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How electric utilities view analytics

Last week, I wrote about public misconceptions concerning usage data collected by their electric utilities.

This week, I'd like to tackle brass tacks: the straight goods on why it's important for electric utilities to collect data all along the grid (not just at usage endpoints), and the ways in which they want to use it.

To do that, I'd like to look back at a study published by SAS last fall, "How Utilities View Analytics." The survey that formed the basis of the study was executed by Energy Central, with the online survey instrument developed by SAS Market Research. More than 300 respondents were surveyed, including 218 North American utilities, and 56 percent of those surveyed were large investor-owned utilities.

As most in the industry are aware, data and information have typically been collected and held in utility silos -- IT, operations or customer service - and rarely shared beyond those silos. It has been acknowledged that this needs to change, but how far have those changes actually gotten?

One of the questions the SAS survey asked was, "Is your organization breaking down silos and mandating new data sharing processes in order to leverage information to your advantage and drive better decisions?"

Somewhat surprisingly, only 18 percent of respondents indicated they do it now, and that it is well underway. Another 44 percent said, "Yes, we recognize, but we've just begun to act," and a full 32 percent said they, too, recognize the potential, but have too many barriers to change.

While it's disappointing that internal barriers continue to exist in that many of the surveyed utilities, it's understandable. Typically, change does not come quickly within this industry. However, there's a silver lining in the statistics, as well, according to Alyssa Farrell, SAS worldwide alliance and product marketing, energy and sustainability.

"The promise of better-informed business operations is precisely why the majority - three-fourths -- of all respondents said they recognize the potential in breaking down information silos, managing new data and sharing information across the organization, but they've just begun to act on this promise and struggle with several barriers," she said.

Another interesting note within those particular survey results: executives (as opposed to managers or analysts) accounted for 40 percent of the respondents who indicated that they recognize the value of information sharing, but that there are too many internal barriers to change. However, 50 percent of analysts surveyed said they are beginning to share data across silos, indicating a tremendous leadership effort among this group, the report noted. Further: "Given these findings, analysts seem positive about progress toward breaking down silos, providing hope that a bottom-up approach may the inevitable solution instead of a traditional top-down utility change management."

What are these barriers to analytics deployment? Well, one of them is budget, as can be expected. In a fairly clean sweep across the board, all respondents to the SAS survey listed both budget and change management as key obstacles to recognizing the benefits of data analytics.

Survey participants were also asked about how they are currently using analytics, and the results were fairly evenly spread across the board: 34 percent are using analytics for transmission and/or distribution network optimization, 28 percent for energy portfolio optimization, 26 percent for customer analytics and 12 percent for enterprise IT analytics.

In terms of network optimization, respondents' Top 2 benefits gained from investing in network analytics software broke down this way: lower the costs of energy transmission and distribution operations (60 percent), improve restoration time and efficiencies (45 percent), predict and prevent outages or mitigate network outages (39 percent), lower the risks and uncertainties of energy transmission and distribution operations (35 percent) and share more near-real-time performance analytics with short-term planners (15 percent).

When it came to customer analytics, the Top 2 benefits were spread fairly evenly between four points: improve our understanding of customer segments (53 percent), better understand customer demand for new products and services (49 percent), identify real sources of customer value (47 percent) and better understand the future behavior of customers (45 percent).

(Unsurprisingly, except perhaps to Mr. Chase and his ilk, "identification of specific electric appliances used within the household" was not noted by any of the utility respondents.)

"There is a huge focus on meter data analytics within the area of customer analytics," Farrell pointed out. "There is an opportunity here for enhanced data visualization opportunities." (Tomorrow's column will discuss this in more detail.)

And, though only 12 percent indicated they were currently using enterprise IT analytics, this is a quickly growing area in which utilities are investing time, energy and resources. Those surveyed in this area identified their Top 2 benefits this way: make business intelligent tools available in a self-service and on-demand manner (74 percent), improve enterprise data quality by analytics to incoming data before it is shared (37 percent), enhance performance management and capacity planning for IT operations (37 percent) and reduce analytical processing time in high performance environment (32 percent).

With utility data analytics usage and interest identified in today's column, tomorrow we will look at where utilities are taking this interest. From forecasting and predictive asset maintenance to revenue assurance and enterprise risk, the usefulness of analytics is cropping up in the most effective areas of the organizational structure first.

Join us as we discuss these issues and more at Utility Analytics Week, Sept. 18-20, in Arlington, TX.


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