Oracle Retail plus Ward, for grocery operators
Oracle tells you what happened. Ward attributes why, and what to do next, across your grocery footprint.
How Ward reads Oracle in grocery retail
In a Grocery & Supermarket store base the job is 30,000+ SKUs over stores. Fresh availability, shrinkage, and promo effectiveness across hundreds of stores. Ward monitors perishable turn rates and flags waste before it happens.
Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.
| Signal | Finding |
|---|---|
labor_efficiency | Rev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak |
inventory.fresh | Fresh fill 83%, backroom replenishment lag at 2–4p |
promo.lift | BOGO crackers cannibalized Brand Y by 28%, net category +6% |
Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.
labor_scheduling…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
sap_pos_transactions | import | 2m ago |
sap_inventory_shrinkage | import | 2m ago |
sap_labor_scheduling | import | 14m ago |
relex_replenishment_plan | import | 1h ago |
blue_yonder_forecast_daily | import | 1h ago |
retail_fresh_waste_daily | import | 1h ago |
retail_promo_calendar | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
lp-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
fresh-team-west | permit | Model::"fresh_waste_daily" |
Metrics Ward monitors
Grocery challenges Ward solves
- Fresh waste & spoilage
- On-shelf availability gaps
- Promo cannibalization
- Supplier fill rate variance
- Seasonal demand spikes
What Ward has eyes on.
Every one of your stores gets its own baseline. Ward monitors fill rate, shrinkage %, fresh waste % against it and pulls forward only the deviations that hold up. The two that show up most in grocery retail are fresh waste & spoilage and on-shelf availability gaps, and both are baseline problems before they are P&L problems.
The connection to Oracle Retail is read-only and runs on your schedule. Ward reads straight from sales audit, inventory positions, and the rest of the feed, then stitches together it with external context your ERP does not carry: weather, local events, competitor pricing.
Why this combination
is its own problem.
Running Ward on Oracle in a grocery store base skips the usual first step. There is no ingestion project, because Oracle Retail already holds sales audit, inventory positions, allocation. Ward ingests what is there.
How Ward connects to Oracle Retail
Ward integrates with Oracle Retail Merchandising (RMFCS), Oracle Retail Demand Forecasting, and Oracle Retail Analytics. Full stack visibility.
Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.
Data Ward reads from Oracle
Impact metrics with Oracle
Data lake enrichment
Ward enriches Oracle data with: Sales audit data, Weather & events, Competitor pricing, Demographic data, Supplier scorecards
Grocery KPI impact
Frequently asked questions
Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments. Data points include: Sales audit, Inventory positions, Allocation, Replenishment, Demand forecasts, Price management.
Yes. Ward reads Oracle data and combines it with contextual signals (weather, events, demographics) to generate Grocery-specific insight cards. No custom development required.
First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable baselines for your specific operation.
No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards, so your team acts on findings instead of hunting for them.
Related solutions
See what Grocery 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.