Stockout Prediction insight cards for Pharmacy & Health.
Ward delivers stockout findings as insight cards, each with a root cause and a recommended action.
Why stockout matters
in pharmacy retail.
Ward doesn't touch regulated Rx inventory, but front-of-store OTC demand can spike dramatically at the zip-code level when illness season hits. Ward models these surges using CDC surveillance data, local school absenteeism signals, and historical seasonal patterns to predict OTC demand 48-72 hours before it arrives.
Benchmarks. Pharmacy front-of-store seasonal categories can swing 200-500% during peak illness weeks. Operators using disease surveillance signals typically capture 20-40% more peak-week revenue than chains relying on prior-year calendars alone.
Flu wave front-of-store prep, 600-store chain
Ward's disease surveillance model detects elevated ILI rates in several metro areas days before competitors react. Ward issues stockout prediction cards with store-level uplift estimates and recommended emergency orders. Stores are fully stocked when the wave hits, capturing share from competitors scrambling with empty shelves.
Three pitfalls Ward catches
in pharmacy stockout.
- 01 OTC ordering follows national seasonal calendars, missing the regional 1-3 week lead/lag that disease surveillance exposes.
- 02 Rx script volume is a leading indicator of OTC companion demand (Tamiflu Rx → cough/cold OTC) but most chains don't link the two systems.
- 03 Allergy and cold demand is treated as one season; pollen peaks shift 2-4 weeks each year and the static plan misses the actual peak.
How Ward runs stockout
for pharmacy retailers.
-
01
Layer disease surveillance onto OTC forecasts
Ward joins CDC ILI rates, local school absenteeism, and pollen indices to OTC demand history at the regional and store level.
-
02
Connect Rx-to-OTC companion patterns
Ward identifies 50-150 high-confidence Rx-to-OTC pairs (e.g., Tamiflu → cough/cold) and uses Rx script velocity as a 24-72 hour OTC leading indicator.
-
03
Issue regional pre-position cards
Cards recommend emergency orders, endcap resets, and forward buys for affected regions ahead of the surge.
What a Ward card looks like.
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…
Dashboards
Pinned views built from saved data-lake queries.
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" |
Pharmacy stockout:
the shift.
- ×Seasonal illness demand
- ×Rx-to-OTC conversion
- ×Expiry management
- ✓Reduce lost sales by catching gaps early
- ✓Automated replenishment recommendations
- ✓Supplier-aware lead time modeling
Questions about pharmacy stockout.
Ward doesn't touch regulated Rx inventory, but front-of-store OTC demand can spike dramatically at the zip-code level when illness season hits. Ward models these surges using CDC surveillance data, local school absenteeism signals, and historical seasonal patterns to predict OTC demand 48-72 hours before it arrives.
Ward's disease surveillance model detects elevated ILI rates in several metro areas days before competitors react. Ward issues stockout prediction cards with store-level uplift estimates and recommended emergency orders.
Ward focuses on illness-driven demand modeling, OTC-Rx correlation (Rx script spikes predict companion OTC demand within 48 hours), seasonal product velocity, and supplement trend detection.
First stockout insight cards arrive within 48 hours. Stable pharmacy baselines form within two weeks.
Pharmacy stockout
by data source.
More Pharmacy insight cards.
Pharmacy retailers: see what stockout problems Ward catches.
Root causes, not just alerts. See it on your data.
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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.