Shrinkage · Epicor · CFO

Epicor plus Ward: shrinkage for a CFO

Find the leak before it drains you. Ward runs it off Epicor, scoped to what a CFO owns.

How a CFO runs shrinkage off Epicor

Here is shrinkage detection in plain terms. Ward identifies abnormal inventory loss patterns and distinguishes between theft, damage, spoilage, and administrative error.

Your P&L surprises are born on the store floor. Ward filters to what a CFO can act on and drops the rest.

What Ward does with that: Ward compares expected inventory against actual counts, segments loss by cause category, and flags store-level anomalies against your estate baseline.

Getting the data in. Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.

The short list

  • Store-vs-estate benchmarking
  • Receiving dock anomaly detection
  • Pattern recognition across time
  • Cause-level shrinkage attribution
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"
Shrinkage on Epicor data, live product demo.

Why this combination
is its own problem.

Shrinkage Detection produces a lot of output that is technically correct and operationally useless to finance. Ward filters on whether the finding changes a decision a CFO can actually make.

What Ward has eyes on.

Ward reads sales orders, inventory, purchase orders from Epicor on a read-only connection. Nothing is written back, and your ERP configuration does not change. Epicor stays the system of record.

The shrinkage model runs daily, not on a reporting calendar. It picks up the pattern, traces the driver, and attaches a recommended action before the number reaches a review deck.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward plugs into Epicor with read-only credentials and begins ingesting sales orders and inventory. No config changes on your side. First insight cards arrive inside the first 48 hours.

  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 daily cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward delivers daily cards daily, each with what caused it and what to do about it. Volume settles at a level a single person can read over coffee. The measure of success is not how many cards arrive, it is how many get acted on.

How Ward connects to Epicor

Ward integrates with Epicor for home improvement, furniture, and building supply retailers. Inventory, purchasing, production, and sales data power insight cards.

Setup: Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.

Data Ward reads from Epicor

Sales orders
Inventory
Purchase orders
Customer accounts
Pricing tiers
Vendor performance

Impact metrics with Epicor

Seasonal Accuracy
Pre-buy timing sharpened
Weather and event signals calibrate seasonal positioning.
Project Basket Value
Cross-sell patterns found
Project purchasing sequences reveal attachment opportunities.
Vendor Fill Rate
Degradation caught early
Fill rate drops flagged before shelf impact materializes.
Inventory Carrying Cost
Slow-movers identified
Demand-aligned ordering frees capital tied in dead stock.

Data lake enrichment

Ward enriches Epicor data with: Sales orders, Weather & events, Contractor/Pro data, Competitor pricing, Vendor scorecards

Your P&L surprises are born on the store floor.

Pain points
  • ×Margin erosion only surfaces at month-end close
  • ×Inventory carrying costs are a black box
  • ×Working capital tied up in slow-moving stock nobody is watching
  • ×Same-store sales comps lack decomposition into actionable drivers
  • ×Capex decisions for store remodels lack unit-economics evidence
How Ward helps
  • GMROI tracking by category with weekly insight cards
  • Inventory carrying cost alerts when capital efficiency drops
  • Working capital optimization recommendations based on turnover trends
  • SSS decomposition into traffic, conversion, and basket components
  • Store-level unit economics cards for capex prioritization

Inventory distortion, overstock and out-of-stock combined, costs retailers $1.77 trillion globally. Source: IHL Group

Frequently asked questions

Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse. Data points include: Sales orders, Inventory, Purchase orders, Customer accounts, Pricing tiers, Vendor performance.

Your P&L surprises are born on the store floor. Ward solves this with automated insight cards: GMROI tracking by category with weekly insight cards. Inventory carrying cost alerts when capital efficiency drops. Working capital optimization recommendations based on turnover trends.

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 shrinkage 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