Henkel might not be a household name for everyone, yet its products are found in millions of homes worldwide. With an extensive portfolio—ranging from beauty care to laundry detergents—Henkel maintains numerous production sites in Germany.

The sheer scale of operations brings significant logistical hurdles, especially when exporting to various global markets. This complexity fuels multiple data-driven initiatives focused on predictive analytics and optimization. Whether it’s demand forecasting or streamlining shipping routes, Henkel leverages technology to remain efficient and competitive.

Logistic Optimization

The Logistic Optimization project addressed a major exporter’s challenge of finding cost-effective shipping routes.

Henkel dealt with a wide range of products, each subject to different tolls, tariffs, and regulatory frameworks across country borders.

Family packs, for instance, could be classified as a single item in one jurisdiction but multiple items in another, creating added complexity.

To manage these variables, I gathered data on possible routes and associated toll structures, visualizing them on an interactive map. This allowed decision-makers to see the comparative costs and customs fees across diverse shipping paths.

I then built a simulation tool to explore multiple route scenarios, factoring in traffic patterns, local regulations, and packaging rules. Combining that with predictive analytics, I helped forecast logistical costs for each route configuration.

As a result, the logistics department could significantly cut expenses and streamline cross-border operations.

Keywords:

Optimization, Data Management, Forecast, Geo, Visualization

Previous
Previous

Bundesdruckerei

Next
Next

Toll Collect