A typical inventory on-hand investment for an average retailer is significant and often equals a value approaching one fourth of annual sales (assumes an average turn of 3X). Given that this investment is so large and dynamic (with outflow due to sales and inflow due to replenishment), the need to manage this asset accurately is paramount. Most current POS systems allow a download of key SKU data, including on-hand position, average cost per unit, status, and related sales by period. Exporting and analyzing this information for a sku rationalization analysis is a very smart way for a retailer to optimize inventory value. Some examples of the analysis you may wish to consider are presented below.
Excel is often an appropriate software tool to perform the inventory analysis required. We suggest starting with the most basic types of sortation to look for anomalies. Suggestions for basic sorts include inventory value of <0 and =0 are important. The same sort should be performed for quantity on hand. The key question you should ask here is “why”? Next look for unusually high values and on-hand quantities. If your system allows a download of last sale date, sort these by the number of days prior to today’s date of review and scan for seriously slow sales activity.
Inventory status sortation is also useful in monitoring inventory (potentially) sidelined from normal accessibility. This process is performed by sorting all on-hand inventory into whatever inventory classification your firm employs. Examples of this might include, normal on-hand, seasonal, seasonal pack-away, damaged, suspended, future, etc. Once your inventory is sorted into these categories of availability, scan the details of each one to look for unusual classifications and aging (sidelined) goods that should be available for sale right away.
Calculating your inventory turns profile
The next level of sort that should be performed utilizes a calculation of annualized (or “seasonal” if you understand the retail math involved) turns, comparing COGS and on-hand values. Turns can then be sorted into ascending values allowing slow moving stock to be identified. This process requires a keen understanding of the characteristics of each SKU, as SKU velocity can be influenced (positively or negatively) by seasonal ebbs and flows.
Lastly, SKU POS data by week can be utilized to show sales profiles that are invaluable in spotting size and color trends, particularly fast-moving merchandise and even re-stocking issues. We strongly recommend that these types of inventory review be used by your firm. They will undoubtably help to optimize the usefulness of your inventory