Pharmacy · Tableau · Head of Procurement

Ward and Tableau for Pharmacy procurement

Ward pulls from Tableau and hands you pharmacy findings scoped to procurement. Merchandising wants Ward. You sign the contract.

What a pharmacy Head of Procurement gets from Tableau

Merchandising wants Ward. You sign the contract. Ward filters to what a Head of Procurement can act on and drops the rest.

For Pharmacy & Health retailers, that means watching 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.

How the connection works. Ward connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context.

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 Tableau data, live product demo.

What Ward delivers

  • 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

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.

A Head of Procurement rarely logs into Tableau. They read what someone else pulled out of it, two days later. Ward removes the two days and the someone else.

What Ward has eyes on.

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.

The connection to Tableau is read-only and runs on your schedule. Ward ingests tableau Hyper extracts, underlying database (direct), and the rest of the feed, then joins it with external context your BI does not carry: weather, local events, competitor pricing.

What the first 90 days
actually look like.

  1. 01

    Week 1: connect

    Read-only credentials to Tableau. Ward reads straight from tableau Hyper extracts, underlying database (direct), published data source metadata and starts building baselines. First insight cards 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 hands back cards each day, each with the driver and a recommended move. 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 Tableau

Ward does not replace Tableau. Ward adds the proactive layer Tableau lacks. When a metric moves, Ward explains why and recommends action.

Setup: Ward connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context.

Data Ward reads from Tableau

Tableau Hyper extracts
Underlying database (direct)
Published data source metadata

Impact metrics with Tableau

Time to Insight
Cards before dashboards
Anomalies explained before anyone opens Tableau.
Anomaly Detection
Extract-gap coverage
Catches issues between Tableau extract refresh cycles.
Decision Velocity
Investigation eliminated
Root cause embedded in cards; no ad-hoc queries needed.
Analyst Productivity
Detection work offloaded
Analysts freed from triage to focus on strategic work.

Data lake enrichment

Ward enriches Tableau data with: Tableau data sources, Underlying database, Weather & events, Competitor pricing, Customer data

Merchandising wants Ward. You sign the contract.

Pain points
  • ×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
How Ward helps
  • 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

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 connects to the same databases Tableau uses. Or reads Tableau Server metadata via REST API for context. Data points include: Tableau Hyper extracts, Underlying database (direct), Published data source metadata.

Yes. Ward reads Tableau data and combines it with contextual signals (weather, events, demographics) to generate Pharmacy-specific insight cards. No custom development required.

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.

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