Furniture · Oracle · CFO

Oracle Retail plus Ward, for a furniture CFO

Ward reads straight from Oracle Retail and hands you furniture daily cards scoped to finance. Your P&L surprises are born on the store floor.

What a furniture CFO gets from Oracle Retail

Applied to Furniture Manufacturing & Retail, the surface area is 10,000+ SKUs throughout 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.

Your P&L surprises are born on the store floor. Ward delivers insight cards scoped to finance decision-making.

Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.

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 Oracle data, live product demo.

What Ward delivers

  • GMROI tracking by category with weekly insight cards
  • Inventory carrying cost alerts when capital efficiency drops
  • Working capital optimization recommendations based on turnover trends
  • SSS decomposition into traffic, conversion, and basket components
  • Store-level unit economics cards for capex prioritization

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.

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

Coverage is store by store, category by category. Ward tracks inventory carrying cost, order-to-delivery cycle, gross margin by channel throughout 10,000+ SKUs and compares each store against its own baseline, not against the chain. That is the difference between knowing the footprint is fine and knowing which seven locations are not.

Why this combination
is its own problem.

A CFO in furniture retail owns numbers that move faster than the reporting cycle that covers them. Inventory carrying cost, order-to-delivery cycle, gross margin by channel shift store by store, on a daily cycle. A monthly pack cannot represent that. Your P&L surprises are born on the store floor.

What the first 90 days
actually look like.

  1. 01

    Week 1: read-only connection

    Ward reads from Oracle Retail with read-only credentials and begins ingesting sales audit and inventory positions. No config changes on your side. First findings arrive within 48 hours.

  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 insight cards are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: operating rhythm

    Cards 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 Oracle Retail

Ward integrates with Oracle Retail Merchandising (RMFCS), Oracle Retail Demand Forecasting, and Oracle Retail Analytics. Full stack visibility.

Setup: Ward reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments.

Data Ward reads from Oracle

Sales audit
Inventory positions
Allocation
Replenishment
Demand forecasts
Price management

Impact metrics with Oracle

Fill Rate
Allocation gaps caught
Replenishment outputs checked against actual shelf conditions per store.
Demand Forecast Accuracy
Accuracy gap closed
External signals enrich Oracle forecasts where they drift.
Markdown Waste
Slow movers caught early
Triggers shallower markdowns before inventory ages out.
Inventory Carrying Cost
Overstock freed up
Demand-aligned inventory releases locked working capital.

Data lake enrichment

Ward enriches Oracle data with: Sales audit data, Weather & events, Competitor pricing, Demographic data, Supplier scorecards

Your P&L surprises are born on the store floor.

Pain points
  • ×Margin erosion only surfaces at month-end close
  • ×Inventory carrying costs are a black box
  • ×Working capital tied up in slow-moving stock nobody is watching
  • ×Same-store sales comps lack decomposition into actionable drivers
  • ×Capex decisions for store remodels lack unit-economics evidence
How Ward helps
  • GMROI tracking by category with weekly insight cards
  • Inventory carrying cost alerts when capital efficiency drops
  • Working capital optimization recommendations based on turnover trends
  • SSS decomposition into traffic, conversion, and basket components
  • Store-level unit economics cards for capex prioritization

Inventory distortion, overstock and out-of-stock combined, costs retailers $1.77 trillion globally. 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 reads from Oracle Retail via REST APIs or direct database views. Compatible with Oracle Cloud and on-premise deployments. Data points include: Sales audit, Inventory positions, Allocation, Replenishment, Demand forecasts, Price management.

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

Your P&L surprises are born on the store floor. Ward solves this with automated insight cards: GMROI tracking by category with weekly insight cards. Inventory carrying cost alerts when capital efficiency drops. Working capital optimization recommendations based on turnover trends.

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