Grocery · Blue Yonder · Director Store Ops

Ward and Blue Yonder for Grocery store operations

Ward ingests Blue Yonder and hands you grocery daily cards scoped to store operations. Managing 800 stores from a spreadsheet is insane.

What a grocery Director Store Ops gets from Blue Yonder

Managing 800 stores from a spreadsheet is insane. Ward writes the finding at the altitude a Director Store Ops works at.

In a Grocery & Supermarket fleet the job is 30,000+ SKUs throughout stores. Fresh availability, shrinkage, and promo effectiveness across hundreds of stores. Ward monitors perishable turn rates and flags waste before it happens.

The connection itself. Ward reads Blue Yonder outputs via API or flat file export. Compares forecasts against actuals to measure accuracy.

app.getward.ai Live demo
Acme Grocery @Merchandising: Fresh Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why did Store 37 miss target last week?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.

SignalFinding
labor_efficiencyRev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak
inventory.freshFresh fill 83%, backroom replenishment lag at 2–4p
promo.liftBOGO 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.

8 parallel queries 3 sources cited confidence 0.92
Show me how to fix the staffing mismatch.
You · 9:43 AM
Labor Agent · drafting schedule diff
Querying labor_scheduling
Ask anything, Ward routes to the right agent. Cmd+K

Reporting

Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.

7d13w52w
Revenue vs. forecast
$48.2M
+4.2% WoW
Gross margin, center store
22.6%
−3.2pp
Fill rate, fresh
83.4%
−4.1pp
Shrink, West region
2.41%
+0.8pp
Revenue vs. forecast 13 weeks actual, 6 weeks forecast, 80% interval
Actual Forecast 80% interval
% of plan 106 94 100 forecast → W−13 W−5 today +6wk
Holt-Winters + weather regressor MAPE 4.1% at 4wk Backtested 24 months Crosses plan in 3 weeks
Forecast error by horizon MAPE, 24-month backtest
1wk 2.1%
2wk 3.0%
4wk 4.1%
8wk 6.3%
13wk 8.9%
Accuracy bar for promo decisions: ≤5% at 4wk
Models in production Every forecast ships a model card
ModelHorizonMAPE
holt_winters4wk4.1%
arima_sarimax13wk8.9%
gbm_demand1wk2.1%
bayes_hiernew store11.4%

Sources

Connect external systems to the data lake.

NameTypeLast sync
sap_pos_transactionsimport2m ago
sap_inventory_shrinkageimport2m ago
sap_labor_schedulingimport14m ago
relex_replenishment_planimport1h ago
blue_yonder_forecast_dailyimport1h ago
retail_fresh_waste_dailyimport1h ago
retail_promo_calendarimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
merch-read-defaultpermitModel::*
lp-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
fresh-team-westpermitModel::"fresh_waste_daily"
for Grocery on Blue Yonder data, live product demo.

What Ward delivers

  • 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

Metrics Ward monitors

Fill rate
Shrinkage %
Fresh waste %
Promo lift
Basket size

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.

The connection to Blue Yonder is read-only and runs on your schedule. Ward reads demand forecasts, replenishment recommendations, and the rest of the feed, then joins it with external context your Supply Chain does not carry: weather, local events, competitor pricing.

Coverage is store by store, category by category. Ward keeps a running read on fill rate, shrinkage %, fresh waste % over 30,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the fleet is fine and knowing which seven stores are not.

Why this combination
is its own problem.

Blue Yonder is the system of record for most grocery operators of your size, which means the indicators Ward needs are already there. The gap is not data collection. It is that nobody has time to read demand forecasts and replenishment recommendations every morning throughout every store.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Blue Yonder. Ward pulls from demand forecasts, replenishment recommendations, allocation plans and starts building baselines. First daily cards land inside 48 hours, before baselines are stable, so you can see the shape of the output early.

  2. 02

    Weeks 2 to 3: baselines

    Ward needs roughly two weeks of history per store to separate a real deviation from normal variance. During this window the cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: operating rhythm

    Insight cards arrive daily 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

Demand forecasts
Replenishment recommendations
Allocation plans
Exception alerts

Impact metrics with Blue Yonder

Forecast Accuracy
Plan vs actual tracked
Forecasts scored against actuals with external signal overlay.
Replenishment Exceptions
Revenue-ranked triage
Exceptions auto-prioritized so high-impact ones work first.
Fill Rate
Allocation drift caught
Plan-to-demand divergence flagged before stockouts form.
Plan vs Actual Variance
Feedback loop tightened
Continuous plan-to-outcome comparison for planning teams.

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.

Pain points
  • ×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
How Ward helps
  • 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

Grocery KPI impact

Shrinkage
Cause-level attribution
Loss prevention shifts from guesswork to targeted intervention.
Fill Rate
24–72hr head start
Stockout prediction cards arrive before customers notice gaps.
Fresh Waste
Flagged before spoilage
Perishable turn rates monitored by store.
Promo ROI
Net lift, not gross
True lift net of cannibalization and pull-forward.

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.

Yes. Ward reads Blue Yonder data and combines it with contextual signals (weather, events, demographics) to generate Grocery-specific insight cards. No custom development required.

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.

Ward delivers daily insight cards covering Fill rate, Shrinkage %, Fresh waste %, tailored for Store Operations decision-making. Each card includes what changed, why it matters, and what to do next.

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.

See what Grocery 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.

Step 1 of 3
What are your goals?
Step 2 of 3
About your operation
Step 3 of 3
Your contact info