Data2Move Research Stories: the VMI effect within Heineken’s Dutch supply chain

Where supply chain management and data science meet, interesting questions arise. In our Data2Move Research Stories, you’ll find out how students have managed to answer them. This time: Rolf van der Plas and his master thesis on the Vendor Managed Inventory effect within the Dutch supply chain of Heineken.

Where it started

The global beer market is consolidating with less local and more global brewing companies. The remaining players enter into a hyper-competition to be innovative and to differentiate themselves from each other, in order to leverage their scale for increasing operational excellence.

As part of Heineken’s drive to improve operational excellence, a new enterprise resource system will be introduced. It has an optional module that supports collaboration based on the Vendor Managed Inventory (VMI) framework. Heineken has been exploring VMI collaboration with a number of customers. Rolf van der Plas aimed to validate the effectiveness of VMI for Heineken and their customers, like retailers, by quantifying the effect on supply chain performance. He investigated:

  • Heineken’s transport utilization
  • Stock levels in the distribution centers (DCs) of the customer
  • Out-of-Stock performance in the customer DCs

Rolf selected three techniques to investigate VMI collaboration:

  • Data analytics to analyze the current effect
  • A simulation model to redesign the VMI process
  • A simulation-based searching (SBS) model to enhance the parameters settings used in the VMI-designs

Findings: a win-win situation

The current VMI collaboration in Heineken results in 15% higher transport utilization compared to deliveries to DCs of customers without VMI.  A new variance-based VMI design with enhanced parameter settings results in an even higher supply chain performance for Heineken and the customer compared to the current VMI implementation.TabelR

The benefits? A 7% higher truck utilization, meaning trucks are used more efficiently and transport costs go down. Also, a 70% reduction of the average stock levels in the customer DCs, while maintaining a 0% Out-of-Stock performance. The main finding: both supply chain partners benefit.

Further advice

In conclusion, the VMI collaboration effect is both beneficial for the suppliers and for the customers. Rolf’s study proves that his SBS model is an adequate method to consistently identify robust settings that enhance supply chain performance. Rolf endorses the usage of the model for future challenges. He recommends setting up (more) VMI collaboration with your supply chain partners as a tool to improve your supply chain performance.

Also check out our previous research stories

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