Analytics can revolutionize supply chain management through predictive modeling. Analytics can be used for demand forecasting, inventory optimization, streamlining supply chain processes, and reduce the risk of stock outages or overstocking. Analytics also has huge applications in the areas like Supplier Management, Risk Management, Route Optimization and Sustainability which are the use cases that every supply chain is looking to solve today. This session will explore Linear Programming for Supply Chain Optimization using the PuLP framework. PuLP is a Linear Programming (LP) modeler created using Python. The session will include use cases for logistics planning and inventory optimization using the PuLP and other python packages.