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How Retailers Might Use Store-Level Risk Data: A Study

More and more, retailers are choosing to assign risk and vulnerability scores to their store locations. Risk profile data may depend on factors such as a given location’s relative exposure and accessibility to local offenders. In terms of vulnerability, a score may depend on factors such as how well a store is prepared to respond to a crime incident.

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In a column in the November–December 2017 issue of LP Magazine, Read Hayes, PhD, CPP, shares the results of a recent study conducted by the Loss Prevention Research Council (LPRC) on whether and how retailers segregate their stores according to metrics relating to risk and vulnerability.

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From the column:

Study Method: Loss prevention executives from twenty-one companies in six categories (mass merchants, department stores, drug stores, apparel stores, specialty stores, and grocery and dollar stores) completed surveys.

Results: Almost all the retailers we talked to use some process and data to evaluate each store’s relative risk and vulnerability. Following are some study highlights.

By far, the type of risk data most likely to be collected by the participating companies is actual loss/shrink, collected by almost all (95.2%) of the participants. More than two-thirds (71.4%) of the loss prevention executives indicate they collect data on the number of incidents by crime, and a similar percentage (66.7%) collects data on the number of accidents at the store level.

Approximately four-fifths (81.0%) of the LP executives surveyed indicate they use the risk data they collect at the store level to make a risk profile for each store or to classify stores into categories. Nearly three-fifths (58.8%) of the companies who report using store-level risk data to classify their stores have three classification levels based on this data. Nearly one-quarter (23.5%) of these respondents have five classification levels based on store-level risk data. The most typical classification schemes are ordered number or letter categories such as “1, 2, 3, 4, 5” or “A, B, C” or categorical ranking schemes such as “low, medium, high.”

See more takeaways from the study, as well as what’s next for the LPRC (hint: it’s a new online course!) and this issue’s recommended reading in “Training Makes a Difference.”

You can also visit the Table of Contents for the November–December 2017 issue or register for a free subscription to the magazine.

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