Would building a model that simulates my company’s supply chain be like a Bayesian network?
For example, if a manger comes up to me and asks, “will we go stock-out in Korea store number 8, if we lower our safety stock at the Korean regional distribution hub?” Or, “if we switch to this new shipper whose transit lead time is one day longer than our currnet, how much will we have to increase safety stock?”
Is it a bayesian network framework that helps answer that?
For example, below is a graph depicting the supply chain network from the customer demand signal to our manufacuring facility (80320) to our warehouse (80322) to our regional warehouse in Korea (80073) to all of our Korean Stores (KR…). Assuming our demand distribution and lead time time distribution crudely depicted on the graphic, could we run a model based on the below information and see on hand inventory, in trasit inventory and probably stock outs at each store, being driven ultimately by demand?
