Inventory Anomalies In Retail

Inventory anomalies are discrepancies that occur in companies’ inventory records compared to physical reality at the store level. This can happen for a variety of reasons, such as errors in the tracking system, theft, or simply misplacing items. These discrepancies can lead to problems for a company, such as lost profits, dissatisfied customers, and damage to the company’s reputation.

One way that companies can prevent this is by implementing an intelligent inventory management system that is built in conjunction with traditional fulfillment system. In addition to regular physical counts of the inventory, as well as using technology such as RFID and portable barcode scanners, Retailers can use sophisticated artificial intelligence models to help predict potential issues. By accurately tracking their inventory, companies can ensure that they have the right products in stock to meet customer demand and can avoid the negative consequences of inventory anomalies.

Another way to mitigate this issue is by implementing strict controls on access to the inventory. This can include security measures such as cameras and alarms, as well as tracking who has access to the inventory and when they accessed it. By limiting access to the inventory, companies can reduce the risk of theft or other forms of inventory loss. Unfortunately, this is often not feasible due to the scope of the Retail chain and variety of SKUs they are selling.

Overall, inventory anomalies are a problem that can have serious consequences for businesses. By implementing intelligent inventory management systems and controls, companies can minimize the risk of inventory issues and ensure the smooth operation of their business without fear for stockouts and customer dissatisfaction and lost revenue.

Remediating Inventory Anomalies

There are several potential ways that Retail companies can remediate anomalies including phantom inventory:

  • Conduct a physical count of the inventory: One of the most effective ways to remediate inventory issues is by physically counting the inventory. This can help to identify any discrepancies between the recorded inventory and the actual inventory on hand. This is usually the most accurate but also most costly way to solve the issue.
  • Implement an intelligent inventory management system: integrating all the information Retailer collects across its systems and store network an artificial intelligence powered inventory management system can help identify and predict where the issues might arise allowing for timely remediation by fulfillment and local store management.
  • Improve inventory accuracy: Retailers can improve the accuracy of their inventory records by implementing measures such as RFID labels, barcode scanners and electronic data interchange (EDI).
  • Improve inventory controls: Implementing strict controls on access to the inventory, such as security cameras and alarms, can help to reduce the risk of theft or other forms of inventory loss.
  • Conduct regular inventory audits: Regularly reviewing and auditing inventory records can help to identify and correct any discrepancies.
  • Train employees: Providing training to employees on proper inventory management techniques can help to reduce the risk of phantom inventory.
  • Identify and address root causes: To fully remediate issues including phantom inventory, it is important to identify and address the root causes of the problem. This involves reviewing metrics, processes, and procedures, identifying, and addressing any bottlenecks, and implementing corrective action.

How can AI/ML help?

Artificial intelligence (AI) and machine learning (ML) can be useful tools for helping Retailers to manage and reduce the risk of inventory anomalies including phantom inventory. Here are a few ways that AI and ML can be used:

  • Predictive inventory management: AI and ML algorithms can analyze past sales data and other factors to predict future demand for products. This can help Retailers to optimize their inventory levels and reduce the risk of overstocking or understocking.
  • Inventory optimization: AI and ML algorithms can help Retailers to optimize their inventory by identifying slow-moving or excess inventory and making recommendations for how to dispose of it.
  • Inventory tracking: AI and ML-powered systems can be used to track inventory in real-time, helping Retailers to quickly identify and address any discrepancies.
  • Fraud detection: AI and ML algorithms can be used to detect patterns of suspicious activity, such as inventory theft or fraudulent returns.

Combining the above approaches with a solid integrated data program, organizations can identify and predict specific stores and/or SKUs with inventory issues. Overall, AI and ML are powerful tools for helping Retailers to improve their inventory management and reduce the risk of phantom inventory. By leveraging these technologies, Retailers can gain a more accurate and up-to-date view of their inventory and make more informed decisions about how to manage it. Due to the specific nature of Retail organizations, there’s a need for services supported approach as “out-of-the-box” models rarely serve the nuances of leading Retailers.

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