Early Warning System for Foodborne Illness in Supply Chain

Student: Kezia Oketch, 2020-2021

Sponsor: McDonald’s Corporation, Chicago, Illinois

Foodborne illness can cost restaurants anywhere from thousands of dollars to millions if the issue has a chance to reach the customer. Millions more when products already on stock shelves need to be recalled or disposed of. By detecting supply chain anomalies earlier, McDonald’s can save owner operators hundreds of thousands if not millions of dollars in overhead by eliminating purchase orders for tainted goods. McDonald’s new Global Analytics Hub – serving as a center of excellence for analytics and machine learning – is partnering with the Food Safety team on the development of technology to provide an early warning for foodborne illness. This project involves analysis of existing food safety audits and third-party data to determine relationships between supply chain activities and food safety events. Ultimately, delivering automated notifications when anomalies are identified. This early warning alert system will be developed and deployed either through a web application, email or text notifications. Including the alert mechanism and a visualization of the issue with the ability to dig into the data for an individual McDonald’s market.