Distributionally robust safety stock

A deployable approach must explain what it optimizes, what it leaves uncertain and when it should defer. Those questions guide this brief on distributionally robust safety stock.

Practitioner lens

Complexity in distributionally robust safety stock should be justified with sensitivity analysis. Vary key inputs and constraints to learn whether the recommended action is stable or fragile.

First experiment

Separate model-generated proposals from approved actions; preserve a safe fallback when inputs are missing.

This is an original educational brief. It is a starting point for discussion, not a claim that one technique fits every supply chain.