Utilizing Meter Data for Better Demand Side Management
By Kate Rowland, Oracle Utilities
Long gone are the days of the one-way utility experience in which utility-customer moments were limited to bill payment and power outages. With nearly 62.4 million residential advanced metering infrastructure (AMI) installations in the United States alone by the end of 2016 (per the U.S. Energy Information Administration), the smart meter has heralded a massive change in the utility-customer relationship.
Over the past decade, the most successful AMI rollouts have put customers front and center. By translating smart meter data into helpful insights and programs, utilities have won regulatory approval, ramped up digital engagement, unlocked new value streams and dramatically increased customer satisfaction.
Better, more granular energy usage data from AMI has paved the way for more individualized customer program modeling and more personal demand side management (DSM) services, all designed to provide customers with better energy savings results. As a result, global spending on behavioral and analytical DSM is expected to increase roughly tenfold between 2015 and 2024, rising from $214.7 million to $2.5 billion, according to Navigant Research’s “Behavioral and Analytical Demand-Side Management” study.
Using Big Data to Enrich Customer Experience
In the past, the primary goal for most utility DSM programs was to help cost-effectively defer the need for the addition of new electricity generation to the system. As the industry changes and customer expectations of their utilities continue to rise, however, utilities have begun to use DSM programs to meet those expectations, provide value-added services and enrich the customer experience. This all begins with meter data.
When smart meters were first introduced, one of the touted future benefits was to be able to provide customers with a near real-time view of their energy usage and empower them to better manage their electricity budget. In the ensuing decade, meter data has proven to be one of the most effective tools utilities have for engaging and empowering customers in the long term.
Behavioral DSM focuses on customer education as the lever to encourage energy savings. By integrating AMI data with demographic data (age, gender, income, etc.), behavioral data and psychographic factors, utilities can create highly personalized experiences for customers, from proactive high bill alerts to insightful energy savings advice. It’s all about the content and the timing: delivering the right insights at the right moments to maximize their effectiveness.
While electricity usage data on its own is useful—even before smart meters, energy-savvy customers were comparing month-against-month usage from printed monthly bills—the real value of more granular AMI data is in the new insights that can be derived from analyzing it alongside other relevant data to make recommendations that are pertinent not to the customer base as a whole, but rather to each individual customer, mirroring their own experiences and preferences.
Data analytics provides a way to better categorize customers based on their energy habits, and then use that information to generate the insights and promote the programs that are most relevant to them. In essence, data analytics provides the ability to create a “segment of one,” treating each customer as an individual with specific needs and interests.
Educating to Engage
There are a number of tools utilities can use to deliver customer insights, from home energy reports and utility web portals providing usage information and energy efficiency tips to proactive high-bill alerts and even peak management alerts.
Just as data analytics is used across the utility enterprise to provide new insights and intelligence, it is also used to then embed intelligence within the enterprise to create new value. The same is true for the utility customer. Once customers are aware of the ways in which they can benefit from the data from their smart meters, the utility can begin to demonstrate those benefits in tangible ways by sharing energy efficiency insights using proactive alerts, including weekly energy updates via e-mail to help customers track their energy habits in a more granular fashion, and high bill alerts to help them curb their usage in a more immediate fashion, rather than after the bill hits.
Once a customer becomes interested and engaged in saving energy, he or she is more likely to want to engage with the utility online, whether it be to regularly track energy usage, pay a bill or look for new ideas and ways in which to save energy. For customers participating in time-of-use pricing programs, online engagement can be particularly appealing to track usage from day to day.
An engaged customer—one who now looks at his utility as a trusted energy advisor—is also more likely to participate in peak management programs, whether those be behavioral demand response-related or rebate-related. In addition, most importantly, a more engaged customer—one with the ability to better manage his or her relationship with the utility, and use of that utility’s products—is a more satisfied customer.
Kate Rowland is a writer and industry strategist for Oracle Utilities. She has more than two decades’ experience in the energy and utilities industry.