Retail Operating Loop

Your systems detect.
Ward decides, executes, and proves it worked.

Six stages, one unbroken chain. The loop is the product. Below is one full cycle, stage by stage.

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01Signal in

Detect

Every store, every KPI, every system of record. Each anomaly is measured against that store's own baseline, so a busy Saturday in one location never hides a dead one somewhere else.

  • POS, inventory, labor, finance, weather, events, and supplier feeds read continuously
  • Forecasts run on the models your planners already trust
System of recordPOS · WMS · ERP · finance ledger · supplier feed
What changesTime-to-detect: minutes, not days
02Cause assigned

Attribute

Every signal traced to a cause: vendor short-ship, promo conflict, planogram drift, schedule miss, dock anomaly. Every link in that chain is signed and reviewable.

  • A reasoning graph: sources touched, SQL run, model fit, causes ruled out
  • The graph travels with the case
System of recordReasoning graph · audit log · model card
What changesTime-to-attribute: under an hour
03Play matched

Recommend

A case opens with the right play already attached. Owner, deadline, target KPI, success metric, all set on day one. No triage meeting.

  • Stockout escalation, vendor dispute, promo cancellation, planogram correction, markdown reset
  • Each play knows its trigger, procedure, and write-back
System of recordPlaybook catalog · case object
What changesTime-to-recommend: seconds
04Action against the SOR

Execute

The play runs against the system of record: Manhattan, Blue Yonder, SAP, Oracle Retail, Relex, the pricing and promo engines.

  • Federated queries for reads, approval-gated writes for changes
  • Cedar policy enforces who can do what against which source
System of recordManhattan · Blue Yonder · SAP · Oracle Retail · Relex
What changesTime-to-execute: hours
05Signed and logged

Audit

Every step signed: detection, attribution, play match, write-back, approver. Streamed to your SIEM the moment it lands.

  • Every number is one click from its SQL, sources, model, and parameters
  • Charters and policies live in your repo, versioned and signed
System of recordSIEM stream · Splunk · Datadog · JSONL audit log
What changesAudit coverage: 100% of cases
06KPI delta proven

Measure

The case closes only when the KPI moves. Fill rate up, shrink down, net promo lift positive.

  • A closed case is a measured delta against a metric you agreed to up front
  • The outcome attaches to the play that fired it and updates its win rate
System of recordKPI delta · attribution chain · play win-rate
What changesClosed-case definition: outcome ≥ pre-agreed threshold
The plays behind the loop

Six that ship in every deployment.

The cycle above is the shape. These are the procedures that run it: what fires each one, the five steps, what it writes back, and the number that closes it.

Stockout Escalation Zero on hand forecast inside 48 hours. Raises the replenishment. On-shelf availability · ≤ 6 hours Vendor Invoice Dispute Invoice ≠ receipt or contract price. Drafts the dispute packet for AP. COGS recovery · ≤ 24 hours Promo Conflict Cancellation Cannibalization mid-promo. Models kill-or-narrow, ends the overlap. Net promo lift · ≤ 2 hours Planogram Correction Sales-correlated shelf drift. Issues the corrected POG, verifies the reset. Compliance + sales lift · ≤ 12 hours Shrink Investigation Shrink above baseline. Attributes dock, floor, or admin and opens the case. Shrink % · ≤ 48 hours Markdown Cadence Reset Style velocity below cluster. Proposes a shallower, earlier ladder. Full-margin sell-through · ≤ 24 hours

All 43 playbooks, filterable by vertical, KPI and system →

One Cycle, Repeated

SolutionThis loop runs 24/7
across every store.

Plays that close build their win rate. Misclassified causes surface and get corrected. The loop learns.

Browse all playbooks → Get a demo →

Walk a real case end to end.

See the loop fire on your data. 90-day pilot. Pre-agreed metrics.

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