Shrinkage Detection for Head of Procurement, read from SAP Retail
Find the leak before it drains you. Ward runs it off SAP, scoped to what a Head of Procurement owns.
Shrinkage Detection on SAP, for procurement
Merchandising wants Ward. You sign the contract. Ward returns cards scoped to procurement decision-making.
Shrinkage Detection is a finding type Ward runs continuously. Ward identifies abnormal inventory loss patterns and distinguishes between theft, damage, spoilage, and administrative error.
What Ward does with that: Ward compares expected inventory against actual counts, segments loss by cause category, and flags store-level anomalies against your estate baseline.
Getting the data in. Ward reads from SAP via RFC/BAPI or OData APIs. No changes to your SAP configuration. Read-only access. Data syncs on your schedule.
Capabilities
- Cause-level shrinkage attribution
- Store-vs-estate benchmarking
- Receiving dock anomaly detection
- Pattern recognition across time
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.
| Signal | Finding |
|---|---|
labor_efficiency | Rev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak |
inventory.fresh | Fresh fill 83%, backroom replenishment lag at 2–4p |
promo.lift | BOGO crackers cannibalized Brand Y by 28%, net category +6% |
Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.
labor_scheduling…
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 |
|---|---|---|
sap_pos_transactions | import | 2m ago |
sap_inventory_shrinkage | import | 2m ago |
sap_labor_scheduling | import | 14m ago |
retail_inventory_weekly | import | 1h ago |
retail_google_ads_daily | import | 1h ago |
retail_meta_ads_daily | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
finance-read-shrinkage | permit | Model::"inventory_shrinkage" |
vendor-blocked | forbid | Model::"labor_*" |
region-west-only | permit | Tenant::"acme" |
What Ward has eyes on.
Find the leak before it drains you. 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 reads straight from SAP rather than replacing it. POS transactions, inventory positions, purchase orders come across on a read-only connection, get enriched with contextual data, and come back as daily cards. Your ERP is untouched.
Why this combination
is its own problem.
Shrinkage Detection produces a lot of output that is technically correct and operationally useless to procurement. Ward filters on whether the finding changes a decision a Head of Procurement can actually make.
What the first 90 days
actually look like.
-
01
Week 1: read-only connection
Ward reads from SAP Retail with read-only credentials and begins ingesting POS transactions and inventory positions. No config changes on your side. First insight cards arrive inside the first 48 hours.
-
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: steady state
Ward returns insight cards daily, each with root cause and the next step. Volume settles at a level a single person can read over coffee. The measure of success is not how many cards 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
Impact metrics with SAP
Data lake enrichment
Ward enriches SAP data with: POS transactions, Weather & events, Competitor pricing, Loyalty & CRM, Supplier fill rates
Merchandising wants Ward. You sign the contract.
- ×Business sponsor saw the demo. You have a week to vet a vendor you didn't pick
- ×AI vendors price by seats and tokens. Total cost is unknowable until invoice three
- ×Multi-year commits with auto-renew. No exit if the pilot stalls
- ×Renewals come back 30% higher, with no room to push back and no benchmark to cite
- ×Security and DPA reviews start after the team has already committed
- ✓MSA, DPA, SOC 2 Type II underway, and architecture review available before signature
- ✓Month-to-month contracts. No multi-year lock-in. No auto-renew traps
- ✓Transparent pricing set by scope and store count
- ✓14-day insight guarantee. If Ward doesn't deliver, month two is on us
- ✓AI strategy, orchestration and reporting-layer work in enterprise grocery at nine-figure revenue. Reference calls available before signature
Enterprise SaaS spend grew 18% YoY. 53% of subscriptions are underused or duplicative. Source: Gartner
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.
Merchandising wants Ward. You sign the contract. Ward solves this with automated insight cards: MSA, DPA, SOC 2 Type II underway, and architecture review available before signature. Month-to-month contracts. No multi-year lock-in. No auto-renew traps. Transparent pricing set by scope and store count.
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 shrinkage 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.