Analytics hurdles: money + staff expertise
What's the next step, now that interval meters are reaching a third of all homes in the United States, soon to be half of all homes?
From a new report, Annual Customer Analytics Report, 2012 [Editor's note: Link is no longer available] it would appear that using data to shore up the meter-to-cash cycle, understandably, is the first task to be addressed. Next comes the marketing of energy efficiency programs to the right customers, presumably to stave off large capital investments. Yet the spending forecasts for customer-related analytics reflect great interest in parsing customer data for even greater value.
You can get the gist of the report from the report's executive summary by clicking on the title, above.
(Disclosure: The report is by the Utility Analytics Institute, a sister organization to Intelligent Utility; both operations are owned and run by Energy Central.)
From our recent piece on Hydro One's data analytics program, it's obvious that the step-by-step process of turning data into meaningful insights takes time. (See "Hydro One: Data Analytics Requires Lead Time, Legwork.") And it costs money. And requires skills sets that may go beyond existing staff.
But let's turn to the report itself for some insights. Some 120 utilities participated in an online survey —and more than a score sat for in-depth interviews—to provide the following results. With interval meters being widely deployed, it's hardly surprising that nearly three-quarters of respondents have customer analytics efforts underway. More than 40 percent of those efforts focus on meter-based analytics. (See "Meter Data, Applied," for two case studies.) The second-busiest endeavor is marketing the right energy efficiency programs to the right customers.
The other take-away, in my view, is that utilities are finding it a challenge to attract the needed analytics practitioners—folks who can guide the design and implementation of analytics. Indeed, we predicted this in "Big Data = Big Challenge: Utilities Compete for Analytics Talent," just based the number of other vertical industries vying for these folks. For in-house end-users, training will be needed in how to ask pertinent business questions of the data and produce the fewest number of reports with the widest relevance.
Two comments by utility respondents illustrate the challenges in hiring new analytics practitioners and bringing current utility staff up-to-speed.
"To work with customer analytics, an analyst or statistician needs to know the purpose," wrote one respondent. "The business person knows the purpose but only knows the old business process. To find open-minded people who can put this together is a challenge."
"I'm looking to add an analyst," wrote another, "and even writing the job description has been challenging. There is a need for someone with technical skills, but also with the creativity to think outside the box, to appreciate the art in customer analytics."
One fundamental underlying these challenges is money. Fully 29 percent of utility respondents in this study cited budget availability as a major challenge. Lack of staff and necessary skills was cited by 22 percent. Data availability was cited by 17 percent. Interestingly, and no doubt promising for the future, is that IT and business support don't appear to be hurdles. Instead, two perennial resources—sufficient money and staff—appear to be the main obstacles.
That's the snapshot, today. The opportunity to apply analytics to customers to not only improve meter-to-cash processes but for customer segmentation and selling new programs, must be getting through to chief financial officers. Fully 84 percent of utility respondents said their customer analytics spending will rise for one to two years, while 69 percent expect spending increases over the three to five years ahead.