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Using Inventory Analysis to Untangle Fraud at 7-Eleven

According to the most recent data, the US retail industry loses nearly $60 billion annually due to shrinkage. As part of an increased focus on monitoring shrinkage loss, the University of Texas Master of Science in Business Analytics (MSBA) program partnered with 7-Eleven to better understand how fraudulent activity relates to inventory loss.

Over the course of four months, students in the UT MSBA program worked closely with asset protection professionals at 7-Eleven to fully understand the organization’s business model and develop hypotheses about how analytics might be used to identify fraudulent activity.

The task was not an easy one. An in-depth article in the November-December issue of LP Magazine details the exploratory research methods undertaken by the group. From the article:

“Because not all SRA [sales reducing activity], inventory variation, and cash purchases are tied to fraudulent activity, we needed to take a methodical approach to untangle the complexities of the problem and better understand how all of these factors interrelate. Most importantly, we wanted to ensure that the results of our analysis made sense within the context of the business. Specifically, we wanted to filter and hone in on the instances of inventory variation that are caused by fraudulent SRA and the associated cash purchases used to cover them up. To do this, we transformed and merged multiple data sets from 7-Eleven that contained two years of financial and SRA data for stores located in the Texas market.”

The findings and conclusions of the research study were presented at the 2016 Retail Industry Leaders Association (RILA) Asset Protection Conference and are also shared in the article. Read “Predictive Data Analytics” to review the promising insights and takeaways from the inventory analysis study. You can also check out the other articles in the November-December 2016 issue. Not subscribed yet? No problem – register here for free.

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