Utilities navigate analtyics pain points
Using analytics encompasses all aspects of utility operations -- from the end customer to business decision makers. But the energy industry as a whole is just feeling its way through using analytics, and a number of challenges remain surrounding managing the rapid influx of data and its possibilities.
At a recent conference hosted by the Utility Analytics Institute, utility staffers from across the U.S. gathered to discuss how they are tackling some of the biggest pain points on the road to successful integration of analytics. These difficulties include: Determining what data to use and what data to ignore; how to filter data; how frequently to pull analytics reports; and how to get value and build a business case from the available data.
Determining data needs
One key is making sure that data is transparent and accessible to those who need it, said Chad Crossley, Manager of Business Intelligence and Architecture at the Orlando Utilities Commission.
"Our thoughts are that we want to make this information pervasive throughout the organization," he said. "We view every employee as a potential knowledge worker, so we want to continue that trend and provide them with the information they need to do their jobs."
There is an acute difference between making the correct, targeted data available and simply dumping a pile of numbers on utility staffers with the hope of sifting out value.
But there is an acute difference between making the correct, targeted data available and simply dumping a pile of numbers on utility staffers with the hope of sifting out value. For example, although smart meter data may be available as often as every 15 minutes, it's often not useful to look at numbers at such a granular level.
"We had to tell management that you can't look at everything," said Marti Harvey, an MDMS project lead with the Colorado Springs Utility, which is using DataRaker analytics software to refine meter data reports into "buckets" based on priority.
A targeted approach to customers
One glowing benefit of analytics is the ability to learn about customer use patterns, including pinning down which customer groups and buildings are using the most -- or the least -- amount of energy. But for the City of Fort Collins Utility (FCU), the method is a stark contrast to the typical way of doing business.
Historically at the utility, messaging and interactions with customers have been uniform, said John Phelan, Energy Services Manager at FCU.
"We have a culture of being democratic with our outreach. We are a municipal utility and we want to treat everybody the same," he said.
It took a persistent approach to convince the marketing team that segmenting customer data (and customer messaging) would help the utility reach its conservation goals by streamlining the messaging process and cutting back on sending out excess materials.
"That was an anathema to them," he said.
Justifying the transition
Above all, the toughest part of implementing grid analytics is crystallizing the business case for the required infrastructure investments. But, aided by government grants and an improved understanding of the value analytics bring in terms of understanding customer usage and the ability to automate data collection and grid operations, more and more utilities are finding ways to justify their investments.
Even with recognized "pain points," stakeholders are working together to overcome growing pains and bring a new age of analytics into the fore. In doing so, the industry is getting one step closer to a grid that can work together to improve energy efficiency, optimization and the reliable delivery of power.