“For utility companies, transforming operations and systems with digital technologies can create substantial value: a reduction in operating expenses of up to 25 percent, which can translate into lower revenue requirements or higher profits. Performance gains of 20 to 40 percent in such areas as safety, reliability, customer satisfaction, and regulatory compliance are also achievable. “—McKinsey Report, “Accelerating digital transformations: A playbook for utilities.”
“Digital Transformation” has been a trendy topic in enterprise technology circles for years, with the buzz extending to just about every industry imaginable. Broadly defined, this concept refers to what CIO magazine calls “ a rethinking of how an organization uses technology, people, and processes in pursuit of new business models and new revenue streams, driven by changes in customer expectations around products and services.”
While this definition is helpful for conceptualizing digital transformation at a high level, it doesn’t tell us much about what digital transformation for electric utilities will specifically look like.
In this blog, we provide a more specific illustration of why digital transformation can be so valuable for utilities. Rather than using technology only to eke out marginal efficiency improvements, a successful digital transformation results in a more agile, data-driven utility. These capabilities are essential for preparing for dynamic, generational challenges, like the need to provide reliable electric service in the face of more frequent and extreme weather events.
For electric utilities, digital transformation is first and foremost being driven by the customer.
In the not too distant past, many utilities saw their customer base as a pool of “rate payers,” depersonalized revenue generating units. But utilities today have increasingly come to the realization that they have customers, no different than other businesses such as Amazon or Verizon. Utilities are under more regulatory pressure than ever to improve reliability metrics for these customers (see our guide to reliability metrics here).
Utilities are also facing greater competitive pressure to improve the customer experience wherever possible. While the “ratepayer” keeps sending in a check no matter what, the energy consumer of today will increasingly have choices in how they consume electricity (and where they obtain it). This fundamental shift in the customer / vendor dynamic has only begun to unfold. Looking forward, we only expect it to exert growing pressure on utilities to re-think their business models, create additional offerings, and streamline the customer journey wherever possible. And the right technology strategy plays an essential role.
As a result of growing pressure to improve the customer experience, utilities are taking a hard look at their own internal IT systems and processes. These systems are essential for improving customer satisfaction while generating as much value as possible from operational data.
For utilities, a successful digital transformation must focus on breaking down barriers between internal data silos. Unifying organizational data is a foundational step for transforming the raw data collected by various systems, devices, sensors, and business units into actionable business intelligence that can be leveraged to make better decisions across all parts of the organization.
The need to provide timely, accurate ETR (Estimated Time to Restoration) estimates to customers is a powerful example of why these data-driven decision-making capabilities are important to crafting a better customer experience.
Timely, accurate communication is the single biggest thing that a utility can do to improve customer satisfaction, and it becomes even more important in the wake of an outage event. These are the times when it is hardest to know precisely when a customer’s service will be restored—and also the times when it’s most important for them to have a timely, accurate answer. Their satisfaction (and even their safety) may depend on it.
Using more robust communication platforms backed by real-time data pipelines, utilities can push much more accurate status information to their customers as soon as it is received. In parallel, inbound communications can be collected from customers, such as reports on failed infrastructure and queries about restoration efforts.
Customers expect ETR times received to be highly accurate, not overly ambitious nor overly conservative. Inaccuracies in either direction can affect decisions made by the customer and drive frustration (no one wants to empty their refrigerator over a 1-hour outage). Because of the complexity and importance of this metric, it has become the de facto poster child of digital transformation efforts for the electric distribution system.
We provide a much more in depth look at ETR times in our blog here. Our advice is to take a hard look at the data flows feeding into the ETR calculation as the first step in the digitization journey. Doing so will go a long way toward ensuring high levels of customer satisfaction. In the context of a digital transformation, improved ETR communications are just one way that improved IT and data analytics can translate directly into valuable operational improvements. And in the nascent age of extreme weather, these capabilities will only become more critical.
While utilities navigate the shift to a more customer-centric service model, a parallel environmental change is occurring that will complicate the transition: the rise of more frequent and extreme weather events. These events include a broad range of phenomena, with recent examples including:
These events result in considerable property damage and often loss of life. They also risk having a dramatically detrimental effect on local utilities and their customer satisfaction rates.
During these events, when the power goes out, customers will often direct all of their built-up frustration directly at the utility. Customer defection is an increasing threat. After these calamitous events, we often see a spike in sales of solar panels, battery storage systems, and generators, as customers evaluate other options to ensure the lights stay on during the next inevitable extreme weather event.
For utilities, responding effectively requires drawing on a myriad of data elements which change in real-time, such as duration of the storm, number of customers affected, crew availability, parts availability, asset health status, etc. Successfully harnessing this data has the potential to fundamentally restructure how utilities interact with their customers.