A changing climate makes weather-related risk management an increasingly perilous task for utilities. It’s not easy to predict the type, severity and location of extreme weather events by committing restoration assets to it at the right time.

That’s especially true for mid-sized utilities that often operate with limited or aging weather prediction methods. By contrast, large utilities reduce risk with custom modeling and proprietary outage data. Mid-sized players need a scalable solution that delivers data-driven intelligence in real time, affordably and confidently. A new infographic illustrates how Storm Risk Analytics does just that, helping deliver response and restoration performance that:

• 39% of organizations using severe weather prediction or response technology report elevated customer satisfaction scores
• 69% of users report maintained or raised reliability scores (SAIDI, SAIFI, CAIDI)
• Better predicts weather impacts up to seven days ahead of the event  

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