Clarity with Data: Logistics Decision Making under Risk Part 2

In the first part of this series, we introduced a use case involving a Midwest valve manufacturer facing potential hurricane threats to its coastal suppliers. We walked through the initial steps of building a supply chain model, including defining the scope, bootstrapping the logistics network with OpenStreetMap data, and simulating a basic supplier network. In this post we will continue the example and show how simulation can be used to understand the operational and financial impacts of disruptions on the supply chain. As in previous posts, we will show our work with full implementations in code.