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How to Profit from Your Loss Prevention Strategy

Analytics and retail: a match made for success. Yet the one mistake retailers make is investing in outdated, exception-based, long-form reporting tools. Prescriptive analytics is one solution that saves retailers valuable time and resources by picking up on irregular patterns. It’s no surprise that Gartner predicts the market will reach $1.1 billion by 2019.

Successful retailers work tirelessly to innovate their big data strategy, but they often miss a vital component: without actionable insights, brands lose revenue and fail to leverage the resources they currently have. To provide a real-world example, grocery stores experience a high amount of the different inventory shrinkage buckets on an everyday basis. Once a particular grocer started using prescriptive analytics, the company was able to pick up on a suspicious delivery, where the retailer was paying for a large size of a shipment of a product but only receiving a small package. An issue that otherwise may go unnoticed and seem minuscule allowed the grocery store to recoup $120,000 from the vendor who had shipped them the incorrectly sized product. If a prescriptive analytics solution hadn’t been in place, this problem would have cost the grocer nearly a million dollars annually.

This example proves it’s about putting the right action in place for a particular employee to take. Another issue plaguing retailers is that more than half of all reports are never even opened. If the report is actually opened, does the person analyzing it understand the data sets? Is the insight readable by the person reviewing the report? Does the person understand what he/she should do to execute on the opportunity? Did the person execute well and deliver the value? These are the key questions retailers should be asking pertaining to analyzing complex data sets and finding irregular patterns.

- Digital Partner -

When it comes to reducing shrink, retailers would agree that finding an easy-to-use, everyday solution is an important component for them. With fashion retailers that have both a brick-and-mortar and an online presence, prescriptive analytics have the ability to identify the particular products that aren’t performing well. For example, a certain pair of shorts that sees a high return rate online should be pulled from both the website and stores. Why? The retailer is losing a significant amount of money selling this product that is being returned and customers aren’t happy with their purchase, which decreases the satisfaction rate. As we know, shrink measures against sales; when sales go down, shrink goes up.

Prescriptive analytics is the next wave of loss prevention strategy and exception-based reporting (EBR) innovation for the simple reason that it allows retailers to identify abnormal issues, inefficiencies and opportunities to improve when it comes to total loss and shrink. At the end of the day, retailers want to increase sales and customer satisfaction while decreasing fraud and shrink. Prescriptive analytics allows this change to take place.

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