LPRC - CrimeScience – The Weekly Review – Episode 232 Ft. Walter Palmer

Episode Date: March 26, 2026

LIVE FROM 2026 LPRC IMPACT: In this special episode of the LPRC CrimeScience Podcast, host Dr. Cory Lowe is joined by Walter Palmer of CAP Index live from the 2026 LPRC IMPACT Conference. Tune in as they discuss the latest insights on risk, crime analytics, and how data-driven strategies are shaping the future of loss prevention. Don’t miss this on-the-ground conversation from one of the industry’s leading events.

Hi everyone and welcome to crime science. In this podcast, we explore the science of crime and the practical application of this science for loss prevention and asset protection practitioners as well as other professionals. Good morning, good afternoon and good evening everyone. Welcome to the crime science podcast. My name is Corey Lowe. I'm the director of research here at the LPRC. I have the distinct honor and pleasure to be joined today by Walter Palmer, senior advisor at

CAP Index. Walter, it's good to have you. Great to be here, Corey. It's been a great week here this week at Impact. Yes, sir. And it's been great to having CAP Index represented on stage and in many different ways. And we'll talk about that in just a moment. One of the things y'all did this

year, of course, there was a main stage session that featured CAP Index and all the wonderful work you'll do with risk modeling and just tremendous work you do there. But another thing that many people don't know about is that you actually actually led the leadership catalyst program. That was focused on getting stakeholder buy-in

when building business cases and then actually building a mock business case. What is one thing that retailers can do, in your opinion, to get buy-in internally when they're putting together their stakeholder strategy and their business case? Well, I think you used the exact right word their stakeholder. We spent a lot of time talking about stakeholder engagement. So when social scientists think about the ability to have influence, or they would call it the art of persuasion, there are two key prerequisites. One, you have to have expertise credibility. People have to believe you're knowledgeable about your domain expertise. And we didn't really spend a lot of time on that. We kind of took that as a given with the audience we have. But the other big prerequisite is

is relationship credibility. And that makes sense, but I think sometimes it's easy for that to get lost. So we spend a lot of time thinking about not thinking about change projects as being an asset protection project, but being an enterprise project. And so therefore, who are the stakeholders, who are going to be affected by this, what's going to be good for them, what's going to be bad for them, what are going to be the objections. And so I think there was a lot of, you know, when you're able to step away from the day to day, I think there's a lot of realization that, oh, man, I could do a better job at really engaging with other people and not.

And I think one of the other tendencies, and we talked about this a lot in the session, is sometimes when we know somebody's going to have some objections to the program, we try to stay away from them because we don't want to hear it. And what we really need to do is invite that in, understand it, see if we can engineer into the project a way to mitigate their concerns or at least be aware of them so that they can be heard and we can know what the lay of the land is. So, you know, we had a great group of people. They were super engaged, took the project super seriously. And, you know, we talked on the idea of an enterprise-level, complex change. But these same principles apply in your day-to-day business, right? You know, it's how do you build the relationship credibility so that people know that you play well in the sandbox because you can be brilliant at what you do.

But if everybody hate you, it's going to be very hard to have a lot of influence. So I think that's, I think that was probably the biggest key thing. We talked a little bit about how you build a business case financially, how you do some other things. But I think stakeholder engagement, I think that's exactly the right word. Yeah. And of course, that was just a very kind thing that you did to support that program for us. Of course, you were senior advisor at Cap Index and involved in a lot of great work there. You were talking about expertise, credibility, and relationships.

And I think that's what characterizes Cap Index. index in a lot of ways. With risk data, that's all bread and butter over there, how does that, can that provide the greatest value to organizations today? Something we covered on the stage yesterday, but can you explain some of that and take us into that? Well, I mean, I think the core value that the cap provides on its own is we collect a tremendous amount of external data. And so we're all about your external risk of crime where you're operating. And we do that really well. That's why so many people use us. But I think there's a couple of things.

Number one, and I want to go into how that integrates with what people's internal experiences, because I think that's very important. But one of the things I think people get confused about is they think, oh, we have big data. You know, we've been saying big data for years, and now we have AI. And so I think that's all great. but data has to be made actionable. And so there's this schema within the theoretical world that says there's data, but data has to be structured to become information,

and then information has to become knowledge, and knowledge eventually becomes insight. And that's where you can actually do something about it. So, you know, when we think about, like, people, let's say you have great, robust police data that's relatively current, and you can look at what we call dots on the map. Well, that's great, but how do you interpret that? What do you do with it?

Are those a lot of dots? Are those not very many dots? or the dots trending this way? Or, you know, are they affecting our operation or not? So I think providing a schema, whether you're doing this internally or whether we're doing it for you or whether we're doing combining the two things, I think the schema is the whole get, right?

Because you can have lots of data and have nothing you can do with it. Yeah, I had a fantastic professor at University of Florida, Moro Crone, who talked about the difference between theoretical modeling to test theory versus predictive modeling. I think that's what's so special about CAP Index is that you have some amazing criminologists on your team who not only understand how to build these predictive models,

but understand all the theories behind it and how it relates to prevention strategies. I think that's what's unique about CAP Index is just all that. I won't disagree. Because, again, the criminological theory helps you make the schema, right? So I think that's one. And then I think the other thing is, is, you know, what we encourage people to do, whether they do it engaged with us and our data or they do it on their own is, is it's not just enough to know your external risk. That doesn't take into account what you're doing to mitigate your risk. It doesn't take into account the nature of your operation.

You talked about that a little bit yesterday on stage. You know, are you right, you know, right next to, are you a liquor store or are you a jewelry store? Are you a financial institution? Those all bring different things into place. So I think you don't want to overcomplicate it, but I would never encourage anybody. I think I can say this, to just use CAP data by itself. I think it's a very powerful tool, and if you are going to rely on just one thing, it's not a bad thing to rely on.

But I wouldn't encourage anybody to just do that any more than I'd encourage them to rely just on their internal incidents or police data. I think you want to be a little bit more robust about that if you really want to build a risk model. Yes. And I wanted to come to that. We started off for the Leadership Catalyst Program, and I wanted to go to that question so I could come back to it and say, how is risk data related to building that business case and getting buy-in internally? Right. So I think it's a couple of things.

I think, number one, it's credibility, long-term, it's credibility because, number one, you have to have a pretty good track record over the long-term if you're going to continue to succeed in the corporate enterprise. And so the more intelligence you have around where you're going to put stuff and things that you can point to as far as your rationale, you know, one of the things that a lot of organizations struggle with, even today, you hear it all the time, is they make a lot of emotional decisions because of the nature of what we do. And certainly when something tragic happens in your operation, you have to respond to it. But it may not necessarily be something that should inform your long-term strategy, especially if you're not. it's a Black Swan event. So I think having a basis that you can say this is how we're making the decision is really important. And it takes some of the emotion out of it. It doesn't take it all out of the equation. But, you know, nobody has an unlimited budget. Nobody has unlimited resources. And so at some point you have to stratify your strategy with rare exception. And so therefore,

you have to have some basis for, again, whether it's whether Capp's part of that or whether Do you have something really robust? Internally, you have to have something that's consistent and repeatable to base your decisions on, I think. Yeah. You have to have a baseline to assess where things are going and what needs to be changed in your program. Now, you mentioned a few of these things, but I wanted to build on that a little bit more. Where do you see risk-based decision-making go wrong most often? Is it the interpretation of the data?

Is it misunderstandings of the nature of risk? Or is it something else entirely? I think my first reaction would be two extremes. One is the one-trick pony, which I talked about already a little bit, just relying on one measure, whether that's cap, whether it's your internal incidence, whether it's shrink. Shrink, as you talked about yesterday, is not a great proxy necessarily for violent crime because there's so many things that are baked into it. But I think it's being the one-trick pony is the first thing I'd say.

I think you can go too far the opposite direction, where you certainly when you're building a model, you want to ingest a lot of data. It's kind of a funnel approach. I don't know what the technical term for it would be. But the more data points you try to make part of your model, and I'm sure there's a statistical term for this, I don't know, but it kind of starts to wash out everything, right? Because it starts to weaken the predictive lift, right?

And so you want to evaluate a lot of stuff. Maybe you can comment on this. Does this sound correct? It's correct. But where it breaks down most of the time is in your ability to understand which predictors are most important and most related to it, so that you can focus on gathering that data in a very strategic kind of way. I can't imagine having a garbage can model where I just get every data point that I can from every open source and throw it into a model and hope to get

something that's actually that I can make meaningful. I need to know what predicts crime so that I can make sure that I'm collecting that data as the best predictor. And I think that's where, the theoretical modeling versus the predictive modeling, there has to be a pretty strong connection between both of those. And so understanding theory and what should be included and where you can refine your data collection strategies. That's what I would say. And I think the key part of that, as you mentioned it, is because you want it to be actionable.

Yes. And if you don't know out of these 200 variables what really is the driver, then what do I do with that information. So I think I'd say those two extremes and then I mentioned it overreaction, I think sometimes to specific events. Again, not that you have to do a reaction when something important happens, but should that drive your posture? We were looking at a location a couple of years ago and we were looking a lot of internal data, our data, crime data, and this particular location was spending an amazing amount of money in guarding and we couldn't see the reason for that in any data.

We actually did a Google search and what had happened was about five years previously there had been a carjacking in their parking lot and there was a little kid in the back seat the person didn't know about and they realized that at some point killed the kid. I mean this is just an awful, awful event, but it was very unrelated in lots of ways to that particular location. It happened off-site once it's going to the actual murder, and it wasn't the intent. And so the question becomes, okay, how long do you do guarding as a result of something that's catastrophic, tragic, but may not be an indicator of what the real risk is there going forward. And so those are tough decisions, and I think there's a lot of angst in making those decisions,

but that's where you have to figure out how to sort it out. Especially if you've put guards there and you've had a guard there and you have if you have no data to say, well, the risk is actually not there. There's no real reason for us to have a guard. It's really a comfort measure at this point rather than anything that's empirically based. Retailers need that. They need that justification to say there's no reason to have this here. So I need to understand that. one of the things you mentioned was making decisions based on sensational data or anecdote or one-off

off events I'm building a strategy around that. When I talk to you, one of the reasons I like spending time with you and reading the articles that you've written over the years because you're very operational-minded, you know, even keel thinking about the business. One of the things I've been thinking about a lot lately is the importance of doing the boring stuff really well, right? If you can do that, I think that there's a lot of benefit in that. What are some of the boring things that you think are most important for retailers to succeed with their LPA programs and beyond? Well, I mean, I think the question almost answers

itself, right? I mean, those boring things might be different by one type of retailer versus another. But, you know, if you think about, you know, the expertise, credibility, and the relationship credibility, the next thing I would add in in regards to being successful in the sector would be execution expertise, you know, being able to execute your programs. You know, even, you know, some might think, oh, well, Corey, you're a researcher. You're in a think tank. So you can just sit around and think of big ideas. And we know that's not true. There's lots of grunt work, boring work that you have to do even just for a research project. Literature review is probably not the most exciting thing you ever do, right? So I think execution focus, whatever those things are,

and I think it's always a balancing act, right? I think you come to a conference like OPRC Impact, you see all this innovation, you see cool new things, you see AI being operationalized, and that's important. But you can't get so focused on that that your team forgets what are the three core priorities, because it's those little misses that end up hurting your credibility over the the course of time. And I would say that's not just around LP-specific or security-specific things. But, you know, the locks have to work. The cameras have to work. You have to do investigations. These are not things that we would write about in Harvard Business Review, maybe, but these are fundamental to what our specific domain of expertise is. But I'd say for any executive, I think I would

add into there things like not missing deadlines, returning phone calls, you know, all those core things that kind of feed into that relationship credibility. Are you not only good at executing your loss prevention programs, but are you good at executing your business as an executive? And so, yeah, they aren't sexy necessarily. You know, relationship building is something you have to be intentional about and it doesn't pay immediate dividends. So is that a boring thing? Well, especially if you don't particularly like it, you know, or if you're in a remote work environment, You're going to have to be very intentional about that. So I think execution focus.

I don't know that I would list off these are the things, but I think what are the things that only you bring to the table for the organization? So, you know, when the pandemic happened and all of a sudden asset protection teams were being called on to figure out buy online, pick up in store, and curbside, and social distancing, I think we did really rose to the occasion, but I think if we didn't get everything right, I think there would be some forgiveness. we weren't expected to be an expert in communicable diseases and mitigation efforts. But I think those things that you're expected to be the expert on, then you better do those

things really well. So it's kind of an on-answer, but I think, you know, whatever it is for you, what are those core things that only you deliver to the organization? You've got to do those every day, every time. Yes, most definitely. Well, Walter, I appreciate everything that you're doing for the LPRC, everything that Captain X is doing. Appreciate the partnership, and I appreciate you spending some time with us today.

So thank you very much. Thank you, Corey. Congratulations on a great conference. Thank you. Thanks for listening to the Crime Science Podcast, presented by the Lost Prevention Research Council. If you enjoyed today's episode, you can find more crime science episodes and valuable information at LPRsearch.org. The content provided in the Crime Science podcast is for informational purposes only and is not a

substitute for legal, financial, or other advice. Views expressed by guests of the crime science podcast are those of the authors and do not reflect the opinions or positions of the Loss Prevention Research Council.