How Big Data will Revolutionize Energy Use and Customer Relationships
The roll out and implementation of “smart meters” among residential and small business customers by US utilities has been gathering momentum over the past five years, and this development promises to revolutionize the data available to the energy industry. Replacing the time-honored legacy of monthly door-to-door meter reading, the capability of smart meters to measure short interval (and potentially real time) energy consumption is fundamentally transforming the ways in which utilities can interact with their customers. These very rich data can provide entirely new perspectives and avenues for customer research and data analytics.
While initial large-scale roll outs of smart meters began in Europe over a decade ago, in North America deployment has also proceeded apace. Generally, the preference here has been for leveraging wireless technology and capitalizing on the flexibility that mobile, application-enabling digitalization allows. Among other capabilities, many of these meters support text messages, pricing signals and load control to residential users. A number of deployment initiatives also encompass the ability to fully share micro-usage information with residential customers via secure websites. In tandem, many utilities are looking into ways that, empowered by smart meter information, customers who become more energy efficient can be rewarded by participating in pricing programs that vary rates according to season and/or time-of-day.
Powerful Analytics, Customized Offerings
Within the next decade, smart meter interval usage measurement will become a standard across nearly all utilities. And the digitalization of short interval energy use and management information at the level of the individual consumer is quickly emerging as a source of deep and expansive data. At the very least, patterns of hourly, or quarter-hourly, usage can provide a much more detailed picture of consumption behavior than has thus far been available, allowing utilities to structure rate offerings, energy efficiency programs and other services that both meet individualized needs and support utilities’ infrastructure planning.
More broadly, the ability to merge and otherwise integrate smart meter data with other sources of customer measurement is beginning to gain traction within the context of data warehousing and other “Big Data” initiatives. When coupled with other sources of data, such as customer surveys (attitudinal measures, consumer choice behavior, energy efficiency and environmental orientations) as well as transactional and program participation data, utilities will have the ability to analyze not only what consumers are doing and how they are using energy, but perhaps more importantly, why they behave as they do.
Specifically, information gained from smart meters can begin to provide the missing link between self-reports of attitudes, perceptions and psychological predispositions in survey data to their actual, smart-metered behavior. Such data can augment survey analyses, identifying and quantifying key predictors of research goals not measured in the survey. Insights and patterns of statistical relationships between the two sets of data can then be robustly projected back to the client’s database as a whole. In short, smart meter data can go beyond just capturing customer behavior in very detailed and expansive ways, and become a key pillar to support ongoing market research activities by providing valuable insights for focused research projects.
What Lies Ahead
Of course, besides holding the promise of revolutionizing research into energy use and customer relationships, at this stage there are also some inherent challenges to smart meter data and its availability and use within the market research community:
- In regard to smart meter data itself, since it measures usage in very small time increments, there is the issue of data size and complexity (clearly, it’s a variant of Big Data).
- Questions of data transformation (from raw data to useful levels of aggregation), processing power and capacity, and smart meter data integration with other data sources of varying quality and location will have to be addressed and resolved. Here, there has been significant movement in the energy industry toward rationalizing and integrating disparate data flows in terms of collection, processing, storage and analysis (e.g., the creation of data marts).
- Finally, especially since utilities tend to operate in highly regulated market environments, protocols dealing with smart meter data security and customer privacy assurance will have to be negotiated and put in place.
No doubt these issues will take center stage in the coming years, but evolution can be swift when a revolution is in sight.
Contact Ron Newheiser for more information.