Promo Effectiveness for Pharmacy on SAP, built for finance
Know which promos actually work. Ward runs it on SAP data across your pharmacy fleet, scoped to finance.
How a pharmacy CFO runs promos on SAP Retail
What promo effectiveness does: Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading.
Pharmacy & Health changes the scale of the problem: 20,000+ SKUs, every one of your pharmacies. Regulated inventory, seasonal demand spikes, and front-of-store optimization. Ward handles the complexity so your pharmacists focus on patients.
Your P&L surprises are born on the store floor. Ward brings up the readings that change a finance decision.
How Ward hands back Promos daily cards: Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.
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.
Key capabilities
- Pull-forward detection
- Promo ROI scorecards
- Net lift measurement (not gross)
- Cannibalization quantification
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled cough and cold against the illness curve for the 38 Northeast pharmacies. Front of store is running two weeks behind the demand signal.
| Signal | Finding |
|---|---|
otc_sales_daily | Cough/cold units +31% WoW, on-shelf availability down to 88% |
replenishment | Vendor lead time 6 days, reorder points still on the summer baseline |
front_store.attach | Wellness attach on flu-season fills 19% vs. 34% chain best |
Recommend: raise cough/cold reorder points at all 38 stores now, pull the wellness endcap forward two weeks, and add the attach prompt at the counter.
otc_sales_daily…
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 |
|---|---|---|
mckesson_wholesale_orders | import | 2m ago |
cardinal_lot_expiry | import | 2m ago |
sap_pos_transactions | import | 14m ago |
sap_inventory_snapshot | import | 1h ago |
retail_otc_sales_daily | import | 1h ago |
retail_front_store_margin | import | 1h ago |
retail_planogram_audit | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-front-store | permit | Model::"front_store_margin" |
ops-read-default | permit | Model::* |
phi-forbid-all | forbid | Model::"patient_*" |
supply-read-expiry | permit | Model::"lot_expiry" |
Why Promos matters for Pharmacy retail
Pharmacy has a unique promotional advantage: Rx refill cycles create a predictable visit cadence. The question isn't whether a promo lifts sales, it's whether it converts Rx-only visitors into front-of-store buyers or merely discounts for customers who would have purchased anyway. Ward measures effectiveness against the refill visit baseline.
Why this combination
is its own problem.
A CFO in pharmacy retail owns numbers that move faster than the reporting cycle that covers them. Rx fill rate, OTC attach rate, expiry waste % shift store by store, each day. A monthly pack cannot represent that. Your P&L surprises are born on the store floor.
- 01 Promo ROI gets measured on category lift without separating Rx-attached incremental conversion from deal-seeker cherry-picking.
- 02 Manufacturer coupon clip-and-redeem programs look efficient on paper but often fund discounts for customers who would have purchased anyway.
Benchmarks. Pharmacy front-of-store promo events typically show 25-60% gross lift but only 5-20% net incremental lift after deal-seeker cannibalization. Targeted Rx-customer offers usually achieve 2-4x the incremental conversion of blanket front-end promos.
What Ward has eyes on.
Know which promos actually work. 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 20,000+ SKUs across your pharmacies, at the store-category level rather than the chain roll-up. The metrics under watch include Rx fill rate, OTC attach rate, expiry waste %. A roll-up hides a single-store problem inside a healthy average, which is how seasonal illness demand stays invisible for a quarter.
Ward pulls from POS transactions, inventory positions, purchase orders from SAP Retail on a read-only connection. Nothing is written back, and your ERP configuration does not change. SAP stays the system of record.
At the metric level. Ward distinguishes between Rx-driven visit conversion, deal-seeker cannibalization, and category-specific promotional ROI. True incrementality is calculated against the predictable Rx visit cadence as a demand baseline.
What the first 90 days
actually look like.
-
01
Week 1: read-only connection
Ward plugs into SAP Retail with read-only credentials and begins ingesting POS transactions and inventory positions. No config changes on your side. First insight cards arrive within 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: operating rhythm
Insight cards arrive every morning 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 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
Your P&L surprises are born on the store floor.
- ×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
- ✓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
Pharmacy KPI impact
Frequently asked questions
Ward measures true promotional lift net of cannibalization, pull-forward, and pantry loading. For Pharmacy retail specifically, Ward monitors 20,000+ SKUs across your pharmacies and delivers automated insight cards with root cause analysis and recommended actions.
Ward tracks Rx fill rate, OTC attach rate, Expiry waste %, Script count, Front-store margin at the store-category level. Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.
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 Pharmacy-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 Rx fill rate, OTC attach rate, Expiry waste %, tailored for Finance decision-making. Each card includes what changed, why it matters, and what to do next.
Ward distinguishes between Rx-driven visit conversion, deal-seeker cannibalization, and category-specific promotional ROI. True incrementality is calculated against the predictable Rx visit cadence as a demand baseline.
A skincare promotion shows strong gross lift, but Ward reveals most of the uplift came from existing skincare buyers cherry-picking deals, not Rx customers making incremental front-of-store purchases. Ward recommends a different model: targeted checkout offers for Rx customers based on health profile. Pilot shows materially higher incremental conversion at lower promotional cost.
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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