As a shipping manager, you’ve got budgetary borders around every decision you make. Most decisions come down to a choice: invest in more shipping containers, or move the ones you have more frequently? More assets mean more storage costs, particularly during slower parts of the season – but fewer assets require more trips to move those containers, with higher costs. Additionally, some assets might be unique – or expensive – and their numbers are deliberately kept low, meaning they need to cycle more often to avoid holding up your production lines.

These decisions can be better informed by running real-world simulations – based on your actual demand, your cycles, and freight versus storage costs – to give you much-needed insights into container usage and achieving the balance between purchasing more and better managing those you have.

Best-Case Scenario

Analysis should start at the highest level – the best-case scenario. Simulations are run with the variables set to optimal conditions. For example – how many containers are necessary for each of your suppliers to keep in inventory to fulfill demand?

Historical Variables

Simulations get more granular by introducing historical variables where available, or simply manually entering variables such as the dwell at each supplier, transit time between segments in the loop, repair rate of each container, loss rate of each container, warehouse fulfillment time, OEM dwell, and cost per delivered container.


Most supply chain loops are “linear,” meaning reusables follow a set progression from one location to the next. Deviating from this pre-determined progression (by showing up at a later stop in the list) is treated as non-conformance. However, for flexibility, limited tracking can be inferred when a reusable might be sent to one of several available locations. These “non-linear loops,” however, should ideally be considered as a segment of a larger loop, to ensure broader tracking data trends are still captured.

It can seem easier to just buy more containers than it is to spend the time and money necessary to correct mistakes in your reusable container fulfillment model. But in the long run, doing so is simply throwing money down the drain, compounding the problem by requiring additional storage without addressing the underlying cause: management based on guesswork.


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