Case Study: Audi achieves more accurate supply chain forecasting with KNIME

How Audi Forecast Their Supply Chain With KNIME

Audi worked with KNIME to improve supply chain forecasting across its manufacturing operations. The automaker needed a more accurate, automated way to predict warehouse stock levels and incoming goods so it could avoid overcapacity, prevent production delays, and make faster decisions with incomplete data.

Using KNIME’s machine learning workflows and KNIME Server, Audi automated data collection, cleaning, analysis, and reporting for real-time forecasting. The solution reduced manual errors, saved €30,000 annually from a single workflow, and cut debugging expenses by 80%, while improving forecast accuracy and helping Audi better manage warehouse capacity and production flow.

Audi

Simon Herzog

Data Analyst