When to acquire new warehouse space?

In a world where uncertainty and complexity increase, challenges arise for the Supply Chain of the future. In our CDT Research stories you will find out how students have come to solutions to these challenges. This time: Kevin America’s master thesis, undertaken at VidaXL, one of Europe’s fastest growing international online retailers. The focus of this thesis: at what percentage of utilization is it better to acquire new warehouse space instead of incurring the additional operational costs of operating at the threshold utilization?

Where it started

The enormous growth that VidaXL is experiencing brings along an increasing need for storage space to store all their products. The construction of storage space, as well as renting storage space, requires substantial capital resources and therefore VidaXL evaluates other options as well. One of these options is to increase the utilization of the already existing storage space (i.e. fill your warehouses more and more). There is, however, a lack of insight in the costs that this option brings along. To support VidaXL in their decision making it is of high importance that VidaXL knows which costs are associated with all available options. As the costs for acquiring new warehouse space are known, it was Kevin’s job to evaluate the costs of increasing the utilization of their warehouse.


To answer his research question Kevin developed a simulation model to simulate all the warehouse tasks over a period of time. This simulation program was able to capture a lot of performance indicators and required as input the pick- and bulk location utilization rates. To determine his input parameters (like picking time, demand rate, replenishment time and relocation time) he analyzed warehouse data of VidaXL. Kevin fitted several distributions to the historical warehouse data to simulate the entire VidaXL warehouse as realistically as possible.

In his research, he found out that several processes within the warehouse take longer at higher utilization rates compared to lower utilization rates. The research shows especially that the pick location utilization  has an enormous impact on several process times (like replenishments) and lead to an increase in tasks to fulfill the same number of customer orders. The replenishment times increase with almost 40% when increasing the pick location utilization from 80% to 120%. Another problem that arises when the pick location utilization exceeds 100%, is that products that are already replenished to a pick location need to be transferred back to a bulk location since there is no pick location available. Therefore, the warehousing process becomes rather inefficient, leading to increased costs.  The research also states that apart from the increased number of tasks for replenishment and relocation (and increased execution times for these processes), the put away times increase when the bulk storage location utilization increases.

These enormous drops in efficiency cause additional workforce to be hired to fulfill the same set of customer orders. Hence, additional operational costs are incurred.


With the results of his research, Kevin compared the additional operational costs with the costs of acquiring new warehouse space. He concluded that when the pick location utilization exceeds 135/140%, it becomes more and more cost-efficient to acquire new warehouse space instead of increasing the pick location utilization even more. Kevin: ‘So, when VidaXL forecasts to go above that threshold, they can anticipate by increasing the pick locations. They can use the output to decide to rent that warehouse space or change their strategy when they are most likely to exceed the threshold. By doing so, VidaXL can save on operational costs and keep the lead times as low as possible.’

It appeared, however, that the bulk storage location utilization increases the operational costs as well, but these additional costs do not outweigh the costs of acquiring new warehouse space. Hence, the pick location utilization is the most important factor to evaluate which is the most cost-efficient option.