Inventory accuracy percentages can be misleading! We already know that inventory accuracy is a very important metric for retailers, measuring how closely system records reflect the actual units found in stores. But did you also know that a straight inventory accuracy percentage stating that inventory records are 75% accurate is missing a very important piece of information? That’s right - as time increases between counts, system records become less and less accurate. This makes sense when you think about it. Theft, mis-shipments, mis-ticketing, vendor fraud, and store process failures constantly spoil inventory records. These incidents occur randomly between counts and incrementally degrade your inventory accuracy. The only way to correct your inaccurate records is to count, returning your system to a state of "operational bliss." This description actually came from one client relaying how their omnichannel process works so much better after full counts.
Here’s a visual representation of how this works. Because accuracy degrades over time Datascan uses a monthly degradation percentage whenever we compare stores within a retailer or retailers within a market segment. It’s easy to calculate - take the inventory inaccuracy percentage (100% - inventory accuracy %) and divide by the number of months since the previous count. We use a standardized month by dividing the number of days between counts by 365 and then multiply by 12.
Let’s look at how to use this concept to compare two stores with different days since their last counts. Which inventory accuracy results would you prefer? Even though Store 1 has a higher inventory accuracy te percentage, Store 2 has a better monthly degradation rate and therefore better results.
Of course, many factors impact the actual level of inventory accuracy, including the selling seasons within the period between your full counts. Calculating a monthly degradation percentage assumes a constant rate of decline in your inventory accuracy percentage. Retailers may require additional investigation and analysis to understand any significant differences between stores, districts, or regions. Even so, comparing monthly degradation rates instead of a straight inventory accuracy percentage equalizes the timeframe between counts and can prevent faulty conclusions.
Add "count fixes everything"
