Predicting Power: How Machine Learning is Transforming Estimated Times of Restoration

In this panel session, utility industry experts will explore how artificial intelligence and machine learning are reshaping the way companies predict and communicate estimated times of restoration (ETRs). Panelists will discuss how these technologies are being used to enhance ETR accuracy, improve internal efficiency, and deliver clearer, more timely information to customers. Learn how utilities are leveraging data-driven tools to solve persistent customer experience challenges and build greater trust during power outages.

Moderator:

 

  • John Board, Senior Consultant, Inc.
John is a certified CX professional and marketing leader with more than 20 years of experience in the utility industry.  He brings extensive experience in qualitative research methodology, journey mapping and marketing experience in B2B, B2C and Multicultural segments. 

 

 

Panelists:

 

  • Ryan Keilen, Senior Manager of Customer Data Analytics, Consumers Energy 
Ryan has been with Consumers Energy for 14 years, and has been working in the Data and Analytics space for the last 6 years within the company.

 

  • Carl Schoenhofer, Director, Customer Outage Journey, PG&E 
Carl has been with PG&E for 12 years. As the Director, Customer Outage Journey PMO, he leads a matrixed team to improve customers’ end-to-end outage experiences.  Previously he was a Regional Senior Manager where he served as the cross functional leader and led a number of strategic initiatives to address customer and community pain-points in the areas of capacity, reliability and PSPS.  Prior to coming to PG&E, Carl worked as a Vice-President & General Manager in the sawmill industry and as Chief Financial Officer for a Dairy Cooperative.

 

  • Tim Krall, Director, Advanced Analytics, Exelon

 

 

 

 

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