Summary: Continuing our series on the three main categories of discoveries that a solution should provide retailers to help minimize the effort necessary to identify controllable factors that can be translated into action, this edition will break down what is known as a “known/unknown”. Recalling from the previous blog, these categories are determined based on whether or not retailers know there is an opportunity, as well as if they know how this opportunity is used to generate value. The value is generated by finding and acting on opportunities correctly within their systems, processes, or personnel. A “known/unknown” is when the retailer knows there is something going on, but doesn’t know how to find it; or they have a gut feeling about some problem, but can’t put a finger on specifics. This may be the most frustrating type of discovery for a retailer, since they are aware something (a system, process, or personnel) is not working the way it should be, yet the cause, and therefore the solution, is unknown. Leveraging pattern seeking software and appropriate benchmarks helps the retailer find the root cause of a known opportunity and assign appropriate actions to correct it, or myth-bust its existence, eliminating false positives. One simple example of this occurrence comes from perpetual inventory, or PI adjustments. Let’s take a retailer that runs based on retail accounting and therefore calculates shrink based on retail price. Now let’s assume a store manager has 1,000 units of a product in their system at $50 (retail) a unit, and therefore they have $50,000 of inventory at “retail”. After an inventory count is performed, the on hand perpetual inventory shows 800 units, meaning only $40,000 of inventory. With this PI adjustment, the store’s inventory value shrunk by $10,000, which is counted as shrink for that store, if calculated at “retail”. However, since PI adjustments can typically be done whenever the store manager decides to perform them, he may wait until this high-priced item is marked down by headquarters, to lets say $25. With 1,000 units in the system, the inventory count at this time is believed to be $25,000, and that loss of $25,000 ($50,000-$25,000) is not reflected upon the store manager; it is the headquarters P&L, because it was a headquarter markdown in price from their level. If the manager performs a PI adjustment now, the current 800 units are now worth $20,000. So the store manager’s shrink number was reduced from $10,000 to $5,000, simply because they chose to count their inventory at a different time. It is very easy for a store manager to discover this power to “lower” the store’s shrink. Once this is realized, it is fairly simple to manipulate the numbers even more. What is even more worrisome is that this practice could be considered legal (however unethical), since the store manager is not responsible to count inventory every day. Managers are often informed in advance about markdowns or cost reduction (for retailers doing cost accounting), and can plan PI adjustments accordingly, for their own benefit. The incentive is high to manipulate these counts, especially since bonuses are often calculated with these shrink numbers in mind. Retailer are aware the PI adjustments are being made, so the problem is known, but it looks like the loss is stemming from corporate, as a result of poor markdown strategies and merchandising. However, the real cause is related to missing inventory in individual stores. The same amount of money is being lost, but these “wooden dollars” are simply being shifted around, moving the blame from the store manager up to corporate. Therefore hitting the product P&L side, and not the shrink side, of the equation. The retailer knows something is happening, and the perception is that its happening in the field. But they cannot perform the complex analysis of the reports needed to find out what is actually happening.
