Stockout Prediction on Blue Yonder, for store operations
Managing 800 stores from a spreadsheet is insane. Ward picks up stockout movement in your Blue Yonder data and traces what caused it.
Stockout Prediction on Blue Yonder, for store operations
Managing 800 stores from a spreadsheet is insane. Ward raises the signals that change a store operations decision.
What stockout prediction does: Ward detects SKUs trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice.
How Ward returns Stockout findings: Ward analyzes sell-through velocity, current inventory levels, lead times, and supplier reliability to predict stockouts 24-72 hours before they occur.
Getting the data in. Ward reads Blue Yonder outputs via API or flat file export. Compares forecasts against actuals to measure accuracy.
What it does
- Priority ranking by revenue impact
- Reduce lost sales by catching gaps early
- Automated replenishment recommendations
- Supplier-aware lead time modeling
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 |
retail_inventory_weekly | import | 1h ago |
retail_google_ads_daily | import | 1h ago |
retail_meta_ads_daily | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
finance-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
region-west-only | permit | Tenant::"acme" |
What Ward has eyes on.
Ward pulls from demand forecasts, replenishment recommendations, allocation plans from Blue Yonder on a read-only connection. Nothing is written back, and your Supply Chain configuration does not change. Blue Yonder stays the system of record.
Know before the shelf empties. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.
Why this combination
is its own problem.
A Director Store Ops does not need the stockout model explained. They need to know which stores moved, why, and what to do by end of day. Ward writes the finding at that altitude.
What the first 90 days
actually look like.
-
01
Week 1: read-only connection
Ward sits on top of Blue Yonder with read-only credentials and begins ingesting demand forecasts and replenishment recommendations. No config changes on your side. First insight cards arrive inside the first 48 hours.
-
02
Weeks 2 to 3: calibration
Baselines stabilize per store and per category. Ward stops flagging normal variance and starts flagging exceptions. This is the window where the false positive rate drops sharply.
-
03
Weeks 4 to 12: operating rhythm
Cards arrive on a daily cycle and get triaged like any other queue. Most teams find the volume settles into something one person clears in ten minutes. What matters is the action rate, not the alert count.
How Ward connects to Blue Yonder
Ward layers on top of Blue Yonder demand planning and replenishment. Ward watches what Blue Yonder recommends and flags when actual diverges from plan.
Setup: Ward reads Blue Yonder outputs via API or flat file export. Compares forecasts against actuals to measure accuracy.
Data Ward reads from Blue Yonder
Impact metrics with Blue Yonder
Data lake enrichment
Ward enriches Blue Yonder data with: Demand forecasts, POS actuals, Weather & events, Supplier fill rates, Competitor data
Managing 800 stores from a spreadsheet is insane.
- ×Morning check-ins rely on phone calls and email chains
- ×No single view of which stores need attention today
- ×Labor scheduling is disconnected from demand signals
- ×Planogram compliance is checked manually, quarterly
- ×Exception management is reactive and inconsistent
- ✓Morning brief delivered at 06:47 with prioritized action list
- ✓Estate-wide heat map of store performance, updated hourly
- ✓Staffing recommendations correlated with predicted traffic
- ✓Planogram compliance anomalies detected and flagged
- ✓Consistent exception handling with recommended actions
Poor labor allocation and inconsistent execution cost multi-store retailers 3–5% in lost sales. Source: RSR Research
Frequently asked questions
Ward reads Blue Yonder outputs via API or flat file export. Compares forecasts against actuals to measure accuracy. Data points include: Demand forecasts, Replenishment recommendations, Allocation plans, Exception alerts.
Managing 800 stores from a spreadsheet is insane. Ward solves this with automated insight cards: Morning brief delivered at 06:47 with prioritized action list. Estate-wide heat map of store performance, updated hourly. Staffing recommendations correlated with predicted traffic.
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 stockout problems Ward catches.
Root causes, not just alerts. See it on your data.
Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly
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.