Spotting and Solving Phantom Inventory


1. What is phantom inventory?

2. Why does phantom inventory happen?

3. How do you spot it?

4. How to fix the problem?

5. Tracking the results

6. Summary

What is phantom inventory?

Phantom Inventory (PI) is one of today’s leading causes of lost sales in the consumer goods industry. It occurs when automated replenishment systems show inventory at a store that, in reality, is not available. This false inventory prevents the automated replenishment systems from ordering and replenishing stock, even though shelves are empty. This Phantom Inventory leads to empty store shelves and lost sales at the cash register. It can also lower the sales forecast for items at the store, causing problems even after the inventory situation is fixed.

Did you know that roughly 3% of a retailer’s system’s inventory is likely phantom? This discrepancy can spike to 10% for faster-selling, heavily promoted items.

Now that people are comfortable being back in stores and supply chain issues are waning, having a strategy to combat Phantom Inventory is critical for consumer goods suppliers and retailers alike.

Why does phantom inventory happen?

Phantom inventory can occur as a result of several events, such as:

  • Misplaced inventory in a store’s stockroom
  • Incorrect receiving at the retailer
  • Lack of modular compliance within store shelves (i.e., retailer product with too many shelf facings or reduced shelf facings, product in the wrong location on the shelf or section of the store)
  • Loss of inventory because of damage, expiration, or theft
  • Incorrect scans at the point of purchase at the cash registers

Any of these situations could lead a retailer’s automated replenishment system to think that there’s inventory at a store and that there’s no need to replenish products when shelves are going to be empty and register rings are lost.

How do you spot it?

Phantom Inventory is difficult to find using typical methods because, as the name implies, it’s hidden. In most cases, if a popular item is out of stock on the shelf, it will be reported to a store clerk, and a manual order will be generated to fix the empty shelf. This gets actual inventory to the store, and sales will happen, but the underlying data error hasn’t been corrected, so that the out-of-stock will happen again. That’s why traditional methods of zero sales analysis won’t work, i.e., where suppliers identify when popular products haven’t sold for four weeks in a row.

Another difficulty spotting PI is when stock is split between multiple aisles, such as the impulse section, right before checking out. Again, this makes it challenging to spot inventory issues because you must account for stock in various registers.

To find and be able to fix the issues, a supplier needs an analytics system that can mine through the millions of rows of store and item POS data to detect the patterns that indicate Phantom Inventory problems. For example, a simple indicator of phantom inventory is seeing a plateau in available inventory and no sales registered for the item after previously seeing sales and steadily diminishing stock.

How to fix the problem?

The false inventory needs to be zeroed out in the stores to fix these issues, typically using a handheld scanner called a Telxon.
Once we’ve identified the issue and what needs to happen to fix it, it’s time to look at different approaches to solving phantom inventory.

Size of the Prize
First and foremost, we start with an audit. With this audit, we can pinpoint precisely where phantom inventory has occurred, to which products, for how long, and how much sales have been lost. The scope of lost sales helps us calculate the best method to fix the issue from an ROI perspective. The options and their relative pros and cons include:

Sending a manual order
Pros: The fastest and lowest cost way to fix the issue.
Cons: A band-aid solution that doesn’t usually solve the underlying false data issue.

Using a call center to contact stores and ask them to fix the issues
Pros: Lowers the cost of sending people to stores and does get the underlying problems fixed.
Cons: Typically, around a 30-50% success rate as store staff doesn’t always take action.

Going into stores to request Telxon updates.
Pros: An average success rate of 60-80% in fixing the problem and leading to the best sales lift.
Cons: The most expensive method. We need to make sure the sales lost from PI issues are worth the spend.

Getting retailers to issue a “need-to-count” in stores
Pros: The absolute best chance of success with more than 90% of the problem fixed.
Cons: It’s improbable that this can get accomplished due to utilizing the retailer’s staff to count each item manually.

Tracking the results

It’s crucial for teams to not only use analytics to find the problems but also to track the results of the fixes so that a spotlight can be shown on the improved sales numbers. For example, suppliers generally see a 30-50% sales lift after correcting on-shelf issues due to Phantom Inventory. By measuring the results, supplier teams can get buy-in from their executives and retail partners to continue attacking these issues.


Unfortunately, solving Phantom Inventory is not a one-time fix, as it will continue to occur due to the abovementioned issues. However, a regular regimen of finding and fixing Phantom Inventory can prevent negative impacts on the bottom line for the companies and improve the customer experience.