Cost-Effectively Responding to Forecastable and Unforecastable Food Aid Needs: A Supply Chain Demonstration Model A Report from the Food Aid Quality Review Prepared by: Ozlem Ergun Stephen Vosti Keziban Rukiye Tasci Weijia Jing Beatrice Rogers Patrick Webb January 2021 COST-EFFECTIVELY RESPONDING TO FORECASTABLE AND JANUARY 2021 UNFORECASTABLE FOOD AID NEEDS This report was made possible by the Recommended Citation generous support of the American people Ergun, Ozlem; Vosti, Stephen; Tasci, Keziban through the support of the United States Rukiye; Jing, Weijia; Rogers, Beatrice; Webb, Agency for International Development’s Patrick. 2021. Cost-Effectively Responding to Bureau for Humanitarian Assistance Forecastable and Unforecastable Food Aid (USAID/BHA) and the legacy Office of Food Needs: A Supply Chain Demonstration Model. A for Peace (FFP) under the terms of Contract Report from the Food Aid Quality Review. No. AID-OAA-C-16-00020, managed by Tufts Boston, MA: Tufts University. University. This document may be reproduced without The contents are the responsibility of Tufts written permission by including a full citation University and its partners in the Food Aid of the source. Quality Review (FAQR) and do not necessarily reflect the views of USAID or the For correspondence, contact: United States Government. Patrick Webb The authors have no conflict of interest to Friedman School of Nutrition Science and declare. Policy Tufts University January 2021 150 Harrison Avenue Boston, MA 02111 [email protected] 2 COST-EFFECTIVELY RESPONDING TO FORECASTABLE AND JANUARY 2021 UNFORECASTABLE FOOD AID NEEDS ACRONYMS BHA Bureau for Humanitarian Assistance CSB+ Corn-Soy Blend Plus DM Demonstration Model DP Distribution Point EDP Extended Delivery Point FAQR Food Aid Quality Review FDP Final Delivery Point FFP The Office of Food for Peace HSC Humanitarian Supply Chain MS Management Science MT Metric Ton OR Operations Research PTH Planning Time Horizon SGM Sorghum Bulk UN United Nations USAID United States Agency for International Development USD United States Dollar USDA United States Department of Agriculture WFP World Food Programme WH Warehouse YSP Yellow Split Peas 3 COST-EFFECTIVELY RESPONDING TO FORECASTABLE AND JANUARY 2021 UNFORECASTABLE FOOD AID NEEDS TABLE OF CONTENTS ACRONYMS .................................................................................................................................................................. 3 TABLE OF CONTENTS ............................................................................................................................................... 4 EXECUTIVE SUMMARY ............................................................................................................................................... 5 1. Introduction ............................................................................................................................................................... 8 1.1. Key Issues Faced by USAID .................................................................................................................... 8 1.2. Key Issues Addressed by the Demonstration Model ........................................................................... 8 1.3. The Content of this Report .................................................................................................................. 10 2. The Underlying Data and Overall Structure of the Demonstration Model ....................................................... 10 2.1. The Data Underlying the Demonstration Model ................................................................................ 11 2.2. Forecastable Demand for Food Aid .................................................................................................... 12 2.3. Adding Unforecastable Demand for Food Aid .................................................................................... 14 3. Forecastable Demand: Key Results from Selected Model Simulations ............................................................... 19 3.1. Increasing the Institutional Visibility of Forecastable Demand .......................................................... 19 3.2. The Impacts on Total Supply Chain Costs of the Cargo Preference Act of 1954 .......................... 23 3.3. The Impacts on Costs of Expanding the Port Network in the Horn of Africa ................................ 24 4. Forecastable and Unforecastable Demand: Key Results from Selected Model Simulations ............................. 25 4.1. Economically Optimal Locations of USAID Warehouses .................................................................. 25 4.2. Responding to Very Large Changes in Unforecastable Demand ....................................................... 28 4.3. Responding to Disruptions in the fFod Aid Supply Chain ................................................................. 29 5. Conclusions and their Implications for Programming .......................................................................................... 30 5.1. Conclusions ............................................................................................................................................ 30 REFERENCES ............................................................................................................................................................... 33 ANNEX 1: DATA PREPARATION ........................................................................................................................... 36 1.1. Ethiopia Study ........................................................................................................................................ 36 1.2. Warehouse Study .................................................................................................................................. 44 ANNEX 2: MATHEMATICAL MODELS ................................................................................................................... 65 2.1. Ethiopia Study ........................................................................................................................................ 65 2.2. Warehouse Study .................................................................................................................................. 71 ANNEX 3: SOLUTION METHODOLOGIES ........................................................................................................... 80 3.1. Ethiopia Study Methodolody ................................................................................................................. 80 3.2. Warehouse Study with Unforcastable Demand Methodology .......................................................... 82 3.3. Software and Solver .............................................................................................................................. 83 3.4. Technical Overview of DM for Warehouse Study ............................................................................. 83 4 COST-EFFECTIVELY RESPONDING TO FORECASTABLE AND JANUARY 2021 UNFORECASTABLE FOOD AID NEEDS EXECUTIVE SUMMARY Millions of tons of food aid are distributed each year by the U.S. Agency for International Development’s (USAID) Bureau for Humanitarian Assistance (BHA) and the legacy Office of Food for Peace (FFP). Yet, needs always exceed the food aid resources available to meet them. Efficiency gains in existing supply chains offer potential for closing this gap. On-time delivery of food aid matters greatly, and there are trade-offs between supply chain efficiency and on-time delivery that decision-makers must be aware of and consider when making procurement, prepositioning, and shipping decisions. We co-developed, with USAID and other partners, a supply chain optimization demonstration model (DM) to assess the range of potential efficiency and effectiveness gains associated with alternative investments in and management of the food aid supply chain. The DM addresses, separately and jointly, forecastable (largely predictable) demand and unforecastable sudden-onset demand. The DM estimates the costs of alternative policy choices in responding to demand, as well as implications for on-time delivery of food aid products. The DM is built upon data obtained from USAID and the U.S. Department of Agriculture (USDA) on food aid procurement, shipping, and warehousing over the 2011-2016 period. While some of the site-specific circumstances (e.g., warehouse costs) and commodity-specific characteristics (e.g., levels and seasonal variations of commodity prices) may have changed since 2016, the basic structure of the food aid supply chain has not changed substantially since then, nor have underlying factors and interactions among them that influence the efficiency and timeliness of supply chain operations. Therefore, we believe that the patterns of results and insights reported below are representative of what one would expect today, and useful for exploring future investments in the supply chain and changes in its management. Needless to say, a concerted effort should be made to connect the current data streams that underlie the model to future data series; doing so would make it useful for informing operations and ongoing discussions regarding strategic investments. The following core messages emerged from the DM model simulations based on the 2011-2016 data. USAID Policies and Practices for Managing On-going Food Aid Demand – The DM was used to estimate cost reductions and improved on-time food aid deliveries