Price Optimization: Furniture retail, Epicor data, Supply Chain decisions
Ward ingests sales orders, inventory, purchase orders from Epicor, monitors pricing over 10,000+ furniture SKUs, and returns the supply chain read daily.
The full picture: furniture pricing, Epicor data, Supply Chain decisions
Price Optimization, in one sentence. Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume.
Applied to Furniture Manufacturing & Retail, the surface area is 10,000+ SKUs across 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 writes the finding at the altitude a VP Supply Chain works at.
Under the hood. Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.
How the connection works. Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.
The short list
- Margin-volume tradeoff modeling
- Real-time elasticity measurement
- Category-level price sensitivity
- Competitive price monitoring
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
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.
| Signal | Finding |
|---|---|
bom_cost_actuals | Foam and frame stock +9.2% since the March price file, never carried to list |
freight.inbound | Inbound container cost +$412 per unit-equivalent on the Vietnam lane |
channel.mix | Wholesale 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.
bom_cost_actuals…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
epicor_production_stage_log | import | 2m ago |
epicor_bom_cost_actuals | import | 2m ago |
sap_inventory_snapshot | import | 14m ago |
netsuite_sales_orders | import | 1h ago |
retail_showroom_pos | import | 1h ago |
retail_freight_inbound | import | 1h ago |
retail_dealer_orders | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
finance-read-default | permit | Model::* |
sourcing-read-bom | permit | Model::"bom_cost_actuals" |
dealer-blocked | forbid | Model::"bom_*" |
plant-read-production | permit | Model::"production_stage_log" |
Why Pricing matters for Furniture retail
Furniture margins are thin enough that a quiet move in raw material cost, lumber, foam, steel, or freight, can erase the profit on a hero SKU before anyone reprices. Ward watches landed cost against retail price in real time and flags the units where the margin has compressed past threshold, so pricing reacts to cost drift in weeks instead of finding it at the quarterly P&L.
What Ward has eyes on.
Price on elasticity you can measure. 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.
Ward monitors 10,000+ SKUs across 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 ingests Epicor rather than replacing it. Sales orders, inventory, purchase orders come across on a read-only connection, get enriched with contextual data, and come back as findings. Your ERP is untouched.
At the metric level. Ward measures landed cost per SKU including materials, freight, and duty, tracks gross margin against category floors, and models price elasticity by piece and channel. Because furniture is a considered purchase, many hero items carry low elasticity, so cost-driven price moves often hold volume better than commodity retail assumes.
Why this combination
is its own problem.
Running Ward on Epicor in a furniture fleet skips the usual first step. There is no ingestion project, because Epicor already holds sales orders, inventory, purchase orders. Ward ingests what is there.
- 01 Elasticity is assumed uniform when a hero piece with no close substitute behaves very differently from a commodity accent item.
- 02 Channel margin is blended, hiding that a wholesale or marketplace price is underwater once freight and duty are loaded in.
Benchmarks. Furniture gross margins commonly run 40 to 50% at retail against 3 to 6% net, so a 10-point swing in raw material cost can move a hero SKU below its floor. A 1% pricing improvement across the assortment typically flows through to a disproportionate net-margin gain on this cost structure.
What the first 90 days
actually look like.
-
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 cards arrive inside the first 48 hours.
-
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 findings are directionally right and the thresholds are still moving.
-
03
Weeks 4 to 12: operating rhythm
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 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
Impact metrics with Epicor
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.
- ×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
- ✓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
Frequently asked questions
Ward monitors price elasticity shifts in real time and recommends adjustments that protect margin without sacrificing volume. For Furniture retail specifically, Ward monitors 10,000+ SKUs across your locations and delivers automated insight cards with root cause analysis and recommended actions.
Ward tracks Inventory carrying cost, Order-to-delivery cycle, Gross margin by channel, Raw material cost variance, Custom order cycle time at the store-category level. Ward continuously measures price elasticity by category, tracks competitive pricing signals, and models the margin-volume tradeoff.
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.
Ward measures landed cost per SKU including materials, freight, and duty, tracks gross margin against category floors, and models price elasticity by piece and channel. Because furniture is a considered purchase, many hero items carry low elasticity, so cost-driven price moves often hold volume better than commodity retail assumes.
Foam prices climb 12% over two months. Retail price on a top-selling upholstered chair has not moved, and the piece is still selling well, so nothing looks wrong. Ward tracks landed cost per unit and flags that the chair's gross margin has fallen from 42% to 33%, below the category floor. The card includes the elasticity read: demand on this piece is inelastic enough to absorb a modest price increase without losing volume. Merchandising lifts price 6% and restores the margin.
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.
Related solutions
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Root causes, not just alerts. See it on your data.
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