Tom Martin leads the data science team and is a key partner to our clients in demonstrating how data science solutions can help solve their challenges. Prior to this role, he served as managing director of data science at TROVE, and he led the implementation of new technology and analytics at PG&E to reduce the company’s operational costs, improve safety, and increase grid reliability.
Content by this author
Storm Insight: Effectively manage storm-related outages to make sure you don’t leave customers in the dark
Major storm events are becoming more frequent and stronger, and with these storm events come outages. Receive accurate and prompt predictions for how, when, and where forecasted weather events will affect the distribution grid with a little help from E Source Storm Insight, a data-driven tool.
Optimize spending and improve grid reliability with data-driven vegetation management
Advances in technology and predictive data science are providing new opportunities for utilities to evaluate existing vegetation-management processes, achieve operational efficiencies, and save money. Read this blog post to learn more.
Optimizing vegetation management: Why data allows us to make better decisions than ever before
Learn how utilities can lower operations costs and improve reliability by applying predictive data and machine learning to vegetation management. With data science, utilities will also minimize problems from unplanned work and ultimately improve safety and customer satisfaction.
Sustainable utility matters: Data science as a service
By adopting our data-science-as-a-service (DSaaS) solution, utilities can become more data-driven in partnership with experts in a flexible, organic way that accelerates speed to value. Learn more in this insightful interview with E Source’s Tom Martin!
Utility risk management: Why “the way we’ve always done it” is now the riskier approach
Well-worn, “safe” risk management approaches that may not deliver results but don’t rock the boat are beginning to come under pressure due to macroenvironmental factors. Find out why doing what we’ve always done may be perceived as safer, but may not be the best option for risk management.