The utility sector has been slow to adapt to the digital revolution. Part of the reason is that it has felt isolated from many of the economic challenges that other companies face. Most utilities have a natural monopoly on services in their area, so they didn’t face the risk of extreme competition that most industries must contend with. However, new challenges are forcing them to adapt and begin embracing big data to save costs and remain competitive in a changing industry landscape.
Stephen Callahan, VP of Global Strategy and Solutions for the Energy & Utilities Industry, IBM, wrote an article for R&D Magazine that states that big data is changing the future of the utility sector in unprecedented ways. He cited research from GTM Research, which shows that the capital that utilities will invest in data analytics will increase from $700 million to $3.8 billion between 2012 and 2020.
Callahan writes that big data is helping the utility sector on multiple fronts.
As smart grid and smart meters become crucial to the industry, they will likely start generating hundreds of terabytes of data every year—or unstructured text data compiled from maintenance records and Twitter feeds. The accuracy, breadth and depth of these new data points present new opportunities for the utility companies that are prepared to take advantage of them. Meanwhile, becoming a customer-centric, information-driven organization is no longer simply an option for most utility companies, it’s a business imperative. Technology shifts, regulatory changes and the emergence of empowered consumers all demand a new approach to customer engagement. With analytics, energy companies can make the shift to engage with customers in highly personalized ways that can increase customer satisfaction, lower the cost of service and promote new products and services. Callahan writes.
Industry analysts from Bain & Company have echoed his predictions. They state that big data is shaping the future of the utility industry by facilitating data driven decision making, complex decision making and multivariable statistical decision models.
