Technology is changing the way that many industries function for the better, offering exciting and dynamic new ways to provide their services to customers. Like many tech businesses, the energy sector is one of many industries to benefit from such technological advancements. From smart meters that more accurately calculate a consumer’s energy bill to the presence of e-bills, reducing paper waste and postage costs, there are plenty of ways that tech and the internet have enabled energy providers to reduce their fees and ultimately make more money.
One way that many businesses around the world are improving their business operations is by leveraging data. From customer data to sales patterns and performance reports, there are hundreds of ways that data can inform your decision making with actionable insights about your company, its customers, and its employers. Predictive analytics tools are taking the way your company uses data up a notch by using machine learning and artificial intelligence algorithms to add even more power to the insights you can gather. Learn more about how predictive analytics can benefit your energy business below.
What is predictive analytics and what can it do?
As previously mentioned, predictive analytics is one of the leading tools for businesses and enterprises looking to truly make the most of their data. All of this begs the question: what exactly is predictive analytics—and why is it so useful to so many industries? At its heart, predictive analytics helps you forecast things about the future of your business by using advanced algorithms and historical data. By harnessing these kinds of tools, predictive analytics allows you to use data in a much deeper way than traditional data analytics or business intelligence reports.
For example, prior to predictive analytics, most data analytics tools were focused on reporting on what had happened and trying to explain why it happened. Thanks to the power of machine learning and AI, predictive analytics takes this sort of reporting into the future. Instead of just reporting on what has happened in the past, data analytics can help you forecast what sorts of events or customer behavior could happen in the future. Even better, some data analytics tools perform prescriptive analytics functions, offering you actionable insights about which sorts of outcomes are most desirable in the future.
How does predictive analytics impact the energy sector?
Clearly, when it comes to identifying future trends and offering powerful insights about your customers and data, predictive analytics truly excels. However, how exactly can it positively benefit the energy sector? One way predictive analytics is making major inroads in the world of power and electricity has to do with the way that predictive analytics tools can help you foresee potential problems in your supply chain or customer behavior prior to them becoming too detrimental.
For example, you may see a trend that energy consumption increases as temperatures increase in a certain geographic area. While that seems like common sense, having a predictive data tool monitoring energy consumption by region can help you act before a service disruption occurs. In this hypothetical situation, if machine learning algorithms forecast that the number of consumers in a specific area and the increase in temperatures could pose a risk to your power supply, you can preemptively act by sending a mobile transformer to the area just to be safe. The resiliency offered by mobile substations makes them integral to keeping your power grid up and running, and by using predictive analytics tools and software, you can better deploy mobile transformers to the areas of your grid must in need of some added resiliency. As such, you can improve the quality and consistency of your service, and, in turn, keep more customers.
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