February 28, 2006
Volume 2 Issue 51

Following the Steps to SKU Success

It’s a dilemma as old as time: To remain competitive, costs have to come down. But still a host of factors push costs in the opposite direction. Every warehouse manager faces it, but luckily many tools and techniques have been developed over the past few years to help warehouse managers make their facilities considerably more efficient. The inefficiencies in many warehouses are in direct relation to a failure to scrutinize and understand the complete data of how inventory truly moves through a facility as the orders are fulfilled. Half of a warehouse’s labor costs are spent on picking, and 65% of the average picker’s time is spent walking to and from the pick face. Making things worse is the unrelenting problem of stock-outs and the costly effort it takes to rise above them. Another 25-40% of warehouse’s labor costs are spent on replenishment-a cost kept high as a result of poor design reserve and forward-pick locations.

Customers are asking more and more for value-added services. This issue pushes up the unit cost of fulfilling orders and magnifies existing inefficiencies. Reducing embedded inefficiencies and cutting per order costs is achievable, but only after a concentrated analysis of SKU (item number) and order line data to reveal true costs per line or order. Bottom line - THERE ARE NO SHORT CUTS; you need to take all the processes and steps outlined here before the data can help you plan to reduce costs. Our next newsletter will discuss the data analysis required to understand labor costs in the warehouse.

Analyzing your data will provide for a better understanding of the effects of seasonality; how to analyze one-line orders; and how to determine a host of other crucial operational details. Determining the allocation of orders to pick module or reserve picking areas prevents making forward-pick areas bigger than necessary and allows for planning to pull solid pallets from reserve to eliminate multiple touches. Without it, a facility’s design could have costly contingencies such as extra storage media, which can lead to a facility that is as much as 35% larger than required. That in turn causes longer travel times in picking. The order velocity analysis provides data needed to choose storage media based on cube or productivity considerations, to understand the effect of replenishment on labor costs and unexpected stock outs in forward-pick locations, to judge the financial benefits and costs of investing in higher-productivity picking media, and to understand seasonality and its impact on the building and operations.

Taking it One Step Further

We all know that customer’s orders consist of lines and that a line is a single SKU in various quantities. In reality, order lines consist of smaller groups that must be picked at a defined pick face. These smaller units are called order sublines. That is a breakdown of a customer’s order into the number of eaches, full cases, and/or full pallets of each SKU (item number), plus any potential combinations of these. It is really these order sublines that define the order picking requirements, the storage media requirements, the impact of orders on operations, the replenishment plan, and the labor needed for key functional areas.

This is where the costs of picking and replenishment are located. Looking at the picking activities at this level makes sure full pallets are optimally picked from reserve, full cases are optimally picked as cases, and eaches are picked as eaches or inner packs. This subline data also helps in designing the pick methods. The subline analysis can also provide a better understanding of the effects of seasonality on operations. By analyzing the data to this subline level, we can distinguish between the movement and storage needs of basic and seasonal items, thus producing a smaller, more efficient operation. By understanding in which seasons a defined SKU is really a fast mover and when it is a medium mover gives you the ability to slot and pick this SKU in a fast-moving method during this prime season. During the slower season, this SKU can perhaps be put away in slower-style media as it is received again into the building. The complete understanding of the differences between peak-season release times and non-peak release times is important to lowering cost.

LOWER LABOR COSTS THROUGH ANALYSIS

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