Pierbridge, a provider of parcel shipping solutions, has come out with an interesting cartonization software solution. In comparison to transportation management systems, which have very robust optimization, parcel solutions have historically been rather limited in the optimization they offer.
In addition to parcel shipping software, warehouse management software providers offered cartonization solutions to help reduce parcel shipping costs. Cartonization has focused on the selection of the right carton based upon the sizes and weights of items for a given order. In practice, most companies had a limited number of box sizes and the cartonization solution was designed to minimize the amount of air in the box. If it was a one product shipment, the solution selects the smallest box the product will fit in. If multiple products are going to a destination, it selected the box size that all the packages could fit with the least wasted space.
Cartonization can have a good ROI. I talked to one distributor several years ago that had a payback period of less than a year. But when the largest overnight delivery carriers (FedEx and UPS) began applying dimensional weight pricing in 2015, the game changed. Now virtually all the parcel carriers have their own set of DIM weights, and they are pretty much all different.
Dimensional weight pricing, referred to as DIM weight, sets the shipping price based on package volume which equates to the amount of space a package occupies in relation to its actual weight. This pricing method considers the exterior package size in relation to its actual weight, to determine the appropriate price. The dimensional weight calculation will apply if it is greater than the actual weight.
This is an optimization problem that to be solved needs to look at DIM rules by carrier, the various services offered by different carriers, and cartonization concurrently. That, by the way, is why I like the name of this product – Opdimizer – which is a play on both “optimization” and “DIM”.
The answer that maximizes savings can be nonobvious. For example, an order with 10 items won’t necessarily be packed in the smallest box that will fit those order lines. It might be that 6 items are packed in one box and four in another. I’ve always been a sucker for clever optimization solutions!
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