Convenience shrinkage, delivered as insight cards instead of dashboards.
Most Convenience retailers find shrinkage problems in the post-mortem. Ward finds them while you can still act.
Why shrinkage matters
in convenience retail.
C-store shrinkage is dominated by slow-bleed employee theft and scan avoidance, small per-transaction losses that compound across thousands of daily transactions. Ward monitors voids, no-sales, and scan-rate deviations, then correlates them with shift patterns and employee schedules to surface risk that audit cycles miss.
Benchmarks. C-store shrink runs 0.8-1.8% of inside-store sales, with tobacco and high-margin impulse categories driving disproportionate dollar loss. A small per-transaction void pattern (under $5) on tobacco can cost $15K-40K per store per year before it triggers traditional threshold alerts.
Shift pattern anomaly, regional c-store operator
Ward flags multiple locations with a consistent pattern: tobacco void rates spike during a specific overnight shift window. The amounts are small enough to evade threshold-based alerts but consistent enough to represent significant annual loss per store. Ward attributes the pattern to specific shift schedules, and investigation confirms scan avoidance by a ring of night-shift employees across the affected stores.
Three pitfalls Ward catches
in convenience shrinkage.
- 01 Threshold-based void alerts catch high-dollar individual events but miss the coordinated small-dollar pattern that adds up to the real loss.
- 02 Vendor-direct receiving for tobacco and beer happens outside the POS; shrink in those categories surfaces only at periodic counts.
- 03 High-margin impulse items (candy, gum) get under-counted because shrink rates are reported as percentages of large category totals.
How Ward runs shrinkage
for convenience retailers.
-
01
Profile baseline transaction patterns per store-shift
Ward learns each store's normal void, no-sale, and refund rates by shift and employee, surfacing deviations against the store's own baseline.
-
02
Correlate anomalies with schedules
Patterns that align with specific shift windows, employee groupings, or vendor visits get flagged with supporting evidence and dollar exposure.
-
03
Coordinate intervention with LP and ops
Cards include suggested actions (covert audit, scheduling change, register reassignment) and track post-intervention shrink trajectory.
What a Ward card looks like.
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled the 6–9a daypart for the 14 Route 9 sites against the chain baseline. Two causes, one of them scheduling.
| Signal | Finding |
|---|---|
daypart_sales | 6–9a revenue −11% vs. chain, coffee units −18% |
labor_scheduling | Second associate clocks in at 7:30a, peak starts 6:40a at 9 of 14 sites |
foodservice.waste | Breakfast sandwich waste 14%, hold times past 4 hours at 6 sites |
Recommend: move the second open to 6:15a at those nine sites, cut the breakfast batch by one tray, and re-check attach in two weeks.
daypart_sales…
Dashboards
Pinned views built from saved data-lake queries.
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
ncr_pos_transactions | import | 2m ago |
pdi_fuel_transactions | import | 2m ago |
verifone_forecourt_events | import | 14m ago |
ncr_planogram_audit | import | 1h ago |
retail_daypart_sales | import | 1h ago |
retail_foodservice_waste | import | 1h ago |
retail_labor_scheduling | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
ops-read-default | permit | Model::* |
lp-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
fuel-team-forecourt | permit | Model::"fuel_transactions" |
Convenience shrinkage:
the shift.
- ×Daypart demand variation
- ×Planogram compliance
- ×Impulse category optimization
- ✓Cause-level shrinkage attribution
- ✓Store-vs-estate benchmarking
- ✓Receiving dock anomaly detection
Convenience KPI impact.
Value compounds across multi-site operators. Chains with 100+ locations see the strongest returns. Fuel-dominant locations should expect impact concentrated on forecourt-to-store attach rate.
Questions about convenience shrinkage.
C-store shrinkage is dominated by slow-bleed employee theft and scan avoidance, small per-transaction losses that compound across thousands of daily transactions. Ward monitors voids, no-sales, and scan-rate deviations, then correlates them with shift patterns and employee schedules to surface risk that audit cycles miss.
Ward flags multiple locations with a consistent pattern: tobacco void rates spike during a specific overnight shift window. The amounts are small enough to evade threshold-based alerts but consistent enough to represent significant annual loss per store.
Ward focuses on transaction anomaly rates (voids, no-sales, manual overrides), shift-correlated patterns, high-theft category velocity gaps, and receiving accuracy on high-value items, benchmarking each store against its own history and the estate average.
First shrinkage insight cards arrive within 48 hours. Stable convenience baselines form within two weeks.
Convenience shrinkage
by data source.
More Convenience insight cards.
Convenience retailers: see what shrinkage problems Ward catches.
Root causes, not just alerts. See it on your data.
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Find out what your data has been hiding.
Tell us about your operation. We’ll show you the problems Ward catches, and the ones your current tools miss.