LP Magazine

JUL-AUG 2019

LP magazine publishes articles for loss prevention, asset protection, and retail professionals covering shrinkage, investigations, shoplifting, internal theft, fraud, technology, best practices, and career development.

Issue link: http://digital.lpportal.com/i/1146652

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Page 22 of 76

more video analytics into its investigative processes. Bloomingdale's is also taking advantage of the "monumental changes" in video analytics that Gonzalez sees. "Who is lingering in what area, putting two things in the bag and ringing up just one—the technology of the cameras and the ability to translate that video information into numbers for analysis is allowing for a much better understanding of what's happening in our environment," he explained. Retailers are also pulling in data from facial recognition or other identification solutions. Using such tools can permit ORC investigators to piece together crime events, each one of which could be its own police report, in a more comprehensive way—to fundamentally disrupt an ORC operation rather than make a single arrest. Managing the privacy component of this and other identification technologies will be a test for retailers and could be a near-term drag on adoption, said some LP leaders. The quality of analytic dashboards grows more important, as even more data heads LP's way. Continuous analytics of all sales reducing activities (SRAs) and related data is inevitable in retail, as it provides a reliable, economical way to fix systemic problems, reduce shrink, and ultimately improve profits. Eventually, all data correlates with future sales figures. Machine learning and artificial intelligence (AI) is also transforming the analytics landscape. Leading global retailers are already leveraging it for a variety of purposes. For example, a mix of accelerated analytics and deep learning is helping retailers with pricing strategies, and retailers are running daily profit-optimization calculations to know how best to distribute which products to which stores. Online, AI works on customer data to help retailers provide more personalized shopping experiences and to help e-commerce platforms adapt to the needs and interest of online shoppers. AI can also fuel predictive price and forecast simulations to boost revenue by fractions of a percent, which for giant retailers can add up to millions. For loss prevention, these advances lay the groundwork for increasingly smart pattern detection in retail transactions. Models become more capable over time at identifying previously undetected fraud patterns and better at distinguishing between problematic and legitimate transactions. Previously hard-to-identify collusion cases—those spread across large numbers of customers, for example—are drawn into sharp ANALYTICS IS NOT JUST A NUMBER'S GAME Analytical Cyber Security Investigative Computer Skills Leadership Emotional Intelligence Interviewing Other 62% 40% 35% 33% 29% 29% 16% Skills Needed by LP Departments, 2019* *For programs to be successful or grow Source: 2019 National Retail Security Survey, National Retail Federation; University of Florida 5% 70% 50% 30% 10% 0% 22 JULY–AUGUST 2019 | LOSSPREVENTIONMEDIA.COM

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