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Have you ever faced the problem in your manufacturing or retail location, when a particular item is showing in the stock in your accounting system and yet you can’t find it anywhere? Is the stock showing in records an illusion or a figment of our imagination, or does it really exist?

Inventory that shows to be on-hand in the company’s accounting system, but in reality are not available, is categorized as phantom inventory.

Inventory that shows to be on-hand in the company’s accounting system, but in reality are not available, is categorized as phantom inventory. Click To Tweet

This can occur due to a variety of reasons like items being moved without appropriate changes recorded in the system, breakage, theft, deliberate fraud or data entry errors.

Irrespective of the cause behind it, phantom inventory results in a discrepancy between the actual physical inventory and the inventory records, thus resulting in out-of-stock incidents, and if left unnoticed and not addressed timely, it can lead to bigger issues like accounting restatements and adjustments.

There are certain solutions and technologies that can help companies with inventory accuracy, like frequent physical inventory cycle counts, RFID technology, statistical modeling, etc.

Spotting Phantom Inventory:

Either deliberate fraud or mistaken inventory information recording, phantom inventory needs to be spotted and controlled timely to contain the corresponding potential losses.

There are certain steps that companies can take to counter phantom inventory instances in their facilities, be it manufacturing or retail:

• Look for instances where the company is trying to obtain finances based on its inventory, as they might get tempted to inflate their inventory balance.

• Look for instances of inventory theft. Missing packing slips and sales receipts, the standard of living of employees extraordinarily high, lost goods complaints by the customers, a high number of damaged items and steep sales drop in high sales seasons are all indicative factors of inventory thefts.

• Look of overstated or understated ending inventory.

• Also, stagnant inventory balances in financial statements over several consecutive financial years, and inventory levels raising more than the sales figures are also indicative of phantom inventory instances.

• Look for unusual outcomes or trends in the inventory related financial ratios calculated. For instance, inventory turnover ratio showing sudden changes, the discrepancy in COGS between company records and tax returns, shipping costs reducing to a percentage of inventory, etc. are all instances indicating towards phantom inventory.

• Look for incorrect or falsified purchase orders, bogus reporting, inflated inventory, etc.

Effect on Manufacturing & Retail:

Even a small rate of stock loss undetected by the information system can lead to inventory inaccuracy that disrupts the replenishment process and creates severe out-of-stock situations. In fact, revenue losses due to out-of-stock situations can far outweigh the stock losses themselves (Kang, Gershwin 2007).

Companies rely on automated inventory management processes and systems for strategic decision making. However, phantom inventory instances due to information inaccuracy hamper the system’s ability to perform, leading to stock-outs, loss of sales and customers, and eventually monumental revenue losses. System’s performance sensitivity to inventory information accuracy becomes much more heightened in manufacturing facilities and retail outlets following lean systems.

With every 1% increase in product visibility, the sales can go up by 0.5%. Click To Tweet

Hence, the occurrence of phantom inventory instances can cause humongous potential sales losses. Phantom inventory at times also leads to no sales of a particular item from the retail shelves, which might lead to the delisting of the item, which might be in demand. Or if the system studies availability from the records for new orders, phantom inventory will show the product available in inventory data, even when not on shelves, leading to no further orders for it, yet again resulting in lost sales.

International industry average out of stock level is around 8%, but in India, it is an alarming 25-30%.

Where does your company stand? Vigilant staff and accurate information recording can help you timely identify and correct the errors, and thus improve your sales many folds.


If you have any thoughts about this topic, feel free to comment below.




Joseph T. Wells (Jun 2001). Ghost Goods: How to spot phantom inventory. Journal of Accountancy, New York 191.6. pages: 33-36. Retrieved from:

Bill C. Hardgrave, John Aloysius, Sandeep Goyal (06 July 2008). Does RFID improve inventory accuracy? A preliminary analysis. International Journal of RF Technologies: Research and Applications. Volume 1,2009. Issue 1. Pages: 44-56. doi: 10.1080/17545730802338333

David C. Twist, (2005). The impact of radio frequency identification on supply chain facilities. Journal of Facilities Management. Volume 3. Issue 3. Pages: 226 – 239. doi: 10.1108/14725960510808491

Yun Kang, Stanley B. Gershwin (23 Feb 2007). Information inaccuracy in inventory systems: stock loss and stockout. IIE transactions. Volume 37, issue 9. Pages: 843-859. doi: 10.1080/07408170590969861

Mahimm Gupta (April 25, 2016). What’s the impact of phantom inventory on your availability. Retrieved from:

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  1. Rohit Abhishek says

    The difficulty of tracking fabric if in weight must be highlighted in the current times. It becomes impossible to track the exact fabric received, resulting in huge wastage and unaccounted fabric.

  2. Frank Lomax says

    Some easily found examples of ‘Phantom Inventory or Stock Loss’ that I uncovered during my career in Management were:
    Factory 1
    a. Tubular Knitted Sweatshirt Fabric was only controlled by Total Weight and an estimate of Meters per Kilo issued by the Fabric Mill..
    Batches of fabric rolls were sent to an External Dye House by Gross weight.
    Business Management had been convinced to believe that due to process shrinkage each roll lost weight during the process.
    One roll from each batch sent was being stolen and the reduced weight returned to the factory.
    Management had not realised that while the Unmeasured Meters of Fabric may reduce, the weight would not reduce but could increase due to the addition of the dyestuff.
    b. In the same Garment Factory, Cut Order planning Printed Piecework Payment Control Tickets for each batch prior to cutting the garments.
    After Cutting a Cut Piece Inspection Process removed panels which were damaged from each bundle. All Panels from that size were removed.
    The bundle ticket quantity remained unchanged.
    Panels from the Damaged sizes were sorted and good panels were matched to make complete garments.
    A new Bundle ticket was issued for these ‘Extra’ garments introducing Phantom Stock by both steps. Operators were being paid twice for making garments which did not exist.
    A investigation to find the ‘Missing Garments’ unearthed both practises.
    Factory 2.
    c. An investigation of Garment Losses in another factory unearthed 3 unrecorded system abuses following issue of a Garment Cut Plan quantity.
    1. The Fabric Store Manager only issued fabric to the nearest whole roll which in most cases was not sufficient to complete the order quantity.
    2. Machinists ‘Hid’ garments or parts of garments returned to them for repair but the bundle ticket used for payment and stock movement recording continued unchanged.
    Orders were never ‘completed’ and theft on a grand scale was anticipated but never found.
    3. Complete and Exact garment quantities of Despatched Garments never matched the Paperwork when they reached the Retail Warehouse.
    After a ‘Van Security System’ was introduced to prevent Theft, It was found that the Paperwork was always incorrect and did not match the actual garments in the Van
    The Warehouse Manager, who recorded the Despatch Quantities, then admitted ‘in tears’ that he just ‘Could Not Count’. No one had known of this problem.
    A separate Clerical Function was introduced and this problem solved.


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