The student team will develop and deliver an improved model for demand forecasting of product at both an individual SKU (Stock Keeping Unit) and aggregated SKU data for Kellogg’s Top 25 Customers within the demand sensing horizon (0 to 6 weeks). The model will be based on input variables from the supply chain. Current datasets available to students will include historical information of Kellogg’s, production, shipments, production plans and customer orders as well as a smaller dataset of POS (Point of Sales) data from one major customer.
More Information: 2017-Kellogg-Supply
Students who successfully match to this project team will be required to sign the following two documents in January 2017: