Optimizing container shipments

Published on by Joannes Vermorel.

Supply chain management has long gone global: even small businesses are now importing goods from overseas whenever they identify the right business opportunities. However, while supply chain data can flow back and forth across the globe at a fraction of the speed of light, physical goods are still mostly freighted via containers with lead times counted in weeks, if not months. On top of that, containers further complicate the task of supply chain practitioners by imposing both volume and weight constraints.

Lokad is now supporting dozens of companies to help optimize their order quantities while taking into account their container shipment constraints. Below, we review some of the most important insights that we have gathered when dealing with demand planning combined with container shipments.

The most frequently overlooked aspect of dealing with containers is probably the importance of the ordering lead times. Indeed, except for extremely large businesses, ordering in containers imposes significant waiting periods between successive orders to the same supplier. Neglecting the ordering lead times results in significant under-estimation of the demand to be covered and causes costly stock-outs. Consequently, the ordering lead time, like the supply lead time, needs to be forecasted too. This makes it not just a demand forecast, but a lead time forecast as well.

Then, the second most overlooked factor is related to how badly the constraints associated with container shipments misfit the classic ordering policies such as order-up-to-level or order-quantity. In reality, such ordering policies fail to satisfy the necessary constraints, and as a result, the ordered quantities either exceed or underuse the entire container capacity. For this reason, supply chain practitioners end up spending a lot of time doing manual corrections in order to get the quantities matching the container capacity. A much more efficient solution implies using a prioritized ordering policy, where items can be added up to the point where the container is full.

When Lokad tackles demand planning in the presence of container shipment constraints, the two primary questions we strive to address are:

  • What is the “best” composition of the next container to be ordered (which items, which quantities)?
  • What is the expected profitability of this next best container?

As long as we can address these two questions, ordering from suppliers becomes a piece of cake. All it takes is refreshing the forecasting “logic” in your Lokad account on a daily basis, and checking whether the next “best” container to be ordered reaches a certain profitability threshold; and when it does, just ordering the suggested quantities. This process is even more flexible than filling the container up to its full capacity as it is possible to consider circumstances where the most profitable containers are not filled up to 100%. In fact, it’s really up to the profitability analysis to decide whether each item is worth putting in the next container or not.

Computing precise estimations of both margins and costs requires a forecasting technology that is capable of considering a myriad of scenarios. At Lokad, we achieve this through probabilistic forecasts: we don’t forecast the average demand, but the probabilities associated to (almost) all future demand levels. Through our probabilistic forecasts, every scenario can be assessed financially and then weighted against its probability. Finally, every container’s potential composition can be assessed through its weighted average of financial outcomes, the weights being the probabilities associated with the respective demand scenarios.

The method for handling container shipments that we have just briefly described might look quite intensive as far as computations are involved. Well, it is. However, the time and expertise of supply chain practitioners is far too valuable to be “burned away” spending countless hours on tweaking Excel sheets.

This leads us to our third most overlooked aspect relating to containers: manually composing containers is a very tedious process, and this process comes at the expense of more fundamental supply chain improvements. Indeed, for small companies, we frequently notice that they could order containers more frequently. However, the process of figuring out the exact composition of containers is so time-consuming that realistically, it can’t be generally done more than once a month. In a similar vein, for larger companies, we also often notice that the opportunities to consolidate shipments from multiple suppliers shipping from the same port are also frequently dismissed not because they are impractical, but simply because this would require using a method that cannot be supported by manual processes.

As a result, in practice, manual container composition "hits" companies in two different ways: first, because the composition of the container isn’t really optimized in the first place, and second, because it consumes most of the supply chain management resources which would be better used for improving the supply chain on the whole.

Lokad’s technology makes it quite straightforward to compose optimized containers in a fully automated manner. Check out our more technical entries in case you would like to tackle the challenge yourself. In practice, our Lokad team is here to assist your company in getting it right, as containers might not be the only constraint that your company is facing: there might be minimum order quantities, warehouse storage capacity, etc.

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