How to Leverage Data Analytic Power to break myths? Dimensions
In this series of articles, we will discuss how to harness data analytic powers to improve the quality of thinking processes, work accuracy, and insight precision. We will first focus on the topics across the e-commerce industry and expand to more and more fields.
Product dimensions play crucial roles when we run the business analysis like inventory space cost, outbound delivery expense, fulfillment center capacity evaluation, etc.
There are two main types of product dimensions, unit dimensions & case dimensions. Unit dimensions are the final product’s weight and size (height, width, and length). Case dimensions are the ones received from vendors. In some cases, unit dimensions could be as same as case dimensions depending on the size of products or how vendors pack and ship the products. Small items like pens or binder case dimensions are likely larger than unit dimensions as we normally place orders of cases of pens instead of pieces.
First, we should always use case dimensions for the inventory-related analysis. When we do the analysis like average on-hand in cube estimation or space costing by-products, some people would directly use unit dimension to calculate the inventory in the cube occupied in the distribution center. It works for some products but overall this will result in the overestimation.
Here is one example, Avery 3" Economy View 3 Ring Binder. The unit dimensions are around 11.6"L x 2.9"W x 11.2" H (377 in³) and there are 12 units per case. The case dimensions are around 24"L x 12.5"W x 12.5" H (3750 in³). Using unit dimensions results in the overestimation as unit dimensions * 12 (units per case) are greater than case dimensions. The main reason is the way the vendor's pack is to intertwine the binders with each other so the required space is less than the stack.
Another tricky examples could be that the product with property of either cavity or nesting can be fitting inside each other. Products like stackable chairs, trach can might have the same case and unit dimensions but in the distribution center they can be stacked on top of each others, which means you can’t directly use dimensions multiplied by unit counts to calculate the space occupied by the multiple units. Instead, in this situation, it requires more research like
- incremental volume per newly added items.
- max units the items are able to be stacked.
Thank you and enjoy it!
