Risk pooling under correlated demand

This technical brief treats risk pooling under correlated demand as a decision system: define its state, objective, feasible actions and evidence before comparing algorithms.

Practitioner lens

Separate prediction from action in risk pooling under correlated demand: identify what is estimated, what is optimized and which business rules must remain binding regardless of model confidence.

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.