Utility 2.0 - How AI can transform everything from utilities’ customer engagement to their operationsPosted to Bidgely
- Oct 29, 2019 10:15 pm GMTOct 29, 2019 9:49 pm GMT
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It’s a funny punchline because it’s true: The goal of most utility executives is to lead the second-most innovative company in the industry.
To be fair, we should all be happy that utilities are more risk-averse than most companies in other industries. When your fundamental mission is to literally keep the lights on and provide the power modern society needs to function, dabbling with untested technologies and business models can have profoundly bad outcomes.
But anyone who has watched a football or basketball game recently knows that artificial intelligence (AI) has long since crossed the chasm from promising idea to foundational business tool. Indeed, all those ads about how AI is transforming industries from logistics to healthcare to professional sports reflects the critical role companies see AI playing in driving efficiency, competitiveness and customer value.
Despite its ubiquity and hype, not everyone understands what AI actually means. At the biggest-picture level, AI is simply the capacity of machines and computers to mimic human behavior. Underneath that big umbrella definition, though, are machine learning technologies and sophisticated algorithms that help machines and computers work smarter and more effectively than us mere mortals.
It’s why AI’s ability to identify trends and anomalies in huge data sets is such a potentially powerful tool for detecting diseases. What’s even more exciting is that AI thrives on data: As the volume of data gets larger, AI’s ability to translate that mountain of information into meaningful insights gets better.
The simple fact that utilities are now evaluating and testing AI to help transform their operations, customer relationships and business models is a testament to how mainstream it has become.
For example, led by the Electric Power Research Institute (EPRI), the industry’s premier research organization, a broad swath of utilities has been investigating the use of drones and AI to improve the inspection of transmission and distribution assets. The underlying rationale is simple: Unmanned drones equipped with cameras can collect massive troves of images of conductors, transformers and other equipment that can then be analyzed quickly and thoroughly by AI. There is already a broad agreement in the industry that this approach has the potential to identify equipment at risk of failure in a manner that is much faster and safer than a current method that relies on manual inspections.
While transmission and distribution infrastructure inspections may be the most well-known application of AI in the utility industry, it’s hardly the only one. AI has the potential to manage the already- large and accelerating influx of distributed energy resources like solar and battery storage, which has triggered a substantial increase in the bi-directional flow of energy and the creation of a whole new class of so-called prosumers – residents and businesses that generate electricity themselves.
“Why not just do business-as-usual? I think utilities are starting to understand that, like a lot of other industries, if they do that their business could be affected in a significant way,” said Abhay Gupta, co-founder and chief executive officer at Bidgely, a software company that works with utilities around the world to harness the power of AI. “North America is currently, for the most part, a regulated environment. But there’s no guarantee that’s not going to change in the future. There are companies out there, particularly in the tech world, that would salivate at having the captive audience or the revenue stream that utilities have from consumers.”
Adding to those competitive pressures is the increasing expectation all consumers have around hyper-personalization, thanks mainly to their day-to-day experience with companies like Netflix, Amazon and Google. Fortunately, utility customers are largely receptive to improved engagement and support from utilities. Indeed, a 2017 Deloitte survey of residential utility customers found that a large majority of people ranked their utilities as the preferred provider of distributed energy resources, like solar. Importantly, the Deloitte survey also revealed an openness among residential customers to additional services from their utilities, including improved monitoring and management of their energy usage. It’s why Deloitte recommends utilities work to not only become more customer-centric, but also consider partnering with companies outside the industry to develop and deliver new data analytics products and services.
Thanks to AI, utilities are enviably positioned to take advantage of customer interest in deeper engagement. In fact, utilities already have what AI needs to thrive. “They have a mountain of customer data. For machine learning to operate or to be successful, it has to have a cache of data to learn against,” said Gupta. “This is an unnatural advantage that they have that they are currently not really exploiting or leveraging.”
But that lack of usage won’t last. Perhaps the most obvious area where utilities can marry their vast collections of data with AI is to improve customer engagement. It’s about taking a Netflix kind of approach to personalization to forge a mutually beneficial relationship with utility customers. And to deliver the equivalent of what Netflix does with personalized movie title and trailer suggestions in the utility world requires genuinely understanding how consumers use energy on the individual appliance level. This scenario is possible only through the energy disaggregation that can be achieved by applying machine learning algorithms to monthly and smart meter data reads.
The difference between an understanding of appliance by appliance energy use in a household and educated guesses about typical household energy usage that are based on neighboring homes is significant. And that difference is even more glaring when the information is used to determine not only which customers utilities seek to enroll in demand-side management programs but also the sorts of messages that are crafted to communicate with them.
“Utilities are still sending offers to upgrade a pool pump to people who don’t own pools,” said Gupta. “If you want to build a relationship with a customer and the customer’s current reference point is a highly personalized interaction, it’s a huge lost opportunity that can be remedied using AI on customer data.”
There’s plenty of reason to believe that an increased focus on customer engagement is good for business. A 2018 report by audit firm KPMG LLP argued that companies delivering the most personalized experiences to their customers ultimately reap higher revenue growth and increased brand standing and loyalty. KPMG’s top-ten ranking of companies providing the most personalized customer experience was led by Navy Federal Credit Union and included three grocery store chains. No utilities made the top ten.
But the consulting firm EY envisions a host of ways that AI can elevate the personalized experiences utility customers receive. The automation that AI delivers to customer service can let a utility know when they need to deliver more personal attention to a customer. “We could use AI to identify patterns of behavior that indicate customer dissatisfaction - perhaps tone of voice or choice of words or questions about energy usage or tariffs - enabling intervention and remediation to reduce frustration,” wrote Thierry Mortier, EY Global Innovation Lead for Power & Utilities, in a blog post.
The use cases for AI in the utility industry extend well beyond improved customer engagement and include improved regulatory compliance, better transmission and distribution planning, and new electrification opportunities that can bolster revenues.
In other words, AI can be a fuel that leads to a new kind of utility.
“A lot of utilities are looking to transition from selling kilowatt-hours to selling products and services,” said Gupta. “In as much as a utility can get more visibility about their consumer’s lifestyle and the profile of their usage and what’s important to them and motivates them, the more they can ensure that what they offer is valuable and useful to them.”