- Data Analytics
- Risk Management
The food-service industry in the United States is worth approximately $300 Billion annually and supports 1 million jobs across the country. The sponsoring company is a major distributor in the United States for different categories of restaurant chains, ranging from counter-only-service to full-service. The key products in their supply chain include meat such as poultry and beef, which are vulnerable to both supply and demand shocks, and could have significant impact to their operations. While they have some visibility downstream to understand causes of demand shocks, there exists an information gap upstream to understand supply shocks. This project aims to connect various external data sources to internal data to 1. identify what supply shocks looks like; 2. find lead indicators of supply shocks in the external data; and 3. quantify their impact on the sponsoring company in order to improve operations planning and contingency planning. The models we built predict instances of expedited shipments and delayed shipments as they relate to macro factors, such as severe weather, wholesale prices, and national slaughter rates.