When many companies set out to manage their reusable container programs in-house, they often end up investing a significant portion of their budget on the wrong kind of “management.” Purchasing the wrong kind of container – or even the wrong quantity of the right container – can lead to shortages, overages, and the reliance on disposable alternate packaging like cardboard boxes – undermining the reason you switched to reusables in the first place!
These issues can be resolved by running real-world simulations, based on your actual demand, to determine the actual containers to purchase, and the amounts to purchase them in.
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?
The simulations get more granular by introducing historical variables (if 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.
Let’s be honest – it can seem easier to just buy more containers than it is to spend the time and money necessary to correct mistakes in your reusables 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.