Utilities Make Better Use of Big Data

According to a new survey of utilities executives worldwide including Oracle and IPSOS, North America Market Research revealed that Utilities congregate enormous quantities of data, but they fight to apply it to grave business problems

Roberta Bigliani, Associate Vice President and Head of Europe, West Asia & Africa for IDC Energy Insights says that the industry overall is still in the early stages of understanding the full potential of big data platforms combined with machine learning, what an analytics strategy entails and what big data and analytics can deliver to the business.

Utilities that are on the cutting edge of developing such cultures are applying analytics to new uses and new kinds of data. Take the issue of unpredictable energy demand: Shifts in customer behavior, such as the growing use of plug-in electric vehicles, have made it increasingly difficult for utilities to predict how much energy will be needed by using traditional forecasting techniques. A sudden, unexpected bump in demand can cause blackouts or require a utility to acquire the energy at a high cost.

Getting Rid of Equipment Malfunction

In the same way, predictive analytics can be applied to a wide range of industry issues, such as energy procurement, rates and tariff modeling and asset health and risk. For example, utilities are applying analytics to predictive maintenance, using data to determine when equipment is about to fail.

According to Mark Peacock, Principal in the strategy & operations practice of the Hackett Group, people talk a lot about smart metering, but that is capital-intensive and requires the utility to touch a lot of homes and commercial places. There is also progress being made in pulling information off other types of equipment so utilities can do better equipment maintenance.

Such early warning systems can give a utility subtle indication that small fluctuation in energy uses in a person’s home—which in the past would probably go unnoticed—signal a coming problem. Predictive maintenance allows a utility to swap out equipment before it fails; saving costs and avoiding interruptions in service that can cause customer satisfaction to plummet.

Analytics are also enhancing safety, a critical issue for any utility. In one case, a utility used sophisticated analytics to immediately determine that high gas usage in unoccupied premises was not a false positive due to pool heaters. In fact, thieves were going into the building and stealing copper pipes, resulting in gas leaks that could have caused deadly fires if repair trucks did not roll out quickly.

Crunching data about weather and the age of power lines and other equipment in different service areas can allow utilities to position repair trucks in strategic places when storms are approaching. This lets them address problems quickly and minimize the consequences of damaged lines.

Thinking about Innovative Technology

In the survey Victor Jimenez, utilities executive and analytics leader, Capegemini mentioned that the growing demands to provide better service to customers at a lower cost will put a premium on ways to rapidly process huge amounts of data—such as the cloud and in-memory computing.

Over the past two years, customer information has been—by far—the fastest growing data type among utilities, according to the survey. For example, utilities are employing “customer sentiment analysis,” which allows them to search out and analyze customer’s comments on the web. This gives them insight into developing new marketing programs and services.

This higher level of personalization, shaped by the use of data and analytics, will be a growing force in the utilities industry in the years ahead. Indeed, more personalized service is a component of almost every use of customer analytics by utilities, from alerting customers of unusual spikes in usage to giving call-center representatives a full view of a customer’s account, so that issues over bills can be resolved quickly.

Utilities are also using analytics to place customers into relevant segments (like company size) and analyze their energy usage to provide them with strategies for reducing consumption and savings costs. Having this type of “demand-side management” at an individual level was nearly impossible in the days before smart meters and analytics. In addition to using these new technologies, these advances require utilities to discard their traditional information system and share information across departments.

Overall Approach to Data

To make effective use of their growing stores, leading utilities are embracing not only new technology, but a new mindset around data. Utilities have seen themselves as a unique industry and they are often not interested in hearing about best practices from adjacent industries. IT people generally begin and end their careers in the utilities industry and their entire perspective is based on traditional industry practices. When utilities upgrade their infrastructure, they also need to teach people to think differently, according to Hackett Group’s Peacock.

As utilities explore greater use of analytics, “The kind of questions we should ask are: Do we have a revenue protection problem? If yes, how can we effectively address it using the data we have? What benefits can we generate through investing in analytics?”