Pharmacy · SAP · VP Merchandising

Pharmacy SAP data, read for merchandising

Your SAP feed covers 20,000+ SKUs throughout your pharmacies. Ward reads it for merchandising.

What a pharmacy VP Merchandising gets from SAP Retail

In a Pharmacy & Health fleet the job is 20,000+ SKUs across pharmacies. Regulated inventory, seasonal demand spikes, and front-of-store optimization. Ward handles the complexity so your pharmacists focus on patients.

Your category managers are drowning in spreadsheets. Ward filters to what a VP Merchandising can act on and drops the rest.

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 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"
for Pharmacy on SAP data, live product demo.

What Ward delivers

  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

Metrics Ward monitors

Rx fill rate
OTC attach rate
Expiry waste %
Script count
Front-store margin

Pharmacy challenges Ward solves

  • Seasonal illness demand
  • Rx-to-OTC conversion
  • Expiry management
  • Controlled substance compliance
  • Front-of-store attach

Why this combination
is its own problem.

SAP Retail was built for transactions, not for merchandising decisions. The data is right there and it is in the wrong shape. Ward reads POS transactions and inventory positions and rewrites them as a decision.

What Ward has eyes on.

Ward pulls 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 findings. Your ERP is untouched.

Ward watches 20,000+ SKUs over 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.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to SAP Retail. Ward reads straight from POS transactions, inventory positions, purchase orders and starts building baselines. First findings 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 daily cards every morning, each with the driver and a recommended action. Volume settles at a level a single person can read over coffee. The measure of success is not how many daily 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

Your category managers are drowning in spreadsheets.

Pain points
  • ×Promo planning still runs off last year's playbook
  • ×Assortment reviews happen quarterly when they should happen daily
  • ×Price changes chase the market a week behind it
  • ×No visibility into true cannibalization across categories
  • ×Vendor negotiations lack real-time sell-through evidence
How Ward helps
  • Insight cards flag promo cannibalization the day it happens
  • Assortment gaps and whitespace opportunities surface automatically
  • Price elasticity shifts detected before margin erosion compounds
  • Category-level performance cards replace manual spreadsheet reviews
  • Vendor scorecards generated from actual fill rate and quality data

Retailers lose an estimated $300B+ annually to suboptimal assortment and promotional decisions. Source: McKinsey & Company

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 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 category managers are drowning in spreadsheets. Ward solves this with automated insight cards: Insight cards flag promo cannibalization the day it happens. Assortment gaps and whitespace opportunities surface automatically. Price elasticity shifts detected before margin erosion compounds.

Ward delivers daily insight cards covering Rx fill rate, OTC attach rate, Expiry waste %, tailored for Merchandising 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 Pharmacy 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