LP Magazine

SEP-OCT 2018

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.

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PARTNERING SCIENCE, DATA, AND ASSET PROTECTION TO TACKLE RETAIL SHRINK nearly impossible to determine the original vendor once the product is on display leading to overlap or confusion between different items and different vendors. Due to these and related issues, the physical inventory conducted every cycle faces similar limitations. Another common issue with produce is the exchange between different categories. For example, a store may order organic grapes but receive regular grapes. This can lead to inconsistencies in billing for inventory and sales. Further, an item can be modified in some manner leading to a different label when the item is finally sold. For example, whole pineapple is cut and sold as precut fruit to customers. Similar issues happen with juice bars, prepared foods, and the deli. Kroger is aware of these issues and makes corrections to their financial records at the commodity level. However, these corrections cannot fully capture all the unique scenarios that arise in produce retail and cause noise in the data. Additionally, it's not uncommon to see negative inventory figures as a result. To compensate for these issues, we have rolled the data up to higher levels, joining items or subcommodities together, or averaging over longer periods of time. This reduces the noise and extracts a stronger signal from the data but also conservatively limits our analysis and recommendations. We elected to provide higher-level analysis for the data at a level we are comfortable with, rather than risk overfitting our models to extremely noisy item- or cycle-level data. These decisions are supported by cross-validation and out-of-sample testing during our analysis. Experience at the RILA Conference Our presentation was scheduled for the afternoon of day one of the Retail Industry Leaders Association (RILA) conference in Orlando. As part of the conference, we had the opportunity to attend a plethora of events, ranging from talks given by distinguished speakers from the retail industry, to networking events where we could meet people and exchange information regarding the innovations in the retail industry. We presented our findings to a crowd filled with experts from the retail industry. It was well received and a proud moment for the team. The conference also had an exhibition hall with solution providers showcasing their products. Donning different caps for each event, we loved learning something new from each and every person we met. Overall, it was a great learning experience and we enjoyed the conference thoroughly. Final Thoughts Our project benefitted immensely from a close partnership with the Kroger team and their willingness to provide support and in-depth information. Many of the most rewarding aspects of our work were only possible because Kroger was willing to provide us with weekly sales data for each item at every store. The success of every analytics project depends on the quality of the data, and we were fortunate to have access to such detailed records. "We were delighted to support this initiative, both for the benefit of the Decision Tree: Which low-shrink stores have above-average performance? Store Mask Store Type Shrink Sales Inventory Ratings Turnover GM% $/Produce SQFT ????? 3 00033 3 00182 3 00070 3 00095 2 00093 3 00003 2 00104 3 00079 1 00008 5 00183 3 00165 4 00010 3 00094 4 00059 3 00102 3 00029 3 00078 2 00125 2 00124 3 00047 2 00056 3 00177 3 00184 3 Inventory Category | Ratings Category | Turnover Category | Shrink Category | Sales Category Above Average Average Below Average 46 SEPTEMBER–OCTOBER | LOSSPREVENTIONMEDIA.COM continued on page 48

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