Enhancing Cost-Efficiency and Effectiveness in USAID’s Food Aid Supply Chain Operations in Ethiopia

Millions of tons of food aid are distributed each year by the U.S. Agency for International Development (USAID) Bureau for Humanitarian Assistance and the legacy Office of Food for Peace (BHA/FFP). However, the need always exceeds available food aid resources. Efficiency gains in existing supply chains offer potential for closing this gap. In this paper, we investigate the impact of advance demand information (ADI) and commodity prepositioning strategies (CPSs) on the cost-efficiency and effectiveness of BHA/FFP’s food aid supply chain. First, we collect and analyze the historical food aid distribution data from 2011 to 2016 from USAID and partners and narrow the focus to Ethiopia, one of the world’s largest food aid recipient countries and the largest in Africa per capita. Next, we develop a data-driven optimization model based on an end-to-end food aid supply chain network from procurement to last-mile distribution. Then, we solve the model with a rolling horizon algorithm, build scenarios to reflect different ADI durations and CPS operational strategies, and analyze their impacts. Finally, we derive insights from the analysis of these scenarios and compare them with BHA/FFP’s historical transactions. We observe strong interaction between ADI durations and CPS on cost and on-time delivery. We conclude that selecting the appropriate CPS based on ADI availability improves both demand fulfillment and on-time delivery ratios and reduces costs in comparison with historical operations.