Utilities
Transform business in many ways from smarter demand management to better weather predictions, finding new energy sources and more.
Embracing the power of data science in utilities
RapidMiner helps utilities tap into data science to ensure smooth delivery, profitable operations and unmatched customer experiences. We’re experienced in helping utilities across the globe drive real business impact through a wide range of data science applications including demand management and forecasting, predictions of disruptions and consumption, fraud identification and much more.
Utilities Industry Use Cases
Drive Revenue
- Forecast demand and predict which incentives and tariffs will improve load management
- Develop customer insights to improve targeting of campaigns about useful programs and offers
Cut Costs
- Predict failure of field and plant equipment and schedule maintenance optimally
- Increase accuracy of storm impact to anticipate and prepare for outages
- Accurately predict production and consumption to avoid costly purchase of peak energy on short notice
Avoid Risks
- Protect customers and escape liability by identifying signs of fraud quickly and stopping it
- Profile EH&S risks and take proactive measures to protect people and the environment
Why AI Now?
Consumers often don’t give their power a second thought — until it goes out. Although they may not realize it, the systems and processes preventing that from happening are getting smarter every day. Utilities companies that leverage the potential of machine learning and AI are enabled to offer less expensive and more reliable services, while those that don’t will surely fall behind.
From smarter demand management to better predictions of weather and other disruptions to finding altogether new energy sources and markets, utility companies have myriad ways in front of them to transform their businesses.
What Our Utilities Customers Say
Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences, and do not represent the views of Gartner or its affiliates.
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