Case Study: Electrolux achieves 3x increase in sales forecasting accuracy with Databricks

Influencing global revenue growth with data and ML

Electrolux, a global appliance company selling across 155 markets with 400+ distribution centers and over 60 million products moved annually, needed to better predict demand and measure marketing impact. Their forecasting was manual and Excel-based, drawing on scattered data sources, which led to inaccurate forecasts, poor visibility into campaign influence, and difficulty managing many models and data quality at scale.

Using Databricks on Azure with Delta Lake and MLflow, Electrolux unified data ingestion, built robust production pipelines, and managed thousands of ML models while delivering a sales-volume forecasting dashboard integrated with Microsoft tools. This drove a 3x increase in promotional sales forecast accuracy, faster model iteration, improved marketing ROI, more reliable product delivery, and stronger cross-team collaboration.

Electrolux

Johan Vallin

Global Head of Data Science