Stockout · RELEX · Head of LP

RELEX plus Ward: stockout for a Head of LP

Know before the shelf empties. Ward runs it off RELEX, scoped to what a Head of LP owns.

Stockout Prediction on RELEX, for loss prevention

Shrinkage costs you more than you think. Ward finds out where. Ward raises the indicators that change a loss prevention decision.

Here is stockout prediction in plain terms. Ward detects SKUs trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice.

The mechanism. 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 RELEX data via API. Monitors forecast accuracy and flags exceptions before they compound.

What you get

  • Priority ranking by revenue impact
  • Reduce lost sales by catching gaps early
  • Automated replenishment recommendations
  • Supplier-aware lead time modeling
app.getward.ai Live demo
Acme Retail @Merchandising: VP 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 %
24.1%
−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
retail_inventory_weeklyimport1h ago
retail_google_ads_dailyimport1h ago
retail_meta_ads_dailyimport1h ago
retail_ga4_website_dailyimport1h 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::*
finance-read-shrinkagepermitModel::"inventory_shrinkage"
vendor-blockedforbidModel::"labor_*"
region-west-onlypermitTenant::"acme"
Stockout on RELEX data, live product demo.

Why this combination
is its own problem.

RELEX Solutions was built for transactions, not for loss prevention decisions. The data is right there and it is in the wrong shape. Ward reads straight from demand forecasts and space plans and rewrites them as a decision.

What Ward has eyes on.

The stockout model runs on a daily cycle, not on a reporting calendar. It picks up the pattern, explains root cause, and attaches the next step before the number reaches a review deck.

Ward pulls from demand forecasts, space plans, workforce forecasts from RELEX Solutions on a read-only connection. Nothing is written back, and your Supply Chain configuration does not change. RELEX stays the system of record.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward connects to RELEX Solutions with read-only credentials and begins ingesting demand forecasts and space plans. No config changes on your side. First daily cards arrive inside the first 48 hours.

  2. 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.

  3. 03

    Weeks 4 to 12: operating rhythm

    Daily 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 RELEX Solutions

Ward integrates with RELEX for unified retail planning. Ward monitors RELEX forecasts against actuals and surfaces planning exceptions as insight cards.

Setup: Ward reads RELEX data via API. Monitors forecast accuracy and flags exceptions before they compound.

Data Ward reads from RELEX

Demand forecasts
Space plans
Workforce forecasts
Promotion plans
Replenishment orders

Impact metrics with RELEX

Forecast Accuracy
Drift flagged per store
Accuracy decay caught before it compounds across locations.
Space Productivity
Planogram gaps exposed
Space plans checked against actual sell-through per fixture.
Replenishment Efficiency
Manual triage reduced
Exceptions ranked by revenue impact and urgency.
Fresh Waste
Perishable ordering tightened
Hyperlocal weather and events sharpen fresh item forecasts.

Data lake enrichment

Ward enriches RELEX data with: RELEX forecasts, POS actuals, Weather & events, Demographic data, Supplier performance

Shrinkage costs you more than you think. Ward finds out where.

Pain points
  • ×Shrinkage lands as a year-end surprise
  • ×Cannot distinguish theft from spoilage from admin error
  • ×High-shrinkage stores only identified during audits
  • ×No correlation between operational changes and loss patterns
  • ×Exception-based reporting misses slow-bleed patterns
How Ward helps
  • Store-level shrinkage tracking with cause attribution
  • Anomaly detection flags stores deviating from estate average
  • Receiving dock discrepancy patterns identified automatically
  • Correlation analysis links operational changes to loss shifts
  • Trend analysis catches slow-bleed patterns audits miss

US retail shrinkage hit $112.1 billion in 2022. Up 19.4% year over year. Source: National Retail Federation

Frequently asked questions

Ward reads RELEX data via API. Monitors forecast accuracy and flags exceptions before they compound. Data points include: Demand forecasts, Space plans, Workforce forecasts, Promotion plans, Replenishment orders.

Shrinkage costs you more than you think. Ward finds out where. Ward solves this with automated insight cards: Store-level shrinkage tracking with cause attribution. Anomaly detection flags stores deviating from estate average. Receiving dock discrepancy patterns identified automatically.

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 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.

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