Grocery · Blue Yonder · VP Merchandising

What a grocery VP Merchandising pulls out of Blue Yonder

Ward pulls from Blue Yonder and hands you grocery cards scoped to merchandising. Your category managers are drowning in spreadsheets.

Ward and Blue Yonder for Grocery merchandising

Your category managers are drowning in spreadsheets. Ward delivers findings scoped to merchandising decision-making.

Grocery & Supermarket changes the scale of the problem: 30,000+ SKUs, every one of your stores. Fresh availability, shrinkage, and promo effectiveness across hundreds of stores. Ward monitors perishable turn rates and flags waste before it happens.

How the connection works. 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

  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

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.

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

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.

Why this combination
is its own problem.

Blue Yonder was built for transactions, not for merchandising decisions. The data is right there and it is in the wrong shape. Ward ingests demand forecasts and replenishment recommendations and rewrites them as a decision.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Blue Yonder. Ward reads demand forecasts, replenishment recommendations, allocation plans and starts building baselines. First insight 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: steady state

    Ward hands back daily cards each day, each with what caused it and a recommended move. Volume settles at a level a single person can read over coffee. The measure of success is not how many findings arrive, it is how many get acted on.

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

Your category managers are drowning in spreadsheets.

Pain points
  • ×Promo planning still runs off last year's playbook
  • ×Assortment reviews happen quarterly when they should happen daily
  • ×Price changes chase the market a week behind it
  • ×No visibility into true cannibalization across categories
  • ×Vendor negotiations lack real-time sell-through evidence
How Ward helps
  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

Retailers lose an estimated $300B+ annually to suboptimal assortment and promotional decisions. Source: McKinsey & Company

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.

Your category managers are drowning in spreadsheets. Ward solves this with automated insight cards: Insight cards flag promo cannibalization the day it happens. Assortment gaps and whitespace opportunities surface automatically. Price elasticity shifts detected before margin erosion compounds.

Ward delivers daily insight cards covering Fill rate, Shrinkage %, Fresh waste %, tailored for Merchandising 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