Food Bank Forecasting with Professor Lauren B. Davis

This episode of Forecasting Impact features Professor Lauren B. Davis discussing her research on applying stochastic modeling and forecasting to food bank operations. Lauren shares how she began forecasting with a local food bank, which led her to focus on forecasting the highly uncertain supply of food donations. She details the food banks' donation sourcing process, the management of their supply chains, and the application of models like exponential smoothing, support vector regression, and ensemble methods to predict donation volumes.

Professor Davis addresses challenges in forecasting at various aggregation levels (network vs. location-specific), using optimization models for equitable allocation of limited supply, and the significance of storage and agency capacity limits. She emphasizes the importance of equity as an objective, the complexity of modeling true demand, and the crucial role of visual analytics and co-design with food bank partners. The episode underscores the practical impact of forecasting in humanitarian supply chains and the necessity of linking models with operational decisions.