Oracle’s second annual study of how North American electrical utilities are leveraging smart grid data reports that there has been great progress across the industry since last year.
“Utilities are accessing valuable data from a variety of sources in addition to smart meters,” the study’s executive summary concludes, citing “outage management systems, supervisory control and data acquisition (SCADA) history and customer data and feedback.”
But while more than twice as many utilities said they were completely prepared to handle smart grid data than did last year, the majority still are unprepared, according to the Oracle study, “Utilities and Big Data: Accelerating the Drive to Value.” Oracle released the report July 23.
Less than half of the 151 utilities executives surveyed in April and May said their companies are using smart grid data to improve customer service. Further, the Oracle report says, “Big opportunities also remain in operational analytics to improve asset performance, reduce operations costs, and improve network reliability.”
And one of the major reasons utilities are not fully leveraging the vast amounts of smart grid data they’re collecting is the shortage of analytics professionals currently available to help make sense of data generated by smart grids, other utilities equipment and customers.
Sixty-two percent of respondents said their utility has a skills gap around smart grid data analytics or data science, while only 31 percent claimed to have the necessary analytics skills. The respondents echoed concerns cited by industry executives at a March conference, who discussed the challenges of hiring talented programmers or developing that talent in-house to take advantage of use cases in both operations and marketing.
While it might be logical to assume that utilities further along the smart grid curve have addressed their analytics skills needs, the report concludes that “utilities in all phases of smart meter rollouts are equally likely to have a data analytics skills gap.”
“It’s a big issue now,” says Guerry Waters, Oracle Utilities vice president of industry strategy. “’Do we have the skill set to even do an analysis of this data?’ And the survey shows that most utilities don’t believe it.”
In particular, Waters tells Data Informed, utilities report feeling most deficient “in the area of predictive analytics.”
“Most of the things they’re doing around analytics today are the traditional types of things they’ve been doing all along, like looking at outage information, looking at asset management information, pretty much siloing the information that’s generated from different operational areas,” says Waters. “But the real value is from taking an enterprise point of view, looking at the data holistically. And then being able to make decisions, have better asset management, and look at how we can prevent failures of equipment by knowing when a piece of equipment is overloaded or operating above a specification.”
To overcome the analytics skills shortage, 90 percent of the responding executives who say their utilities have a skills gap report that they are training employees in data analytics, while 60 percent are hiring from the outside. Another 45 percent are using pre-packaged analytics platforms, while 30 percent are outsourcing to a third party.
One of the reasons utilities lean toward training current employees is that analytics professionals are in great demand, Water says, “not just by other utilities, but by companies across a number of industries.”
Even if a utility decides to build analytics expertise in-house, Waters says, it still will face asset retention challenges due to the analytics skills shortage.
“They can train them internally,” he says. “But how are they going to keep them? They’ve got a big issue here.”