Phantom inventory can be as spooky as it sounds if you let it get out of hand.
Phantom inventory occurs when a Retailer’s Perpetual Inventory System states there is sellable inventory available in a store, but none actually exists. It can also occur when the store’s system displays a higher quantity of product in-stock than is actually available in the store; phantom inventory is the difference between the two. Because phantom inventory never generates sales, Store Managers and Buyers may conclude the product is not selling well and decide against reordering or even carrying the SKU. The reported inventory level is essentially a figment of the imagination, hence the “phantom” moniker.
Phantom inventory can cause major out-of-stock issues, thereby contributing to the “Ghost Economy”, a term used to describe the staggering $1.75 trillion combined impact that out-of-stocks, overstocks, and preventable returns have on retailers worldwide.
A number of issues can cause phantom inventory:
Let’s walk through a scenario. For example, the store’s system shows that your company’s product is in-stock and ready to be bought. But in reality, it’s not in the store. A customer is looking for your product. They can’t find it; so they enlist a store employee’s help in locating it. The product is nowhere to found. This results in a lost sale, a dissatisfied customer, and operating costs spent on the employee’s time responding to the customer’s request.
The employee may not address the issue, thinking that the product will simply turn up eventually. The employee may make a manual order for additional inventory, but once that newly received inventory sells through, the same phantom inventory situation will occur again, unless the inventory is adjusted. However, it is very unlikely an adjustment will be made until the end of the modular cycle. Thus, the store’s potential sales for this SKU will be impacted for the entire modular cycle. Phantom inventory strikes again!
The effects can be dire. As detailed in a Wall Street Journal article, professors at Stockholm Business School, Air Force Institute of Technology, and MIT’s Center for Transportation & Logistics sought out to measure the effects of phantom inventory by collaborating with a major CPG.
Their research “showed that for a category of laundry detergents sold by a large retailer, lost sales were almost five times greater than previously assumed owing to unobserved stock-outs.”
Identifying and fixing phantom inventory issues begins with product visibility. Product visibility becomes more and more difficult based on the number of SKUs you’re tracking. Let’s say you’re a CPG with 5 SKUs, available in 2,000 Walmart U.S. locations. Or you’re a larger CPG with 40 SKUs in all 4,761 Walmart U.S. locations. Whether you’re examining 10,000 data points or 190,000 data points per week (or even per day), legacy spreadsheet systems aren’t going to cut it when it comes to crunching data in a timely manner.
How can you spot inventory discrepancies when you’re manually running reports on thousands of data points per day? You have poor product visibility because getting granular with sales and inventory data would require a major time commitment that no CPG analyst likely has.
Phantom inventory analysis, at any scale, calls for a more powerful retail intelligence tool that can quickly work through your data points for you to point out trends and irregularities so they can be addressed in a timely manner. Particularly, if the analytics solution is equipped with machine learning capabilities, demand inventory uncertainties can be worked into forecasting plans by copying demand patterns for each individual SKU. This will provide a more accurate picture of future inventory needs, thereby helping to curb phantom inventory issues and save the associated costs.
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