Furniture stockout from Epicor, briefed to technology
The business wants AI. You sign off on the architecture. Ward picks up furniture stockout movement in your Epicor data while it is still fixable, with the driver and a recommended action attached.
How a furniture Head of IT runs stockout on Epicor
The business wants AI. You sign off on the architecture. Ward writes the finding at the altitude a Head of IT works at.
Stockout Prediction. Ward detects SKUs trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice.
Furniture Manufacturing & Retail changes the scale of the problem: 10,000+ SKUs, every one of your 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.
How it runs. Ward analyzes sell-through velocity, current inventory levels, lead times, and supplier reliability to predict stockouts 24-72 hours before they occur.
Setup: Ward connects via Epicor REST API. Compatible with Epicor Prophet 21 and Epicor Eclipse.
What you get
- Automated replenishment recommendations
- Supplier-aware lead time modeling
- Priority ranking by revenue impact
- Reduce lost sales by catching gaps early
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 Stockout matters for Furniture retail
In furniture, a stockout is not a one-day gap, it is an 8 to 16 week hole. Replenishment often means a new container from an overseas plant, so the reorder decision has to fire weeks before the shelf runs dry. Ward models sell-through against inbound container schedules and supplier lead-time variance, flagging the reorder point early enough that a hero SKU never goes dark through a full production cycle.
What Ward has eyes on.
Ward monitors 10,000+ SKUs throughout 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 pulls from 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.
Know before the shelf empties. 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 sell-through velocity by SKU and configuration, inbound container ETAs, supplier lead-time variance by plant, and on-hand plus in-transit position. Long lead times mean the cost of a late reorder is measured in lost months, not lost days, so Ward weights revenue-at-risk across the full replenishment window.
Why this combination
is its own problem.
A Head of IT does not need the stockout model explained. They need to know which stores moved, why, and what to do by end of day. Ward writes the finding at that altitude.
- 01 Configurable SKUs are forecast at the parent level, hiding that one fabric or finish is driving the demand spike while the others sit.
- 02 Reorder points are set on domestic lead-time assumptions when the real lead time is a 14-week overseas container, so the trigger fires far too late.
Benchmarks. Furniture lead times commonly run 8 to 16 weeks for imported goods. A stockout on a top-20 floor SKU typically costs 4 to 8% of category revenue for every month it persists, because customers who cannot buy the piece they came for rarely substitute and often leave the sale entirely.
What the first 90 days
actually look like.
-
01
Week 1: connect
Read-only credentials to Epicor. Ward ingests sales orders, inventory, purchase orders and starts building baselines. First daily cards land inside 48 hours, before baselines are stable, so you can see the shape of the output early.
-
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.
-
03
Weeks 4 to 12: operating rhythm
Findings arrive daily 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
The business wants AI. You sign off on the architecture.
- ×Business sponsor already chose the vendor. You inherit the security review
- ×Every AI vendor wants write access and a copy of the production data
- ×Model lock-in means rewriting the stack when GPT or Claude moves again
- ×Audit trail is an afterthought. Compliance has nothing to pull on
- ×Data lake project keeps getting bumped for the next thing the business wants
- ✓Federated query: data stays in your warehouse. No copies, no shadow lake
- ✓Read-only credentials. Cedar policies enforce least-privilege per agent
- ✓LLM-agnostic. Anthropic, OpenAI, Gemini, Ollama. Bring your own keys
- ✓Every query, every model, every source logged. SIEM-ready audit output
- ✓VPC peering, PrivateLink, SOC 2 II. Your security review is short
74% of enterprise AI projects stall before production. Integration debt and security review are the top two reasons. Source: Gartner
Furniture KPI impact
Frequently asked questions
Ward detects SKUs trending toward zero-on-hand and alerts your team with replenishment recommendations before customers notice. 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 analyzes sell-through velocity, current inventory levels, lead times, and supplier reliability to predict stockouts 24-72 hours before they occur.
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.
The business wants AI. You sign off on the architecture. Ward solves this with automated insight cards: Federated query: data stays in your warehouse. No copies, no shadow lake. Read-only credentials. Cedar policies enforce least-privilege per agent. LLM-agnostic. Anthropic, OpenAI, Gemini, Ollama. Bring your own keys.
Ward delivers daily insight cards covering Inventory carrying cost, Order-to-delivery cycle, Gross margin by channel, tailored for Technology decision-making. Each card includes what changed, why it matters, and what to do next.
Ward tracks sell-through velocity by SKU and configuration, inbound container ETAs, supplier lead-time variance by plant, and on-hand plus in-transit position. Long lead times mean the cost of a late reorder is measured in lost months, not lost days, so Ward weights revenue-at-risk across the full replenishment window.
A best-selling sectional in one fabric colorway starts selling 40% above forecast across the showroom network after a catalog feature. On-hand covers six weeks, but the factory lead time is 14 weeks and the next container is not booked. Ward issues a stockout prediction card the moment velocity clears threshold, with the recommended reorder quantity and the booking deadline to avoid a two-month floor gap. The buyer places the PO with ten weeks of runway instead of finding out at the empty slot.
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
See what Furniture stockout problems Ward catches.
Root causes, not just alerts. See it on your data.
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