To Thrive, Utilities Must Have a Data Analytics Strategy and a Business Intelligence Plan

Tyler Chase, Managing Director Energy and Utilities Industry Global Leader
Steve Freeman, Managing Director Data Management and Advanced Analytics

The big data revolution transforming industries worldwide is bearing fruit as companies improve their understanding and analysis of their information to increase efficiency, reduce costs, predict outcomes and enhance customer satisfaction. The utility industry, however, continues to be one of the laggards in the race to harness big data. In light of the prolonged sluggish demand for power, there are certainly opportunities for utilities to boost their bottom lines by using information more effectively.

One reason for the industry’s feet dragging is that utilities today are collecting more information than ever before, leaving them a bit overwhelmed. Data pours in from connected supervisory control and data acquisition (SCADA) systems along the transmission grid, smart meters, distributed generation resources, and customer-centric technologies designed to track and conserve power. Billing, workforce management, maintenance and other operational processes are also throwing in reams of data.

To stay on top of and extract benefits from the enormous volumes and speed of information now available, it becomes critical for utilities to develop a robust data management strategy. Cost, accessibility and governance are key considerations when formulating the data strategy for this new information asset. Important questions in developing this strategy include:

  • How can the company effectively store all the data it receives?
  • How can this data be integrated with other systems?
  • How can the information be accessed efficiently to make better decisions and benefit customers?
  • What data is useful and what data is noise?

The data strategy also must ensure that the information is retained and prioritized for analytical and regulatory purposes while being ever mindful of both security and scalability. It must be designed with an eye to the future, allowing for growth in both data volume and new and varied data assets yet to come.

To illustrate the trend, consider that smart meters and advanced metering infrastructure (AMI) are now capable of transmitting customer usage data several times an hour – versus utility workers physically reading meters once a month. And this data torrent is affecting all utilities, regardless of size or business model.

On this backdrop, it’s no surprise that the industry is spending billions of dollars a year to implement analytic technologies. GTM Research predicted last year that utilities worldwide would spend more than $10 billion through the year 2021 on analytics and integration services to leverage the value of AMI investments alone. Some years earlier, the same research organization anticipated that from 2012 through 2020 utilities globally would spend $20 billion on power utility analytics – anything from grid sensors on the transmission side to AMI on the consumer end – with investment increasing annually and hitting $3.8 billion in the final year.

To provide actionable information, much of that energy analytics investment must go toward dashboards, modeling tools and other visualization technologies that collect, streamline and integrate information for a real-time, minute-by-minute, picture of the grid and other systems. Accurate and timely information like this can lead to better predictions about peak usage periods, possible transmission and distribution bottlenecks or interruptions, and even when particular customers are likely to have problems paying.

More specifically, visualizing utility data can help utility companies:

  • Perform load management and real-time forecasting. Harnessing data to foresee power supply and demand can help provide more affordable services to consumers.
  • Identify problems quickly. Utilities that can immediately address transmission and distribution interruptions or other glitches along the grid can avoid service outages, or at least minimize their duration.
  • Detect theft. Illegal power connections steal some $89.3 billion from utilities around the globe annually. While the majority of that theft occurs in emerging markets, local U.S. utilities are no strangers to this illegal activity and typically provide customers with hotline numbers to report unlawful connections. Data analytics visualization can help spot when and where those connections go live.
  • Improve management. Providing customers with better visuals made possible by data analytics can help explain pricing swings, service disruptions or other variables that affect consumers. Ultimately, that will give customers the information needed to conserve energy and may even defuse potentially volatile utility-customer interactions.

While the deluge of data is without doubt currently challenging the ability of utilities to integrate and make sense of such data in the most profitable way possible, the opportunities are clear, and we’ve outlined some of them. Utilities should be investing in a comprehensive data analytics strategy today, to inform and guide management on decisions that will deliver benefits for years to come as the proliferation of data continues to grow. Effective use of visualization tools can further put this information to work, and the companies that take advantage of the available technologies and use them as part of a well-honed business intelligence plan can quickly transform from laggard to leader in today’s challenging environment.

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