Investigate a shrink anomaly before automating action
Use cause-analysis thinking to investigate an AI shrink anomaly before taking action.
Shrink alert Store 118 is flagged for cosmetics shrink 2.4 times above peer stores. The model is not wrong to flag it, but the reason is still unknown. A bad escalation can damage trust with stores and teach the model team nothing. Cause analysis Effect -> possible causes -> evidence -> action Treat the AI anomaly as the effect. Your job is to sort possible causes and gather enough evidence to pick a proportionate action. Shortcut Flag equals blame. The store gets a fair process and the model gets better labels. An anomaly is a question with evidence attached, not…
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