Segmentation and Market-Based Pricing for Uncertain Episodic Service Demand: Case Study of Truckload Service Procurement for FEMA

Abstract

Following natural disasters and man-made disruptions, the uncertain, episodic, and time-sensitive demand for relief services increases the competition between humanitarian actors and private-sector customers. This leads to high procurement costs for both parties. Humanitarian actors focus on high service level first, but also care about reducing costs and externalities on local actors. We work with one such actor, The US Federal Emergency Management Agency (FEMA), and study their case of transportation service procurement. We propose segmenting FEMA's demand network and using market-priced contracts to improve service-level while reducing costs in order to satisfy emergency transportation demand. We find that implementing even simple procurement portfolios such as paying 71% over market rates and additionally paying front and back-haul prices for high frequency segments could have resulted in cost savings of $9.85 million over 2 years for FEMA.

Bio

Shraddha Rana is a postdoctoral researcher in the Humanitarian Research Group at INSEAD. Prior to that, she was a graduate research assistant at the MIT Center for Transportation and Logistics. Shraddha holds a MS and PhD in Transportation and Logistics from MIT and a B.Tech in Civil Engineering from IIT Bombay. Her research focuses on transportation and distribution capacity planning for critical operations, working closely with various humanitarian organizations.