AI & BI use case · Business Intelligence

Medication demand planning

Plan medication inventories to actual demand.

What it's about

Medication demand planning forecasts consumption from patient data, seasonality and treatment plans, minimising shortages and expiry.

  • Lower inventory
  • Cost reduction
  • More safety
Business case & ROI
−25 %

stockouts

−20 %

expiry

4–6 Mon.

payback

+15 %

inventory turnover

Calculated from fewer emergency purchases, less expired medication and lower inventory costs.

How we do it
  1. 01

    Data integration

    Consolidate data from ERP, MES and further sources for Medication demand planning.

  2. 02

    Data quality

    Clean, harmonise and validate data for plausibility.

  3. 03

    Model development

    Train and validate the Medication demand planning model on historical data.

  4. 04

    Pilot

    Pilot Medication demand planning in one area and collect feedback.

  5. 05

    Rollout

    Scale the solution and integrate it into operational processes.

5

Steps

6

Data sources

4

Stakeholders

From first data access to production – every step delivers a tangible interim result.

Data typically needed

Inventory data

Stock levels, movements and locations.

Patient data

Treatment data, appointments and resource use.

ERP data

Master and transaction data from ERP.

Appointment data

Patient and customer appointments with history.

Supplier data

Lead times, certificates, prices and ratings.

Documents

Specifications, quotes, contracts and reports.

Stakeholders
  • Patient management

    Improves processes and resource utilisation.

  • Purchasing

    Improves negotiations and supplier selection.

  • Controlling

    Quantifies effects and supports budgeting.

  • IT

    Builds on a scalable and secure data infrastructure.

Typical business value
01

Lower inventory

02

Cost reduction

03

More safety

04

Better planning

05

Higher efficiency

The data platform advantage

With a solid data foundation this use case gets faster, cheaper and far more stable.

Central data platform

Real-time data integration

Scalable analytics pipelines

Reusable data products

Build a data platform
Synergies & positive side effects

Inventory optimisation

Forecasts drive inventory and procurement.

Demand forecasting

Data flow enables more precise forecasts.

Supplier scoring

Quality and delivery data feed scoring.