THE MAGAZINE

New Solutions to Old Problems

By Ann Longmore-Etheridge
The latest National Retail Security Survey confirms what most retailers know instinctively: Retail shrink continues to rise. The survey, released in June, puts 2008 losses at $36.5 billion, up from $34.8 billion in 2007.
 
Companies don’t just passively accept the status quo, however. They constantly adjust their countermeasures in an effort to hold shrink to a manageable level. The companies highlighted in this article say that new technologies have made a substantial difference in the ongoing war against shrink. The following case studies illustrate how implementation of some of these measures is working.

Souring the Sweethearts
 
Big Y Foods, Inc., is an independently owned regional supermarket chain with 58 stores in Massachusetts and Connecticut. According to the company’s director of loss prevention, Mark L. Gaudette, “Retailers know that a lot of shrink is caused by employees. No matter whose survey you look at, it’s always about 40 to 45 percent.”
 
Solutions such as access control, CCTV, and exception reporting—which highlights irregular transactions—have helped to address the problem. However, Gaudette says, “One area where there was still a big void in loss prevention was ‘sweethearting’ at point-of-sale (POS) stations.”
 
Sweethearting is when a cashier does not scan an item before placing it in the shopping bag, thus giving it to the customer for free. Exception reporting systems cannot catch sweethearting, Gaud­ette explains, “because if an item isn’t scanned, it doesn’t become part of the aggregate, and therefore, it can’t be measured.”
 
While it’s possible that the theft may have been caught with surveillance equipment, trying to catch sweethearting incidents by reviewing CCTV video of all transactions would take resources far greater than those of the average retail security and loss prevention operation.
 
That’s assuming the review would have to be carried out by a human. Newer video analytics technology, however, offers a way to automate at least the front end of that process so that the amount of video a human has to review is limited to what has been flagged as suspicious.
 
One product that is specifically designed to address the problem of sweethearting is the StopLift Checkout Vision System by StopLift, Inc. The software mathematically analyzes the pixels of digitized video, scrutinizing how cashiers handle items to determine whether or not they have properly scanned them. This type of analytic had not been previously available, according to Gaudette.
 
Big Y decided to pilot the system, which consists of an appliance with the analytic and a monthly service contract providing that StopLift personnel at a central station would review footage flagged as suspicious by the analytic and cull out false alarms. The pilot was carried out in three stores for four months beginning in September 2008. Employees were not informed that StopLift had been installed at the stores.
 
Installation was simple. There were no requirements on camera type or resolution but, says Gaudette, “We had to have CCTV in place that gave a straight dropdown shot of each register.” After that, all it took was plugging the store’s digital video recorders (DVRs) into Stop­lift’s appliance, which housed the analytic software.
 
Each day, the data is sent via the Internet to StopLift’s data center. There, suspicious transactions flagged by the analytics are reviewed by human analysts who confirm or negate them. “They take out the false positives,” says Gaudette. “For example, they make sure it isn’t a pocketbook placed accidently over the scanner.”
 
Other commonly flagged transactions involve free publications. For instance, “Big Y produces a magazine with recipes and coupons…. It looks like a Sports Illustrated or a Woman’s Day going across the belt. We provide that information to Stop­Lift so that their reviewers can look at it and say, ‘Oh… it’s the free magazine and not sweethearting.’”
 

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