EVIDENCE-BASED LP

using Big Data for Precision Prevention Measures

Precision is always the goal. And the more we know, the better we’ll be. Today crime and loss problems are primarily defined by recent incidents and emerging patterns. This is good, but we can continue to get better. We can use the term “precision LP” (or “precision AP”) to label our efforts to first move to “evidence-based LP” using scores of LP studies to make better decisions, then push further to “precision LP.”

The goal of precision LP is to identify the underlying granular drivers of retail crime attempts, similarly to what is being done in certain subtypes of cancer for example. Understanding crime problems, or diseases, at the molecular level allows for much more precise diagnoses, targeted solutions, and, of course, much better prevention and recovery.

Precision LP will be based on future advances in understanding underlying causal mechanisms of our problems, like the interaction of surrounding offenders, their ease of access to our assets, how well we protect those assets, and how well we can learn and improve.

We will also need to do something else—share. And that means sharing good stuff. The real key to precision LP is having a central clearinghouse of studies. No single retailer or solution provider can provide the deep and wide data we will need to get very, very good at crime prevention, mitigation, and recovery. We will need to pull together third-party scientific as well as retailer-proprietary studies.

Big data are needed in other words. We will need to know how differing neighborhood settings, store types, merchandise mixes, manager priorities and skills, and protective techniques work alone and together.

The Rationale

Why do we want to go to the precision LP model? There are at least two reasons:

To truly maximize the impact, effectiveness, and ROI of protective treatments and

To minimize negative side effects like shopper and employee frustration and waste.

It is important to note that every location, management team, and problem is slightly…but importantly…different. This understanding is very important. It would be great if we could apply prevention measures across the board, but that will never deliver the results we and our management expect. So key precision elements include:

Correct understanding of the underlying causes of a specific problem.

Understanding how each problem has slightly different elements like we mentioned above. Neighborhoods, managers, and other factors vary, and this variation is really important to sustained success.

Assuming we select the right solution or combination of solutions, these measures need to be tweaked to affect that location’s problem.,

by Read Hayes, Ph.D., CPP

Dr. Hayes is director of the Loss Prevention Research Council and coordinator of the Loss Prevention Research Team at the University of Florida. He can be reached at 321-303-6193 or via email at rhayes@lpresearch.org. © 2013 Loss Prevention Research Council

Precision lP will be based on future advances in understanding underlying causal mechanisms of our problems, like the interaction of surrounding offenders, their ease of access to our assets, how well we protect those assets, and how well we can learn and improve.

Getting There

Like anything good, getting to a much more precise level of LP practice will take vision, time, and action. LP practitioners need much more information to make better decisions. As I mentioned, that information will need to come from individual retail organizations, be blinded as to source, be warehoused, and be analyzed along with collective study data to provide more in-depth information.

Take for example an LP department team that is meeting to form their next year’s strategy. They realize a particular product category’s losses are hindering sales along with profitability. The team then conducts their internal problem diagnostics, and then turns to

the precision LP data warehouse to look at their evidence-based options. They find three preventive options that have been extensively tested by several retailers and once by an independent organization. The team then chooses their top two options, and plans to assess those options in two or three locations. Pending that analysis, they may abandon one or more options, find ways to make them work in their stores, or go forward as is.

Following are some possible next steps to get us closer to precision LP at the industry level.

We don’t just need big data, we need little data, and, most importantly, we need to have all the data flow into a central, secure repository. We need practitioners and scientists alike to both feed into and have access to the data.

All retailers would feed in their test results via a web-based form that provides the research method and results without revealing the submitting retailer’s name.

We can also look toward bringing together data from broader studies and datasets like the University of

Florida’s National Retail Security Survey, the Centre for Retail Research’s Global Theft Barometer, the evolving National Shrink Database, LERPnet, and other sources.

We need scientists to evaluate the data and provide simple descriptions of what they find, and what those findings mean in practical terms for retailers. We then build a global best methods database. The

LPRC Research Fusion Center is helping to work toward that goal as part of this scenario.

We can work toward a comparative effectiveness matrix for common problems. For example, the truck hijacking problem might be addressed by a practitioner looking at several anti-hijack methods that have all been rigorously evaluated.

When you move from the industry to the retailer and solutions provider level, greater precision means consistently using the problem-solving techniques discussed here and elsewhere like SARA (scan, analyze, respond, assess) to really identify problem causes, and then focus solutions. Ideally, this means in-house assessments should be fairly rigorous, including using control locations to rule out many other causes of observed outcomes. And then as mentioned, retailers and their vendor partners should submit their findings to the data warehouse.

Concept to Action

These are my initial thoughts on how we can all keep moving our discipline toward greater precision and even better results. Please send your thoughts and suggestions to rhayes@lpresearch.org. Also, please contact us if you have interest in participating in this year’s LPRC Impact conference at the University of Florida, October 14 – 16.

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