Mercedes-Benz Management Consulting: Raw Material Analytics
Data-Driven Insights for Strategic Sourcing
Problem
Mercedes-Benz needed to anticipate raw material price volatility in order to make smarter, more cost-efficient sourcing decisions across their global supply chain.
Approach
I used Python and PySpark in Databricks to analyze stock price trends for over 200 materials, developed a mapping algorithm to connect them to internal procurement data, and validated the results through 13 expert interviews. Insights were visualized in a Power BI dashboard for decision-makers.
Solution
The resulting model helped identify pricing risks early and supported sourcing strategies estimated to save over $600K annually, informing executive-level planning with clear, data-backed insights.
This work was part of a 6 months internship at Mercedes-Benz Management Consulting in Stuttgart and gave me experience collaborating with senior leadership, combining quantitative analysis with strategic business insight in a global automotive context.
Mercedes-Benz Management Consulting: Raw Material Analytics
Data-Driven Insights for Strategic Sourcing
Problem
Mercedes-Benz needed to anticipate raw material price volatility in order to make smarter, more cost-efficient sourcing decisions across their global supply chain.
Approach
I used Python and PySpark in Databricks to analyze stock price trends for over 200 materials, developed a mapping algorithm to connect them to internal procurement data, and validated the results through 13 expert interviews. Insights were visualized in a Power BI dashboard for decision-makers.
Solution
The resulting model helped identify pricing risks early and supported sourcing strategies estimated to save over $600K annually, informing executive-level planning with clear, data-backed insights.
This work was part of a 6 months internship at Mercedes-Benz Management Consulting in Stuttgart and gave me experience collaborating with senior leadership, combining quantitative analysis with strategic business insight in a global automotive context.
Mercedes-Benz Management Consulting: Raw Material Analytics
Data-Driven Insights for Strategic Sourcing
Problem
Mercedes-Benz needed to anticipate raw material price volatility in order to make smarter, more cost-efficient sourcing decisions across their global supply chain.
Approach
I used Python and PySpark in Databricks to analyze stock price trends for over 200 materials, developed a mapping algorithm to connect them to internal procurement data, and validated the results through 13 expert interviews. Insights were visualized in a Power BI dashboard for decision-makers.
Solution
The resulting model helped identify pricing risks early and supported sourcing strategies estimated to save over $600K annually, informing executive-level planning with clear, data-backed insights.
This work was part of a 6 months internship at Mercedes-Benz Management Consulting in Stuttgart and gave me experience collaborating with senior leadership, combining quantitative analysis with strategic business insight in a global automotive context.