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RILA Student Mentor Program and The Kroger Co Tackle Grocery Shrink with Data

As those working in the grocery industry know, the perishable nature of merchandise in the produce department make it susceptible to greater loss numbers compared to the organization as a whole. In an attempt to tackle grocery shrink within the produce department, students from the Retail Industry Leaders Association (RILA) Student Mentor program worked alongside the asset protection team from The Kroger Co. The research team collaborated to dig deep into the data and use predictive modeling to help make recommendations about problem areas.

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This research was presented at the 2018 RILA Asset Protection Conference and is now the focus of a feature article within the September-October 2018 issue of LP Magazine. Written by the students themselves, all budding data scientists at the University of Texas, the article delves into an exploratory data analysis, a more granular review of item-level information, and an explanation of the predictive modeling used to inform their recommendations on grocery shrink. From the article:

Our first step was to better understand the business and determine the need. Due to the lack of bar codes, the variety of products and vendors, and the perishable nature of the products, produce department data can be extremely problematic. We needed to understand the departmental structure at Kroger, financial data, how Kroger measures and records produce inventory, and how to calculate shrinkage at a granular level. This information played a crucial role in understanding which questions to ask next, which direction to take the analysis, and ultimately which recommendations to provide.

Good practice dictates exploratory data analysis (EDA) when starting any analytics project to better understand your data. As a first step in our data analysis we decided to analyze data at the overall store level, focusing on the big picture and looking at trends that affected each location as a whole. Our questions included:

  • Which stores were performing the best and worst in terms of shrink results?
  • Do these stores have any clear physical relationship?
  • How do average shrink results vary depending on store type, produce square footage, number of deliveries per week, and seasonal considerations?
  • Are there correlations between produce freshness and wastage?
- Digital Partner -

Check out the full article, “Partnering Science, Data, and Asset Protection to Tackle Retail Shrink,” to see what interesting takeaways were uncovered in the research process.

For more great LP content, visit the Table of Contents for the September–October 2018 issue or register for a FREE print or digital subscription to the magazine. [Note: if you’re already a logged-in subscriber, the previous link will take you to the current issue instead.]

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