Cycle-count anomaly targeting

The aim is not to automate every exception. It is to recognize which one deserves attention first. This note examines cycle-count anomaly targeting as a practical decision-support pattern.

Practitioner lens

Treat cycle-count anomaly targeting as a workflow hypothesis. Compare the proposed intervention with the current way of working and check whether the improvement survives a busy planning cycle.

First experiment

Check whether source data is timely, owned and consistent across the systems that planners actually use.

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