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Loss Prevention · All retail

Sweethearting Detection

Discount and void patterns suggest sweethearting. Correlates operator and lane.

Target KPI Shrink
Executes in ≤ 48 hours
System of record POS · LP analytics
Run this on your data → How the loop closes
Trigger condition

Employee-discount, manual-override or skip-scan indicators concentrate on an operator well outside the peer distribution, and repeat across shifts.

Write-back

Review case opened in LP analytics with the signal set and peer comparison attached; observation scheduled.

Every write is gated on an approver role you name. Nothing runs unattended.

Procedure
  1. Combine the weak signals, since no single one is evidence: scan gaps, discount frequency, and basket value against lane norms.
  2. Test whether the pattern follows the operator across lanes and shifts, which separates behaviour from equipment.
  3. Check the mundane explanations: a faulty scanner, a produce code everyone gets wrong, an untrained new starter.
  4. Route to LP as a review with the statistical basis stated plainly, so a human judges it rather than a threshold.
  5. Close when the pattern resolves, whether through coaching, a repair, or a substantiated case.
Outcome metric

Signal concentration against the peer distribution over 45 days, and recovered value where substantiated.

The case closes on this number, not on the action being taken. A playbook without a close condition is a dashboard.

The rest of Loss Prevention

Shrink Investigation Shrink above baseline. Attributes dock, floor, or admin and opens the case. Shrink % Receiving Dock Audit Dock-receipt mismatches recurring. Flags the vendor and deliveries to audit. Shrink POS Exception Sweep Voids and refunds clustering on a register or operator. Shrink Refund-Fraud Pattern Refund behavior outside the norm. Builds the case with the timing. Shrink

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