Last week I attend the Utility Analytics Summit in Irvine, CA, which was sponsored by Southern California Edison. I’ve been to a lot of data conferences in my day, (let’s just say this was not my first rodeo) however, it was my first foray into the world of utilities. What I noticed right away was that data-related challenges run rampant regardless of the industry. The analysts, data scientists, and engineers that I met at the summit were all struggling with similar issues that organizations in finance and government have been challenged with for years.
Todd Inlander, SVP & CIO at Southern California Edison put it best when he said, “The promise of predictive analytics is not for naught if you don’t have clean data.” It was evident in the opening general session that digital transformation in the utility sector requires good data quality, and it became even more clear in subsequent breakout sessions when we started to dive into the challenges of customer analytics projects.
The Journey into the Customer 360
The breakout session that I enjoyed most focused on a case study given by the Director of Marketing Intelligence and Customer Analytics from a large utility in the Midwest. In his world, customer experience is a new priority. Five or ten years ago, utilities didn’t have such a high focus on their customers as much as they do today. This is a result of the fact that the industry was heavily regulated, most companies were near monopolies, and customers therefore did not have a lot of choices when it came to selecting a supplier.
Times have changed. With the deregulation of utilities in many states as well as the increasing popularity of alternative energy options (wind, solar, etc.), utilities now must increase their emphasis on keeping customers happy. This posed a significant challenge for this Marketing Director because the customer data that he had was not up to the task. It was stored in multiple locations: the website management system, the contact center, in people’s heads, in excel, on a whiteboard, and none of it was standardized. This made marketing segmentation impossible; they were unable to combine demographics, firmographics or customer research data to inform decision-making. Some of their top challenges included:
• Not having a single source of truth for customer data
• Being unable to easily answer the question, “what do our customers want?”
• Having no visibility into how many times they were contacting customers
In addition to the challenges posed from data being stored across multiple, disparate sources, the company also faced challenges with their data quality. Their service addresses and street names were invalid which was hindering their ability to accurately service and market to their customers. To rectify this situation, they established a new data governance team and evaluated tools like Experian Pandora to help with profiling and cleansing their data. These initiatives are still in their infancy, but they are well on their way to establishing more effective and efficient marketing initiatives, as well as delivering an improved customer experience.
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