Home · Shrinkage · Epicor · Head of Procurement

Shrinkage Detection: Home retail, Epicor data, Procurement decisions

Ward reads sales orders, inventory, purchase orders from Epicor, scans continuously shrinkage throughout 50,000+ home SKUs, and returns the procurement read on a daily cycle.

How a home Head of Procurement runs shrinkage on Epicor

A Home Improvement operator is tracking 50,000+ SKUs over stores. Project-based purchasing, long-tail SKUs, and seasonal volatility. Ward manages the complexity of 50,000+ SKU environments with ease.

Merchandising wants Ward. You sign the contract. Ward filters to what a Head of Procurement can act on and drops the rest.

Shrinkage Detection, in one sentence. Ward identifies abnormal inventory loss patterns and distinguishes between theft, damage, spoilage, and administrative error.

The mechanism. Ward compares expected inventory against actual counts, segments loss by cause category, and flags store-level anomalies against your estate baseline.

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

Capabilities

  • Cause-level shrinkage attribution
  • Store-vs-estate benchmarking
  • Receiving dock anomaly detection
  • Pattern recognition across time
app.getward.ai Live demo
Acme Home @Merchandising: Seasonal Analyst claude-sonnet default
A

Chat

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

Why did the spring mulch pre-build miss in the Southeast?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

I pulled the spring pre-build against the last three seasons and the weather signal for the 22 Southeast stores.

SignalFinding
seasonal_prebuildMulch on-hand hit 61% of plan the week temps broke 70°F
dc_pushDC push started 9 days after the first-warm-week trigger, LY it was 2
attach.projectSoil and edging attach fell 18% at stores that gapped on mulch

Recommend: tie the push trigger to the 10-day forecast instead of the calendar week, pre-position two truckloads at the 8 stores that gapped, and re-set the attach endcap.

9 parallel queries 4 sources cited confidence 0.88
Which stores get the pre-position first?
You · 9:43 AM
Supply Chain Agent · ranking stores
Querying seasonal_prebuild
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. plan
$57.3M
+2.9% WoW
Gross margin, seasonal
31.2%
−2.4pp
Mulch on-hand vs plan
61.4%
−18pp
Special order cycle time
11.6 d
+3.1 days
Revenue vs. plan 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
epicor_pos_transactionsimport2m ago
epicor_special_ordersimport2m ago
netsuite_inventory_snapshotimport14m ago
retail_seasonal_prebuildimport1h ago
retail_sku_velocityimport1h ago
retail_pro_account_salesimport1h ago
retail_weather_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::*
pro-team-read-accountspermitModel::"pro_account_sales"
vendor-blockedforbidModel::"labor_*"
supply-read-orderspermitModel::"special_orders"
Shrinkage for Home on Epicor data, live product demo.

Why Shrinkage matters for Home retail

Small hardware has the highest per-unit theft rates but lowest dollar impact; power tools have lower frequency but massive loss per incident. Ward segments shrinkage by value tier and department so loss prevention allocates resources where the dollar impact is highest, not just where the unit count is.

What Ward has eyes on.

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

Coverage is store by store, category by category. Ward monitors project basket value, seasonal accuracy, long-tail turn throughout 50,000+ 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.

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.

At the metric level. Ward segments by value tier, tracks geographic clustering for ORC detection, monitors receiving accuracy on bulk/pallet deliveries, and measures POS velocity-to-inventory count gaps.

Signals · POS at SKU-store-shift, receiving logs and PO variance, store geocodes for ORC clustering, employee schedules, and category-value-tier overlays.

Why this combination
is its own problem.

Epicor is the system of record for most home operators of your size, which means the readings Ward needs are already there. The gap is not data collection. It is that nobody has time to read sales orders and inventory every morning across every store.

  • 01 High-volume small hardware shrink dominates incident counts and pulls LP attention toward unit-level fixes; the bigger dollar exposure is in low-frequency power tool theft.
  • 02 ORC patterns concentrate geographically; chain-wide LP allocation misses the cluster signal that directs investigative focus.

Benchmarks. Home improvement shrink runs 1.4-2.6% of sales, with power tools, copper, and high-value building materials accounting for 30-50% of total dollar shrink despite small unit volume. ORC events typically affect a tight geographic cluster of 5-15 stores.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward connects to Epicor with read-only credentials and begins ingesting sales orders and inventory. No config changes on your side. First findings 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: steady state

    Ward hands you cards every morning, each with the cause and a recommended action. Volume settles at a level a single person can read over coffee. The measure of success is not how many insight 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

Merchandising wants Ward. You sign the contract.

Pain points
  • ×Business sponsor saw the demo. You have a week to vet a vendor you didn't pick
  • ×AI vendors price by seats and tokens. Total cost is unknowable until invoice three
  • ×Multi-year commits with auto-renew. No exit if the pilot stalls
  • ×Renewals come back 30% higher, with no room to push back and no benchmark to cite
  • ×Security and DPA reviews start after the team has already committed
How Ward helps
  • MSA, DPA, SOC 2 Type II underway, and architecture review available before signature
  • Month-to-month contracts. No multi-year lock-in. No auto-renew traps
  • Transparent pricing set by scope and store count
  • 14-day insight guarantee. If Ward doesn't deliver, month two is on us
  • AI strategy, orchestration and reporting-layer work in enterprise grocery at nine-figure revenue. Reference calls available before signature

Enterprise SaaS spend grew 18% YoY. 53% of subscriptions are underused or duplicative. Source: Gartner

Home KPI impact

Seasonal Accuracy
Weather + event driven
Pre-positioning adjusted for peak season signals.
Long-Tail Turn
Dead weight separated
Which tail SKUs serve project needs vs sit idle.
Project Basket Value
Cross-sell surfaced
Project purchasing patterns drive attachment.
Inventory Carrying Cost
Capital freed
Demand forecasting reduces slow-moving overstock.

Frequently asked questions

Ward identifies abnormal inventory loss patterns and distinguishes between theft, damage, spoilage, and administrative error. For Home retail specifically, Ward monitors 50,000+ SKUs across your stores and delivers automated insight cards with root cause analysis and recommended actions.

Ward tracks Project basket value, Seasonal accuracy, Long-tail turn, Pro customer share, Attachment rate at the store-category level. Ward compares expected inventory against actual counts, segments loss by cause category, and flags store-level anomalies against your estate baseline.

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.

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

Merchandising wants Ward. You sign the contract. Ward solves this with automated insight cards: MSA, DPA, SOC 2 Type II underway, and architecture review available before signature. Month-to-month contracts. No multi-year lock-in. No auto-renew traps. Transparent pricing set by scope and store count.

Ward delivers daily insight cards covering Project basket value, Seasonal accuracy, Long-tail turn, tailored for Procurement decision-making. Each card includes what changed, why it matters, and what to do next.

Ward segments by value tier, tracks geographic clustering for ORC detection, monitors receiving accuracy on bulk/pallet deliveries, and measures POS velocity-to-inventory count gaps.

Ward flags elevated power tool shrinkage at a geographic cluster of stores, concentrated during weekday afternoons, a pattern consistent with organized retail crime. Ward recommends immediate spider-wrap enforcement and receipt-checking at affected locations. LP investigation confirms a theft ring, and targeted intervention brings shrinkage back toward estate averages within weeks.

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 Home 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