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Head of E-Com: home fill rate, read from Epicor

A home Head of E-Com on Epicor should not be hunting for fill rate problems. Ward brings up them every morning.

Fill Rate Monitoring for Home on Epicor, scoped to e-commerce

Your online and offline data live in different worlds. Ward writes the finding at the altitude a Head of E-Com works at.

Here is fill rate monitoring in plain terms. Ward monitors on-shelf availability across your entire estate and flags stores or categories dropping below threshold.

In a Home Improvement estate the job is 50,000+ SKUs across stores. Project-based purchasing, long-tail SKUs, and seasonal volatility. Ward manages the complexity of 50,000+ SKU environments with ease.

What Ward does with that: Ward tracks expected vs actual on-shelf availability at the store-category level and escalates when fill rate drops below configurable thresholds.

How the connection works. Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.

The short list

  • Estate-wide fill rate dashboard
  • Threshold-based alerting
  • Store-vs-estate benchmarking
  • Category-level drill-down
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"
Fill Rate for Home on Epicor data, live product demo.

Why Fill Rate matters for Home retail

A store can report 96% fill rate while missing the one fastener that completes every deck project basket. Ward monitors fill rate through a project-basket lens, flagging when project-critical items drop below threshold even if aggregate availability looks healthy.

What Ward has eyes on.

Ward tracks 50,000+ SKUs over your stores, at the store-category level rather than the chain roll-up. The metrics under watch include project basket value, seasonal accuracy, long-tail turn. A roll-up hides a single-store problem inside a healthy average, which is how project basket identification stays invisible for a quarter.

The connection to Epicor is read-only and runs on your schedule. Ward pulls from sales orders, inventory, and the rest of the feed, then stitches together it with external context your ERP does not carry: weather, local events, competitor pricing.

Every empty shelf is a lost sale. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.

At the metric level. Ward tracks project-basket completion rates, department availability with project-dependency weighting, seasonal merchandise positioning timing, and Pro customer order-fill rates, since Pros expect near-perfect availability and defect immediately on gaps.

Signals · POS at SKU-store-day with basket linkage, current inventory positions, Pro account order history, planogram and endcap positions, and project basket affinity graph.

Why this combination
is its own problem.

Most fill rate projects stall at data access. This one does not, because Epicor already exposes sales orders, inventory, purchase orders through an API Ward reads directly.

  • 01 Pro customer order fill rate is benchmarked against estate-wide DIY fill, hiding the much steeper Pro defection curve when a flagged SKU goes out of stock.
  • 02 Endcap and seasonal positioning is tracked separately from fill rate, but the customer experience is shaped by both, a fully-stocked product hidden in a non-seasonal aisle still functions like a stockout.

Benchmarks. Home improvement project-basket completion: healthy chains run 88-94% on the top-100 project baskets; below 80% on a top basket cuts category revenue 3-7% over the affected weeks. Pro customer fill rate matters disproportionately, Pros typically defect after 2-3 stockouts on flagged SKUs.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Epicor. Ward reads straight from sales orders, inventory, purchase orders 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: 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 daily cards every morning, each with the driver 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 online and offline data live in different worlds.

Pain points
  • ×Nobody can see one inventory position across every channel
  • ×Online promo performance is measured separately from in-store
  • ×Customer behavior data is siloed by channel
  • ×BOPIS/BORIS operational complexity is growing unchecked
  • ×Digital marketing attribution stops at the click
How Ward helps
  • Unified insight cards across online and in-store channels
  • Cross-channel promo effectiveness with true attribution
  • Customer journey tracking across digital and physical touchpoints
  • BOPIS fulfillment performance monitoring with exception cards
  • Full-funnel marketing attribution to in-store conversion

Retailers with unified omnichannel data see 30% higher lifetime value per customer. Source: Harvard Business Review

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 monitors on-shelf availability across your entire estate and flags stores or categories dropping below threshold. 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 tracks expected vs actual on-shelf availability at the store-category level and escalates when fill rate drops below configurable thresholds.

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.

Your online and offline data live in different worlds. Ward solves this with automated insight cards: Unified insight cards across online and in-store channels. Cross-channel promo effectiveness with true attribution. Customer journey tracking across digital and physical touchpoints.

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

Ward tracks project-basket completion rates, department availability with project-dependency weighting, seasonal merchandise positioning timing, and Pro customer order-fill rates, since Pros expect near-perfect availability and defect immediately on gaps.

Estate-wide fill rate looks healthy, but Ward's project-basket analysis shows the "deck build" basket has far lower complete-basket availability because a single specialty fastener is out of stock. A standard fill rate report would bury this item among 50,000 others. Ward surfaces it through basket completion analysis, and the supply chain team expedites the item to restore project-level availability within days.

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 fill rate 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.

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