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Panalpina World Transport (inventory reductions)

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Panalpina World Transport BV, Tilburg, Netherlands
Panalpina World Transport BV, Tilburg, Netherlands

Developing a demand-driven inventory forecasting model to facilitate inventory reductions.

The research team collaborated with Panalpina World Transport Ltd, to improve the firm’s ability to forecast inventory demand and facilitate inventory reduction for their customers.

Professor Aris Syntetos, Chair in Operational Research and Operations Management at Cardiff Business School,  established a Knowledge Transfer Partnership aimed at developing a demand-driven inventory-forecasting model to facilitate inventory reduction.

Project aims

The Panalpina Group is one of the world’s leading providers of supply chain solutions, combining intercontinental air and ocean freight with comprehensive value-added Logistics and Supply Chain Services.

The logistics product was a high priority for Panalpina and its development was key to the overall group strategy.

One way the company could differentiate itself from its major competitors is by becoming the first logistics provider in the world to actively buy and manage customer’s inventory. To do this, the company needed:

  • to develop a demand-driven inventory-forecasting model to facilitate inventory reductions at the customers’ businesses, and
  • to develop a commercial model to allow the organisation to cost-effectively buy and manage the customer inventories.

This KTP will enabled the company to achieve both those objectives.

KTP associate

The project was driven by one full time KTP Associate, Nicole Ayiomamitou. Nicole has a first class honours degree (BSc) in Mathematics from the University of Surrey and an MSc in Operational Research from the School of Mathematics at the University of Edinburgh.

Nicole’s work was co-supervised by Andrew Lahy, who is the Global Head of Continuous Improvement in Logistics at Panalpina.

Further information

Further information on this project can be obtained by contacting Professor Syntetos.

Funders

The project was co-funded by the Technology Strategy Board and the Engineering and Physical Sciences Research Council.

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