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Predictive Analytics: Powering The Utility Sector

As the opportunities for the adoption of predictive analytics continue to infiltrate almost every vertical, one industry investing heavily in exploiting these opportunities is energy and utilities. In order to successfully position themselves as utilities of the future, providers are embracing these emerging technologies, turning their focus to becoming more customer-centric through data analytics and AI-assisted technologies. In fact, the utilities industry is forecast to invest billions of dollars into more advanced analytics platforms that will leverage data from their own devices and Internet of Things devices of their customers.

Optimizing Supply and Demand

While early adoption of analytics solutions within the utility sector focused on the analysis of data to better understand their businesses, providers are now moving towards transforming new data streams, delivering actionable insights that benefit not only themselves but the entire industry. With the introduction of technology like smart grids, predictive analytics are helping utility providers deliver a dependable supply. Whether analyzing network data in real-time to predict network failures, or utilizing IoT devices such as ‘smart meters’ to provide more accurate forecasting, predictive analytics allow for optimized supply and demand.

Fueling Customer Retention Strategies

Predictive analytics utilized to monitor the buying intent of current customers, can alert providers to when a customer is indicative of a high intent of defection. Monitoring at-risk customers with ongoing behavior and purchasing patterns can alert sales and marketing when accounts are showing activity around competitive offers. Providers can then program an immediate response to competitive situations and reduce customer churn rate.

Accelerating Collection Cycles

One of the biggest challenges for businesses is the need to work with their customers to reduce their levels of debt quickly. Using data analytics, providers can better understand customer segments and payment behaviors better, while predictive models can identify which debtors are most likely to pay, accelerating the collection cycle. Predictive analytics can also help optimize operations by reducing average credit collection periods and improving staff performance.

 

As the industry strives towards transformation, technology is the overriding force driving this revolution. Whether harnessing predictive analytics to create a more personalized experience or utilizing machine learning to assist in debt management, the utility market is already shifting towards providers that can best harness the potential of emerging technologies. Key players in the industry need to continue to evolve or risk falling behind the pack.

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