April 28 Asset Health Analytics Community Conversation - "An Analytics Approach to Vegetation Manage

Join the Asset Health Analytics Community on Wednesday, April 28, 2021 at 2:00 PM CT for a panel discussion on "An Analytics Approach to Vegetation Management".

Maintaining vegetation is one of the leading challenges for utility companies. Trees and branches can cause power lines to fall – leading to service interruptions and potential wildfires. Vegetation can be one of the leading drivers in power outages. Traditional approaches to vegetation management has involved time-consuming and costly on-site inspections, relying primarily on human observation. Now, to address this challenge more proactively, utility companies are moving towards an analytics approach to vegetation management. Join us for this panel discussion to learn from multiple utilities, including:

• How an analytics approach to vegetation management gets put into action
• What does the data science approach to vegetation management look like
• Business benefits that have been realized with an analytics approach to vegetation management
• We will learn how a utility will use existing asset management data for transmission lines and apply that data to solve vegetation management project priorities. This utility has information on consequence of failure of transmission lines, but they don’t currently apply it to their vegetation management methodology. they will share information on a proposal in the works to help fix that
• A solution provider will share how they have helped their utility partners deploy vegetable management data science projects to help them reduce their veg budget with no negative impact to safety or reliability.

Panel Discussion Facilitator and Panelists: 

• Facilitator: Charlie Schaeffer, IT Director - Ameren
• Panelists:
  • David Martin, Sr. Manager, Vegetation Management - Evergy
  • Rebecca Afsar, Civil Engineer - WAPA
  • Ron Adams, General Manager of Vegetation Management - Duke Energy
  • Tom Martin, Vice President of Product, Data Science Division - E Source

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