Case Study: Adamed achieves automated demand forecasting and reduces forecast errors to below 5% with Microsoft Power BI

Pharmaceutical manufacturer automates demand forecasting, errors drop below 5 percent

Adamed, one of Europe’s largest pharmaceutical manufacturers, faced inefficient, opaque 18‑month demand forecasting that relied on subject‑matter experts and multiple spreadsheets. To modernize forecasting across hundreds of SKUs and brands with differing seasonality and drivers, Adamed worked with Predica and adopted Microsoft Power BI alongside Azure services to consolidate data and increase transparency.

Predica built an extensible platform using Azure Data Factory, Azure SQL Database, Azure Machine Learning, and Microsoft Power BI to automate monthly 18‑month forecasts, retrain models, and surface reports for managers and sales teams. The solution centralized data, sped decision‑making, and reduced forecasting errors to below 5 percent across Adamed’s product lines while giving stakeholders clear, drillable insights via Microsoft Power BI.

Adamed

Joanna Kuduk

Digital Transformation Manager