smart companies are talking to mass markets customers 9

22 Why? Because THAT S the Answer to Today s Question It is true that small consumers are not experts in bulk power or commodity markets. They don t need to become experts they already have the tools necessary to make good retail market choices they do it all the time on many essential products and services. What they need is access to a translator and service provider: the Third Party Supplier or their local utility The TPS can manage all of the intricacies of commodity markets while expanding consumer choices and providing the attributes of electric service that small consumers really care about which is products and services. Source: DEFG 2015 ABACCUS Report 10

23 Products & Services: Not a Commodity Residential customers don t want a commodity The extent to which we talk about our industry in those terms is the extent to which we have failed to understand residential consumer preferences This is why we need to not ask what consumers need, but rather what they want Source: DEFG 2015 ABACCUS Report 11

24 Understanding Our Consumers: Psychological/Need Drivers Research has identified the following need categories: o o o o Lifestyle Need for more time, more money, less stress and more enjoyment Fairness Importance of ethics, equality and the environment Social Appropriateness Desire to do the right thing and do what others do Predictability Need to know where prices are heading, to budget, to be safe and reliability If an energy provider can make the customer perceive that they are receiving good lifestyle, fairness, predictability and social appropriateness, their attitude towards the company will be equally good o The customer does not individually perceive the hundreds of service dimensions that comprise that attitude, except for one or two salient points that represent each of the need categories Source: vaasaett 2012 World Energy Retail Market Switching Analysis & Rankings 12

25 Talking to Consumers About Energy Related Products & Services Tomorrow Things are about to get more confusing: 13

26 The Challenge & Opportunity Find ways in which service providers can create Energy Related Value-Added Products & Services from among the various potential industry value streams (DR, DER, EV, TVP, etc ) and distill them down into easy-to-understand offerings that resonate with consumers and that also help achieve vital public policy goals. Become an energy advisor to your customer someone who provides answers and solutions. Engender trust through satisfaction of customers psychological needs and drivers. 14

27 Enabling Proactive Customer Service Challenges, Opportunities, Technology and Value Prepared for: Utility of the Future and Energy Innovation Workshop September 16 th, 2016

28 TROVE Overview Predictive Data Science Software Company, Founded in 2011 TROVE Approach: Deploy software harvesting predictive insights from data science applied to the fusion of client data with TROVE data package Office Locations: Buffalo and San Francisco Strategic Investors: 2

29 TROVE Unboxing Component Description Cross-Industry Energy Utility Sunstone Platform Middleware for operationalizing data science models. Machine Scale Packaged with 3 rd Party Data Runs On-Prem or Hosted Generic Domain Model (Relational and Time series) Domain Model Projections for Utility Applications User Interfacing to particular Machine Learning and Distributional Model Libraries. Segmentation Application Dynamic Segmentation Customer Churn Customer Lifetime Value Demand Response (DR) Integrated Load Management (ILM) Asset Maintenance Scheduling Optimization APIs Integrate or extend TROVE with your own Model Libraries or Applications. Access and leverage rich Consumer Data packages Operationalize your own data science models. Store and access AMI, Grid Topology, Meter Events, Customer/Account, and other utility-specific data types. Access customer-specific loading measurements and behavioral labels 3

30 The Challenge of Finding Data Scientists Artist Mathematician + Statistician Domain Expert Data Scientist Computer Scientist 4

31 PROACTIVE CUSTOMER SERVICE (PCS) 5

32 Reactive vs. Proactive Reactive Proactive Describe Who are my e-bill customers now? Summarize Past Events Low-income customers complain when their bill is 50% higher on avg. Assume Where Value Lies Let s target high income families who own their home. Surface Mining These 3 Prizm codes are good targets for this new program. Infer What is the expected increased e-bill adoption rate resulting from this outreach program? Predict Future Events This specific customer is 90% likely to call in the next week. Dynamically Engage the Market Let s design offers tailored to our key target customer segments Deep Mining These are the uniquely behaving demographics for this new program. 6

33 Utility PCS Business Use Cases Micro-targeting new accounts for service plan enrollment Segment payment-challenged customers by usage, behaviors and demos, micro-target early interventions Identify high-value Pre- Pay adopters Predict impacts of customer interventions on individual customer satisfaction scores Personalized energy profiles Identify next wave of likely e-bill/auto-pay bundle adopters Propensity models tailored to discrete offerings Predict and target weathertriggered, high-bill complaint callers to avoid calls Tailor outage communications to target based on predicted behaviors 7

34 Data Quality Challenges 80% Of a Data Scientist s Job Raw Data Timeliness Freshness of consumer attributes. Interval data lag. Completeness Utilities don t have good visibility behind the meter. Blind spots in distribution network. Integrity Hundreds of tables and complex relationships. Tracking data lineage. See CIM. Validity (Values within expected Ranges) Name/Address challenges. Interval outliers. Consistency Ad hoc databases, spreadsheets. Historical data gaps. Analytical Ready Data Accuracy Expensive to measure real-world state. 8

35 Data Opportunities Demographic 800+ Attributes Premises 400+ Attributes News & Weather 60+ Attributes Mobile 20+ Attributes Financial 150+ Attributes Web / Social 250+ Attributes GIS 20+ Attributes Data Fusion Dynamic Segmentation Data Quality 9

36 Illustrative Example International Corporation Selling In-Home Devices and Subscription Services Challenge Reduce customer attrition and increase customer lifetime value. Customers became profitable 75% into their initial contract term on average 12% Annual Customer Churn Attrition spikes after initial contract Opportunity Proactive Customer Service Inbound Call Prioritization Loyalty Program Design Proactive Customer Engagement Personalized Outbound Retention Offers Technology Survival-based Predictive Churn Models Predictive CLV Modeling Dynamic Customer Segmentation Value 250% gain in churn predictions Strategy Alignment: 50% of Client assumptions shown to be insignificant Retention Costs << Acquisition Costs 10

37 Illustrative Example Putting Together the Pieces Data Computing Data Science 3 rd Party Data Client Service Portal Integration Developed on R Billing Data Customer Variables Product Variables Integration API Development API Data API Distributed Analytics (ML@Scale) In-Mem Caching System Activity Data Relational Data Columnar Storage (Timeseries Data) Hybrid Storage

38 Why Proactive Customer Service? Understand and anticipate individual customer needs, preferences, behaviors Improve customer experience, satisfaction Mitigate escalating cost-to-serve, improve process efficiencies Position utilities to Proactively engage customers in Smart Energy programs and services Harvest operational value from improved understanding of usage behavior 12