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Forecasting Supply and Demand Is Essential for Energy

Between changes in weather, occupancy, foot traffic, business workloads and more, consumer energy needs can fluctuate significantly. This makes it difficult for energy providers to ensure supply will meet the demand. For example, if an energy provider generates more energy than needed, it has wasted time and money. Conversely, if it fails to meet consumer demand, customers can lose trust in the provider.

Thats why many energy providers are turning to predictive analytics to draw from dozens of variables and stay on target. These analytics, according to a 2022 report by Popmodo, help forecast consumption and improve a companys chance at achieving their sustainability goals.

READ MORE:What trends to watch for in energy and utilities in 2023.

Predictive analytics uses data on what has happened in the past to make highly educated guesses about what is likely to happen in the future. More specifically, and often through the use of statistical models, machine learning algorithms and other data analysis techniques, predictive analytics finds patterns in historical data to identify risks and opportunities and forecast potential scenarios. In this way, predictive analytics helps drive strategic decision-making.

For energy companies, trying to forecast without predictive analytics can be particularly daunting due to the numerous variables at play, including energy sources, weather conditions and inconsistent workloads. Predictive analytics efforts greatly improve the accuracy of these forecasts, especially when they involve regression analysis.

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How Predictive Analytics Can Help Forecast Energy Needs - BizTech Magazine