How do you know what you know? Have you read it somewhere in a book or online? Did you hear it from a friend or family member? Did you witness it yourself? Did someone you respect reassure you that’s just how it works? Or perhaps it’s a mixture of all these sources?
More likely than not, you learn about the world around you via a mixture of what you experience, the type of media you consume, and the social networks you use. What about within loss prevention? How do you know “what works and what doesn’t”? Have you gone through training on how to conduct investigations? Have you searched for information on your own, or have you asked senior members of your team for advice on what to do?
All of these are ways in which we interpret the world around us and learn what is going on. Another way to learn about the world is through research, and it is very likely that research touches on all the previous ways mentioned (such as the news, friends and family, etc.) However, what makes research so different from all those other sources? Why should we value its input? To better understand why, it is important to understand what it is first.
What Is Research?
Research is a systematic way to study something to determine new facts on a particular topic. It is generally considered “empirical,” which means it is rooted in experiences rather than logical conclusions (think philosophy for the latter). In social science, we often suggest there are four main types of social research.
- Exploratory: concerned about investigating a topic without prior assumptions
- Descriptive: concerned about the frequency or characteristics of a phenomenon
- Explanatory: concerned about finding the cause and effect of something
- Evaluative or Applied: concerned about the effects and impacts of a program or intervention
Research, then, tries to determine the characteristics of a phenomenon, and the “why and how” of its occurrence. No matter the type of research, all of those “things” must be measured in some way, such as through a survey, by asking questions, or witnessing it with our own sense. When we conduct research, we often will first need to make sure we can define what it is we are interested in studying (and there are often debates in research about whether those things are measured correctly. At the end of it all, though, research needs to answer certain questions so that we have a better understanding of what is happening.
We can use an example to illustrate this point. Suppose we are curious about the relationship between drug use and crime. Do you think:
- Drug use ultimately leads to crime?
- Crime ultimately leads to drug use?
- There is a feedback loop between drug use and crime?
- There is something else that influences both drug use and crime?
- It is just a coincidence if there is drug use and crime?
Research tends to find that it’s unclear what is happening between drug use and crime. Some studies find there is a relationship where drug addicts and high-rate users of drugs tend to engage in “income-generating” crimes (like theft). Others have found the opposite—that crime preceded the onset of drug use. These are called “direct effects,” where one “effect” will lead to the other.
When looking at violent crimes instead, some studies have found that drug use may influence our thoughts and feelings on violence (increasing them). That increase in violent thoughts can then increase the likelihood of violent behavior. In this way, drug use is not directly causing violent behavior; rather, it is altering our thoughts, which then alters our behavior. This “pathway” of change is generally called an “indirect effect” in research because, in this case, drug use is indirectly influencing violent behavior through a change in our thoughts.
What if instead there is a feedback loop, where initial drug use leads to crime, and that crime leads back to further drug use? Some studies have found this exact process, especially in terms of those “income-generating” events mentioned earlier. In that case, offenders need money to feed their addiction, so they use crime to obtain money to purchase drugs. Once they need more drugs because of that addiction, the cycle repeats itself. This is known as a “reciprocal effect” in research.
However, what if there were factors that influenced both drug use and crime, but they do not interact with each other? For example, some studies have found that our peers (especially when we’re juveniles) can influence our drug use and whether we engage in delinquency. Drug use and crime, then, are independently influenced by our peer groups separate from each other. This is known as a “spurious effect,” and it is the bane of all research. You may have heard the expression “correlation is not causation”—it stems from this concern that just because we identify a relationship between two variables does not inherently mean that one causes the other. That requires additional conditions that certain research methods can accomplish.
After all this, you may be wondering why we bother doing any research at all if it does not always neatly answer our questions. It is certainly a valid question, and, as a research scientist, I often have to navigate how to give a concise answer despite recognizing and knowing the challenges with all this conflicting information. However, research has many benefits to us within the loss prevention field. Below are five reasons why research is important for us to consider.
Reason 1: Research Avoids Our Natural Biases
We all make mistakes and errors in our understanding of the world. Sometimes we overgeneralize something about a group based on the limited experiences of a few people. Other times we misinterpret what we do have, or we choose the cases that match our conclusion. Sometimes we can jump to conclusions when interpreting what is happening in the world. And we could just make a mistake! We could have misheard or misread what we know, or it could be as simple as misremembering information. We are all human, and it is perfectly natural to make mistakes.
To give an example of this, during one of the sessions at our 2025 IMPACT Conference, we asked members of the crowd (filled with loss prevention and threat assessment professionals) what they thought was the percentage of retail workers who felt unsafe at work. During the session, those audience members estimated it was 70 percent. However, data from the 2024 Voice of the Victim project (discussed in the next section) showed that only 27 percent of respondents felt unsafe at work.
Why this discrepancy? We could do a study on those audience members to determine “why,” but one theory could be that they are generally dealing with the harm done to their own employees in the course of their jobs. In other words, their exposure to those serious cases of harm may have skewed their view of the landscape for violence. This is just a theory, however; research could verify possible reasons for this discrepancy.
Research tries to reduce these issues through the scientific method. This is the systematic way we conduct research, with known steps and procedures that are both transparent and repeatable. Transparency is very important because it allows fellow researchers and practitioners alike to critique and improve upon the methods we use to collect and analyze data. So, don’t be afraid to criticize research in the hopes of improving it—we welcome the challenge!
Reason 2: Research Adapts to the Natural Changes of Our World
Our world is constantly changing as new innovations take hold, as social movements rise and fall, and as people change their preferences with the times. In some ways, though, people are also staying the same—people still need food and water, to connect with one another, and Tax Day within the United States is still April 15. With this in mind though, it is clear that our world is complicated, and sometimes we are just trying to distill the chaos into something meaningful and simple. Research can accommodate this need by breaking down those complicated pieces into something measurable and testable; a key component of research, after all, is defining what it is we are studying.
Additionally, research has context. Whenever we conduct a new survey, ask people for interviews, or look at the data collected by your organizations, that information is based on a certain place and a certain period. For example, in 2024, the Loss Prevention Research Council (LPRC) in collaboration with Verkada and Harris Polling conducted a mixed-method study of retail workers across the United States to understand their feelings of potential victimization while on the job.
Surveys were conducted during the summer of 2024, at the height of the US political election season. Experiences captured in those surveys and interviews likely reflect some of those key concerns that may not be reflected by individuals surveyed today. Some of the Hispanic respondents, for instance, indicated they were concerned about how the political environment vilified them, and that the political environment was sometimes brought up in interactions with customers. However, would those same concerns be captured if the interviews or survey were conducted today?
This is why it is important to repeatedly measure and reliably measure trends over time—just as our world continues to change, we need ways to continually adapt and capture those changes. Additionally, if you need to make important decisions about any changes you need regarding your organization, having the most up-to-date data to inform that decision may mean the difference between success and failure. Research can help with this and provide insights on the current pain points within the industry.
Reason 3: Research Expands Beyond Our Own Experience
Experience is a great resource we can use when trying to problem solve something. Often, we internalize what we’ve learned in the past and rely on it when trying to determine how to do something in the present and future. This can be incredibly helpful since we become faster and more efficient in solving our problems over time as we accumulate this internalized knowledge.
However, there are two concerns when we are solely reliant on our own experiences for all our decisions. First, our experience will be uniquely situated in a specific context. Think about what is acceptable to do today versus ten years ago; your experiences from ten years ago may have their limits in helping you navigate a changed world. This is the same concern presented in Reason 2.
Second, experience can be limited to just ourselves or the few people surrounding us who may be able to help us with a particular situation. From a research perspective, we typically say this is an “N of 1” problem because any analysis we are doing or conclusions we are prescribing are only coming from one source. And it’s quite possible that someone outside of your social orbit has figured out a better and faster way to solve the problem you are concerned with, but how would you learn it if you’ve never met them?
Sometimes this can be fine for our research purposes. If we are doing a case study on something and we are just trying to figure out what something is and how it works, then observing one case can be useful. However, if we want research to advise about industry trends or provide recommendations about key considerations for an issue, we may want more data points, especially from those who have figured out those faster and better ways.
Reason 4: We Love Numbers and Stories for Our Arguments
We love to use numbers and stories to argue our point in a debate! Sometimes those numbers succinctly capture what we are trying to argue. For instance, we see headlines on the news that grab our attention, especially if there’s some statistic or percentage attached. You may have seen, for example, one of the big headlines circulating around the recent National Retail Federation report conducted in partnership with the LPRC that found a “93 percent increase in average shoplifting incidents in 2023 versus 2019.” It is quite shocking and impactful, and we could use this information to convince others of the problems with shoplifting:
“See! It nearly doubled from pre- and post-pandemic, so we must do something to address it!”
On the opposite side of the spectrum, we may want to “humanize” our data points. We may not want to reduce people to simply numbers, especially when it deals with harrowing topics such as violence. Instead, we may want to contextualize data by people’s lived experiences, to understand how someone like us may have witnessed or felt based on those statistics. Using the Voice of the Victim project as another example, though we had collected survey data to partially inform our understanding of the state of violence among retail workers, we also wanted to make sure we captured people’s experiences. Why should these statistics matter, and under what circumstances might these numbers “make sense?” Again, think of how convincing using this data could be in an argument:
“See what happened with them? It’s clearly an issue that should be dealt with!”
While the above can be very useful, one word of caution whenever you use statistics or stories for your arguments: Statistics, especially those percentages or averages you may have seen in research studies, are only as good as the data that derives them. For example, if you find a study that claims “95 percent of participants stated they love body-worn cameras,” but the sample is primarily those that work for body-worn camera companies, then the value of that statistic for your argument is going to be questionable. Similarly, if you only interview individuals who have experienced violence while working in retail, you are missing the experiences of those that have not, which may be starkly different. Thus, while statistics and stories are useful tools for an argument, use them responsibly.
Reason 5: Research Can Suggest “What Works and Why”
Recall from earlier that one type of research which is done is called “evaluation research.” There are different types of evaluation research, but I’ll focus on two for this discussion. Sometimes, we are solely focused on the outcome of a program, intervention, or new technology on an outcome of interest. This type of research is called an “outcome evaluation.” Perhaps we are interested in reducing shoplifting within stores, and your company has decided to use facial recognition technology as a deterrent towards this. We may want to see the levels of shrink, loss, sales, or other variables we are concerned about before implementing the facial recognition technology and compare them to having the technology six months later.
By doing this, we are evaluating how facial recognition technology impacts the outcomes of shrink, loss, and sales, and this informs us about the changes in the outcomes because of that intervention. However, what if we were also concerned about how employees were going to implement the technology? How should it be installed? What types of procedures need to be in place so that customers and employees feel safe and accept the technology? We could conduct a “process evaluation” to better understand how it is used, what steps are taken to install and utilize the technology, and any problems when it was being used.
In this case, evaluation research tries to determine the outcomes of a particular intervention as well as how they are implemented. Other types of evaluation research include cost-benefit and cost‑effectiveness analyses, which focus on the return on investment based on designated outcomes. It could be very valuable to know, for example, how much it will cost to implement facial recognition technology and the types of outcomes that would be impacted by those costs.
An important note about cost-benefit analysis is that, when we conduct those kinds of analyses, we must assign a monetary value to something like “peace of mind.” This isn’t always easy—how do you place a price tag on something like happiness? Typically, we may have to look at proxies, such as insurance payouts, medical bills, etc. that are saved because of doing something. It’s not perfect by any means, but it does help at least provide some numerical value that we can use to compare the cost with the benefit of a technology or intervention.
Conclusion
Research can have several benefits within the loss prevention world. It can help us understand current trends beyond our own companies, provide us with data for our arguments, and help provide guidance on what could happen when new procedures and technologies are brought into your stores and distribution centers. Hopefully this list of five benefits inspires you to get involved in future research, encourage its use in the industry, and suggest ideas for research to explore.
