August 20, 2025, 2 p.m. - 3 p.m. ET
FEMP IACET: 0.2
Level: Advanced
In this workshop, participants will explore best practices for analyzing fleet utilization and right-sizing using a sample fleet dataset. Using an example fleet dataset, attendees will learn how to identify low-use vehicles and prioritize fleet assets based on data-driven insights. The session will provide a practical framework and best practices for determining which vehicles to flag for potential elimination or downsizing to reduce fleet costs, while still maintaining agency fleet mission requirements.
Learning Objectives
Upon completion of this course, attendees will be able to:
- Understand key metrics and thresholds for evaluating fleet utilization and identifying low-use vehicles;
- Apply a step-by-step framework to analyze utilization data and develop right-sizing recommendations that maintain mission readiness;
- Use real-world examples and peer insights to explore common barriers and successful strategies for utilization analysis;
- Interpret and validate data findings by engaging with drivers, custodians, and leadership to support informed decision-making;
- Create an actionable plan for implementing fleet optimization recommendations and communicating them effectively to stakeholders.
Instructor
- Emily Kotz, National Renewable Energy Laboratory (NREL)
About FEMP Training
The Federal Energy Management Program (FEMP) provides live and on-demand training to foster and maintain a high-performance workforce that constructs, operates, and maintains cost-effective federal facilities. Choose from topics like project financing, facility and fleet optimization, fleet management, resilience, sustainable product procurement, and more.
FEMP is accredited by the International Association for Continuing Education and Training (IACET) and awards IACET continuing education units (CEUs) upon the successful completion of select courses. FEMP training is provided through the National Institute of Building Sciences' Whole Building Design Guide (WBDG) learning management system.