Blog: Tackling Shrinkage with AI

Specifically, the message was that retailers need to sort out what exactly to do with it all—particularly now that they’re faced with a rapidly growing range of solutions. That requires a careful understanding of one’s goals, including what AI is currently equipped to do for retailers (and what it isn’t).

Understanding your goals often begins with understanding your problems. For retailers, one growing problem has been shrinkage at various touch points within the retail environment. 

The National Retail Federation’s most recent National Retail Security Survey found that “the average shrink rate in FY 2022 increased to 1.6%, up from 1.4% in FY 2021. When taken as a percentage of total retail sales in 2022, that shrink represents $112.1 billion in losses.”

Other indicators of the rise in retail theft are even more dramatic, though there is debate as to how to best measure it. One recent New York Times piece reported that shoplifting complaints have almost doubled according to NYC police data, while notable incidents such as the closing of a historic Nike outlet in Portland due to an alleged ‘spike in theft’ have gained more public attention.

However you measure or understand the problem, at a time when pressures on the bottom line aren’t letting up, retailers can’t afford to let drains on profitability go—especially as they continue to automate stores and as self-service technologies rise in popularity.

Retailers can also find both intentional and unintentional shrink in self-checkout lanes. The two types require different responses, particularly so as to not alienate customers. AI can help provide solutions to both. Furthermore, the problem goes beyond self-checkout, though it has received the most attention of late due to media coverage. Here again, AI has the capability to monitor for and help to address all forms of shrinkage found in stores.

One of Diebold Nixdorf’s latest solutions—Vynamic^® Smart Vision | Shrink Reduction—is an AI-powered declaration of war on shrinkage at the point of self-checkout, and it couldn’t have come at a better time, aimed at decreasing friction at self-checkout while increasing security and combating shrinkage. 

Powered by SeeChange’s AI and machine learning, cloud-based platform, the solution exists to truly evolve what has long been a common pain point for customers: lumbering self-checkout solutions that require too much input.

By bringing together a range of technologies into one integrated, smart, AI-driven package, Diebold Nixdorf’s offering can make (e.g.) produce scanning, age verification, and other common pain points in traditional self-service checkout a thing of the past by intelligently automating those services, and all while monitoring for theft. 

“We designed our new AI-powered offerings based on insights we’ve gained deploying millions of PoS and thousands of self-checkouts across the major retailers we work with,” Redwood continues.

“We’ve left no stone unturned when it comes to enhancing customer and employee experiences, as well as retailers’ need to scale easily and improve efficiency.”

While the war against shrinkage in the retail industry is undoubtedly set to continue evolving in response to a wide and difficult-to-predict set of scenarios, and while it may never be feasible to prevent all forms of shrinkage, state of the art AI solutions can help to prevent the bulk of those losses in the retail storefronts of today and tomorrow in a way that was once science fiction. 

To explore more about how AI is shaping the retail industry’s future, download our latest industry report, or contact us today to speak with a retail expert.  


Original published in RETHINK Retail