Pharmacy · Promos · SAP

Promo Effectiveness for Pharmacy & Health on SAP

Your SAP data already carries the promos indicator. Ward reads straight from it, accounts for root cause, and attaches what to do about it.

How Ward turns SAP data into pharmacy promos

Promo Effectiveness. 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.

Under the hood. Ward isolates incremental volume from baseline, measures cross-SKU cannibalization, estimates pull-forward effects, and calculates true ROI.

The connection itself. 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

  • Cannibalization quantification
  • Pull-forward detection
  • Promo ROI scorecards
  • Net lift measurement (not gross)
app.getward.ai Live demo
Acme Pharmacy @Merchandising: Front-Store Analyst claude-sonnet default
A

Chat

Ask anything. Ward routes to the right agent and returns cited answers.

Why are we behind on cough and cold in the Northeast?
You · 9:42 AM
Schema Scout · routed to Merchandising Agent

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.

SignalFinding
otc_sales_dailyCough/cold units +31% WoW, on-shelf availability down to 88%
replenishmentVendor lead time 6 days, reorder points still on the summer baseline
front_store.attachWellness 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.

8 parallel queries 3 sources cited confidence 0.90
Which stores need the reorder point change first?
You · 9:43 AM
Replenishment Agent · ranking stores
Querying otc_sales_daily
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
Front-store revenue
$22.4M
+3.6% WoW
Front-store margin
28.7%
−1.8pp
OTC on-shelf availability
88.1%
−2.9pp
Expiry waste, 60-day risk
1.72%
+0.9pp
Front-store revenue 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
mckesson_wholesale_ordersimport2m ago
cardinal_lot_expiryimport2m ago
sap_pos_transactionsimport14m ago
sap_inventory_snapshotimport1h ago
retail_otc_sales_dailyimport1h ago
retail_front_store_marginimport1h ago
retail_planogram_auditimport1h ago

Policies

Browse and manage Cedar access policies for your tenant.

TLS 1.3 AES-256 Read-only SOC 2 II
Policy IDEffectResources
merch-read-front-storepermitModel::"front_store_margin"
ops-read-defaultpermitModel::*
phi-forbid-allforbidModel::"patient_*"
supply-read-expirypermitModel::"lot_expiry"
Promos for Pharmacy on SAP data, live product demo.

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.

What Ward has eyes on.

The connection to SAP Retail is read-only and runs on your schedule. Ward pulls from POS transactions, 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.

The promos model runs daily, not on a reporting calendar. It spots the pattern, accounts for root cause, and attaches the next step before the number reaches a review deck.

Every one of your pharmacies gets its own baseline. Ward keeps a running read on Rx fill rate, OTC attach rate, expiry waste % against it and pulls forward only the deviations that hold up. The two that show up most in pharmacy retail are seasonal illness demand and rx-to-OTC conversion, and both are baseline problems before they are P&L problems.

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.

Signals · POS with Rx-OTC basket linkage where loyalty data exists, full promo calendar with funding, Rx visit timestamps, and promo redemption tracking.

Why this combination
is its own problem.

SAP Retail is the system of record for most pharmacy operators of your size, which means the signals Ward needs are already there. The gap is not data collection. It is that nobody has time to read POS transactions and inventory positions every morning throughout every store.

  • 01 Wait-time merchandising next to the pharmacy counter is the highest-incrementality promotional surface, but most promotional spend goes to circulars and front-of-store endcaps.
  • 02 Promo ROI gets measured on category lift without separating Rx-attached incremental conversion from deal-seeker cherry-picking.

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 the first 90 days
actually look like.

  1. 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 cards arrive in two days.

  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 findings are directionally right and the thresholds are still moving.

  3. 03

    Weeks 4 to 12: steady state

    Ward sends cards on a daily cycle, 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 insight 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

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

Pharmacy KPI impact

Expiry Waste
Flagged before close
Shelf-life velocity tracked per store.
Front-of-Store Margin
Highest-margin area
OTC adjacency and illness prep cards for the front end.
OTC Attach Rate
Rx-to-OTC conversion
Seasonal wellness bundling patterns identified.
Fill Rate
48–72hr lead time
Illness demand modeled before seasonal spikes hit.

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.

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.

See what Pharmacy promos 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.

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