Furniture · Epicor · VP Supply Chain

Epicor plus Ward, for a furniture VP Supply Chain

A furniture VP Supply Chain running Epicor gets inventory carrying cost, order-to-delivery cycle, gross margin by channel tracks on a daily cycle, with the driver attached.

Ward and Epicor for Furniture supply chain

Applied to Furniture Manufacturing & Retail, the surface area is 10,000+ SKUs over locations. ERP-locked production data, long lead times, and margin erosion you don't see until quarter-end. Ward connects your internal systems and surfaces what matters.

You find out about stockouts after customers do. Ward sends findings scoped to supply chain decision-making.

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

app.getward.ai Live demo
Acme Furniture @Finance: Margin Analyst claude-sonnet default
A

Chat

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

Why is upholstery margin down four points this quarter?
You · 9:42 AM
Schema Scout · routed to Margin Agent

I pulled upholstery cost of goods by BOM line against the last price file. Three quarters of the drop is material and freight, not discounting.

SignalFinding
bom_cost_actualsFoam and frame stock +9.2% since the March price file, never carried to list
freight.inboundInbound container cost +$412 per unit-equivalent on the Vietnam lane
channel.mixWholesale share up 6pp, and wholesale runs 11pp under DTC margin

Recommend: reprice the six affected SKUs at the next list cycle, quote the alternate foam vendor, and hold wholesale allocation flat until list catches up.

11 parallel queries 4 sources cited confidence 0.90
Show me the SKU-level margin waterfall.
You · 9:43 AM
Margin Agent · building waterfall
Querying bom_cost_actuals
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
$19.8M
+1.8% WoW
Gross margin, upholstery
42.1%
−4.1pp
Order-to-delivery, custom
14.2 wks
+1.9 wks
Aged inventory, 180+ days
$6.4M
+$1.2M
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
epicor_production_stage_logimport2m ago
epicor_bom_cost_actualsimport2m ago
sap_inventory_snapshotimport14m ago
netsuite_sales_ordersimport1h ago
retail_showroom_posimport1h ago
retail_freight_inboundimport1h ago
retail_dealer_ordersimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
finance-read-defaultpermitModel::*
sourcing-read-bompermitModel::"bom_cost_actuals"
dealer-blockedforbidModel::"bom_*"
plant-read-productionpermitModel::"production_stage_log"
for Furniture on Epicor data, live product demo.

What Ward delivers

  • Stockout prediction cards arrive 24-72 hours before empty shelves
  • Supplier fill rate tracking with automatic escalation
  • Dynamic safety stock recommendations based on current demand signals
  • Weather, event, and macro-driven demand adjustments
  • Replenishment exceptions auto-prioritized by revenue impact

Metrics Ward monitors

Inventory carrying cost
Order-to-delivery cycle
Gross margin by channel
Raw material cost variance
Custom order cycle time

Furniture challenges Ward solves

  • Disconnected ERP, warehouse, and POS systems
  • Custom/configurable SKUs that break standard reporting
  • 8–16 week lead times with no demand signal
  • Raw material cost drift invisible until P&L close
  • Channel mix shift between showroom, e-commerce, and wholesale

What Ward has eyes on.

Ward watches 10,000+ SKUs over your locations, at the store-category level rather than the chain roll-up. The metrics under watch include inventory carrying cost, order-to-delivery cycle, gross margin by channel. A roll-up hides a single-store problem inside a healthy average, which is how disconnected ERP, warehouse, and POS systems stays invisible for a quarter.

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.

Why this combination
is its own problem.

A VP Supply Chain rarely logs into Epicor. They read what someone else pulled out of it, two days later. Ward removes the two days and the someone else.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward sits on top of Epicor with read-only credentials and begins ingesting sales orders and inventory. No config changes on your side. First findings arrive in two days.

  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 returns insight cards every morning, each with the cause 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 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

You find out about stockouts after customers do.

Pain points
  • ×Demand forecasts are off by 15-25% and nobody catches it until the shelf is empty
  • ×Supplier fill rate problems announce themselves at the receiving dock
  • ×Safety stock levels get set once a year and left alone
  • ×No early warning system for supply chain disruptions
  • ×Replenishment exceptions require manual triage every morning
How Ward helps
  • Stockout prediction cards arrive 24-72 hours before empty shelves
  • Supplier fill rate tracking with automatic escalation
  • Dynamic safety stock recommendations based on current demand signals
  • Weather, event, and macro-driven demand adjustments
  • Replenishment exceptions auto-prioritized by revenue impact

Stockouts cost retailers $1.14 trillion in missed sales globally each year. Source: IHL Group

Furniture KPI impact

Inventory Carrying Cost
Aged stock flagged
Slow-moving SKUs identified before carrying costs compound.
Order-to-Delivery Cycle
Bottleneck visibility
Cycle time tracked by production stage against baselines.
Gross Margin
Real-time by channel
Material cost drift detected the week it starts.
Stockout Frequency
Advance warning
POS and e-commerce signals feed back into production.

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.

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

You find out about stockouts after customers do. Ward solves this with automated insight cards: Stockout prediction cards arrive 24-72 hours before empty shelves. Supplier fill rate tracking with automatic escalation. Dynamic safety stock recommendations based on current demand signals.

Ward delivers daily insight cards covering Inventory carrying cost, Order-to-delivery cycle, Gross margin by channel, tailored for Supply Chain 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 Furniture 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