While most companies wait until December to release their yearly outlook, at the Utility Analytics Institute we always like to be ahead of the curve. In 2013 (and, well, part of 2012) the Utility Analytics Institute will be diving into deeper research around these top analytics topics.
The optimization of asset management is finally getting the attention it deserves. Asset optimization analytics assist with optimizing the performance and reliability of grid assets. This analytics area includes categories such as transformer management, substation management, and overall transmission and distribution asset management. With all the oohing and aahing over advanced analytics in areas like grid optimization and engaging customers, folks in asset management analytics have admitted to us that they can feel a little left out.
However, at Utility Analytics Week, I sensed a buzz around predictive asset management. I can't tell you how many people talked to me about advancing asset optimization analytics, and were trying to figure out how to introduce or bolster predictive asset management in their organizations. Asset optimization is an analytics area that is attracting the attention of many utilities.
Key questions for 2013: How can utilities move forward asset optimization analytics? How can asset optimization focus on both improving data quality and developing real-time, predictive analytics?
Who are the ideal analytics employees for utilities? Do they exist? These questions come up again and again for utility companies looking at analytics initiatives. According to some utilities, the person would need a strong analytics background, but also a solid understanding of how utilities operate. According to others, the person would need to be more of skilled facilitator who could help bridge the gap between IT and the business units in order to move analytics forward. Utilities also are considering how, ultimately, it may not have to be one person with all of these skill sets. As one insightful participant noted at our Utility Analytics Week event, "If we could just get two 20 year-olds with computers together with a 60 year-old lineman, then we'd set."
Key questions for 2013: Who is the right person to address the analytics needs of utility companies? How do utilities find those individuals or develop them within their companies? Can outside providers serve these needs?
Customer segmentation and marketing
Personalized marketing is huge, well, at least in industries like retail, finance and telecommunications. In those industries it is all about reducing customer churn in incredibly competitive markets. As a result, there is a great need for sophisticated customer marketing and segmentation analytics. With most North American utilities, the competition for customers isn't quite the same. However, although a utility may not lose a customer, customer satisfaction is king. And when utilities don't fully understand their customers, this can have disastrous consequences for customer satisfaction. Analytics can help limit detrimental impacts to customer satisfaction. As a result, we're seeing an increased focus on analytics that help utilities better understand their customers, and increase customer participation in offerings such as energy efficiency and demand response programs.
Key questions for 2013: How do utilities successfully embrace customer individuality and incorporate it into their businesses? How do they better engage customers in their energy consumption? How much do utilities really need to engage customers?
Data quality and data integration
The more advanced analytics become, and the more utilities rely upon them for key decisions, the more important it is to focus on the foundation of analytics: data. The guidance utilities extract from analytics is only as good as the data feeding into the analytics. Data quality is paramount.
Another key area utility companies need to consider with analytics is data integration. Having good data is a first step, but may not be enough for success in the complex world of utility analytics. A utility may have great, high-quality data, but if it can't access easily the data, it won't be able to extract much value from those data sources. Many data sources already exist in utility companies, but due to the siloed nature of these businesses, these data sources are often not connected. To begin leveraging advanced analytics, utilities need to realign these data sources to provide a solid foundation of data that can be accessed throughout the company.
Key questions for 2013: What can utilities do to ensure their existing data is accurate? How can utilities create an environment the supports data quality? What barriers can utilities tear down to ensure better data integration? How much data integration is really needed?
Building the USS Analytics Enterprise
The push to tear down traditional business silos and spread advanced analytics across the company is putting significant pressure on utilities to manage the flood of data they're swimming around in, and figure out how to put analytics in the hands of nearly every employee. We're seeing the focus on customer and grid analytics starting to spread to enterprise-wide analytics efforts, which brings a new set of issues as utilities look to scale up their advanced analytics efforts.
Key questions for 2013: How can utilities ensure that accurate, reliable data is available across the enterprise for a variety of analytics uses? How can utilities successfully plan for and deploy the infrastructure needed to support real-time, predictive analytics across the enterprise?
These are just a few hot topics that utility analytics professionals need to be aware of for 2013. Again, we'd love to hear your thoughts about these research areas, and what you'd like to see from the Institute.
Thanks for reading!
H. Christine Richards is the director of knowledge services for the Utility Analytics Institute, a division of Energy Central.