Case Study: US Foods achieves real-time demand forecasting and reduced perishables waste with SafeGraph Patterns

US Foods Creates a COVID-19 “Disruption Index” Using SafeGraph Patterns Data

US Foods, a leading American foodservice distributor that partners with 300K+ restaurants and operators, needed a way to anticipate local demand during the COVID-19 crisis so it could reallocate people and perishable inventory and avoid waste. To get real-time visibility into where customers were — and weren’t — going, US Foods turned to SafeGraph and its Patterns foot‑traffic dataset.

Using SafeGraph Patterns data, US Foods built a COVID‑19 “disruption index” that combined government shutdowns, local case and unemployment data with SafeGraph and transaction feeds to correlate foot traffic with shipped case volume. The insights revealed a 20–30% spike in grocery traffic, helped close a record number of new accounts in late March 2020, enabled sales of perishable goods that would otherwise have spoiled, optimized supply chains, and provided county- and ZIP‑level reopening signals — demonstrating the measurable impact of SafeGraph’s data.

US Foods

Federico Masais

Sr. Director, IT Supply Chain Systems