Furniture · SAP · CFO

SAP Retail plus Ward, for a furniture CFO

A furniture CFO running SAP gets inventory carrying cost, order-to-delivery cycle, gross margin by channel watches daily, with the driver attached.

Ward and SAP for Furniture finance

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

In a Furniture Manufacturing & Retail estate the job 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.

How the connection works. Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule.

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 SAP 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

Why this combination
is its own problem.

Running Ward on SAP in a furniture estate skips the usual first step. There is no ingestion project, because SAP Retail already holds POS transactions, inventory positions, purchase orders. Ward ingests what is there.

What Ward has eyes on.

The connection to SAP Retail is read-only and runs on your schedule. Ward reads POS transactions, inventory positions, and the rest of the feed, then combines it with external context your ERP does not carry: weather, local events, competitor pricing.

Every one of your locations gets its own baseline. Ward watches inventory carrying cost, order-to-delivery cycle, gross margin by channel against it and pulls forward only the deviations that hold up. The two that show up most in furniture retail are disconnected ERP, warehouse, and POS systems and custom/configurable SKUs that break standard reporting, and both are baseline problems before they are P&L problems.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to SAP Retail. Ward ingests POS transactions, inventory positions, purchase orders and starts building baselines. First 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 returns findings each day, each with the cause and a recommended action. 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 SAP Retail

Ward connects to SAP Retail (S/4HANA, ECC, CAR) via standard BAPIs and IDocs. Transaction data, inventory positions, and master data flow into Ward without custom development.

Setup: Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule.

Data Ward reads from SAP

POS transactions
Inventory positions
Purchase orders
Material master
Vendor master
Promotion calendar

Impact metrics with SAP

Replenishment Accuracy
Gaps flagged early
Inventory positions matched to POS velocity before shelf impact.
Shrinkage
Anomalies surfaced continuously
Transaction-level detection catches what periodic audits miss.
Forecast Accuracy
External signals layered
Weather, events, and competitor data sharpen SAP demand signals.
Promo ROI
True lift isolated
Sell-through data exposes cannibalization and halo effects.

Data lake enrichment

Ward enriches SAP data with: POS transactions, Weather & events, Competitor pricing, Loyalty & CRM, Supplier fill rates

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 SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule. Data points include: POS transactions, Inventory positions, Purchase orders, Material master, Vendor master, Promotion calendar.

Yes. Ward reads SAP 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