Rapid Development of a Decision Support System to Alleviate Food Insecurity at the Los Angeles Regional Food Bank amid the COVID‐19 Pandemic

Abstract

To address the food assistance crisis during the Covid pandemic, the United States Department of Agriculture (USDA) launched a multi‐billion dollar “Farmers to Families Food Box program” (Box program) by working with approved suppliers (or distributors) to purchase fresh produce, dairy, and meat directly from farmers and package them into boxes. Recognizing that food banks did not have spare capacity to support the Box program, how should these food boxes be distributed to people who are in need? The USDA developed a novel solution by asking: (a) suppliers to distribute food boxes directly to agencies (shelters, food pantries, and soup kitchens); and (b) food banks to serve as “virtual intermediaries” to coordinate supply and demand between suppliers and agencies. However, as food banks were overwhelmed with their regular operations for distributing donated food during the pandemic, the Los Angeles Regional Food Bank (LARFB) found it difficult to develop and deploy a Decision Support System (DSS) to support the Box program with limited manpower and expertise. In this study, we describe a DSS co‐developed by LARFB, Salesforce, and UCLA. Unlike other DSSs developed in normal circumstances, the development and deployment of the DSS were conducted virtually within 45 days. Without this DSS, it would have been impossible for LARFB to support the Box program. Because this DSS was developed in a record time, we discuss several limitations and suggest future research opportunities for managing food bank operations during a pandemic.