Regardless of the protective progress retailers and solutions providers are making, thieves are still carrying off billions of dollars’ worth of goods annually. While merchandise loss costs retailers huge amounts of money, theft-driven product out-of-stocks, and sometimes locked-up goods, it also deters sales to good customers. Happy, buying customers are the lifeblood of retailing. Tragically, many theft attempts create violence, injuries, and crippling avoidance behavior by good customers from the fear of crime. Naturally, loss prevention executives continue to seek more impactful countermeasures, such as evidence-based retail crime prevention tools.
Evidence-Based Practice
In the past, many loss prevention decision-makers based their protective strategies and actions on anecdote, gut feeling, and comparisons with other retail companies. But LP executives are increasingly moving to the evidence-based model favored by the healthcare industry and other high-risk disciplines. Gut feelings can be accurate, but crime and loss, and particularly life safety, are too important to be tackled without using focused retail crime prevention tools supported by extensive and rigorous scientific evidence.
Predictive modeling, offender interviewing, and randomized field experiments provide that needed evidence. Sound, research-supported theory should support the “how-to” for best business practices. Good theory is practical, not guesswork. Theory is simply an explanation about how things work; there is nothing more practical than a good theory.
Retail crime prevention theory is a work in progress, but the idea basically explains how criminals come into contact with desirable, vulnerable targets and how they tend to behave in differing situations and environments.
Theory provides practitioners with the tools to better prevent, discover, and solve crime events. Theory describes how retail crime prevention tools actually work to affect offender behavior—in other words, their “mechanism of action.” Situational crime prevention is probably the most useful and empirically supported prevention theory or toolkit that crime and loss control executives have.
Rational Choice
Most professional disciplines have research-backed guiding principles. Security and loss prevention professionals require similar support to help practitioners more accurately diagnose problems, as well as describe and deploy appropriate crime prevention treatments.
Criminology’s rational choice perspective or theory provides much of what is needed by spelling out how criminals make semi-rational choices about what, where, and how to offend based on opportunities as well as perceived personal risks and rewards. Each person has differing genetic makeups, self-control levels, and social learning experiences. But regardless of these background factors, the foreground factors, such as the built and social environment; movement and travel patterns for work, shopping, and recreation; and socialization, also shape behavior in both positive and negative ways.
Nearly everything an individual does is the result of a choice. We do have free will, and deciding to be deviant or to commit a certain crime is a choice, regardless of different biological and social backgrounds. Rational choice theory describes this process so we can shape our deterrent measures.
Consider a potential offender walking into a store to steal something. Their heart rate may be up, they may be in a hurry, they may be high, they may not be the brightest intellect around, and they probably tend to underestimate risk or over-value rewards like money or peer praise. All of these factors constrain or negatively affect judgment. But they make rational calculations—thus rational choice. Their decisions may not be totally rational, but their decision process has the elements of a rational calculation. They consider opportunity, personal risk, and, of course, personal rewards when choosing what, why, and how to steal.
Situational crime prevention is designed to consider each factor offenders look at, and then precisely shape perceptions and reality. The current array of these deterrent measures is compiled in the Situational Crime Prevention matrix (see Figure 1).
Situational Retail Crime Prevention
Each type and subtype of crime is subtly different, as is each location, meaning retail crime prevention efforts should be precisely focused on the situation at hand. This is the basis for Professors Derek Cornish and Ronald Clarkes’ situational crime prevention (SCP) toolkit.
SCP spells out how practitioners should use a diagnostic process like criminologists’ John Eck and William Spellman’s scanning, analysis, response, and assessment (SARA) model to precisely define a problem, such as commercial armed robbery of a pharmacy for pain drugs versus robbing departing customers in a parking lot. Both are robberies, but each is different as far as offender motives as well as the hunting, attack, and commission styles. Like evidence-based medical treatments, cost-efficient crime prevention treatments are made possible by detailing situational crime problems.
Once the crime event problem is thoroughly described, executives apply indicated SCP techniques. The primary SCP techniques involve making crime attempts more difficult, more risky, and less rewarding. To be effective, preventive interventions don’t have to perfect, or even for real, they just have to convince would-be criminals that theft attempts are too much work, too risky, or not worth it. After deployment, retail crime prevention interventions are rigorously evaluated to determine their real-world impact and cost benefits.
Benefit Denial Defined
Much of the University of Florida’s Crime Prevention Research Team and the Loss Prevention Research Council‘s research team’s efforts are directed at developing and rigorously field-testing highly focused crime prevention interventions using the SARA and SCP process. We look at various ways people, programs, and systems are best deployed to deter offenders by increasing their crime effort, making them feel more at risk of detection and response, and helping them sense their contemplated crime attempt will not be rewarding enough.
Our research methods include systematic offender interviews in commercial spaces and places to get their perspectives. We want to understand what interventions they see (see it), if they can explain how they work (get it), and how their behavior has been or might be affected by them (fear it). The see it, get it, and fear it factors are essential to deterrence.
We make ongoing innovations and adjustments for real-world field evaluation. Our evaluations are usually randomized controlled trials (RCTs) in order to compare crime event or loss levels before and after in test locations compared to non-test control places. RCTs not only provide rigorous impact measurement, but cost-benefit estimates as well.
Our teams also examine how long and why it takes retail crime prevention treatments to reach “therapeutic” levels, peak, and then to lose steam. Critical questions include:
- What are the best dosage levels, for example, how many camera domes, and
- What are the optimum deployment tactics, such as best heights, placement, signage, and other factors?
We have to better understand why some retail crime prevention treatments work better in some spots than others. Like medications, crime prevention treatments have varying effects in different locations and on different people. We want to identify and address those critical risk and protective factors that affect differential impact to make impact improvements.
Loss prevention practitioners already deploy protective singular and combined techniques to make crime attempts riskier or more difficult. When it comes to making offenders think their contemplated crime act would be too risky, practitioners use many of the following techniques:
- Employee awareness campaigns,
- Guards,
- Store detectives,
- Lighting,
- Reporting hotlines,
- Transactional approval procedures,
- Exception reporting,
- EAS,
- Burglar alarms,
- Spider wraps, and
- Safers or Keepers, to name a few.
Physical barriers, locks, combinations, passwords, cabling, limiting curb cuts, and numerous other tactics increase crime effort. But since crime levels remain at unacceptable levels, loss prevention managers need more tools. Making crime attempts less rewarding is where benefit denial comes into play.
Benefit Denial’s Background
Retailers adopted ink or dye tags from Sweden in the late 1980s to protect apparel merchandise, heralding the first known use of benefit denial devices in the U.S. In 1989, the author created the term “benefit denial” when Bob DiLonardo, then of Security Tag, which was later purchased by Sensormatic/ADT/Tyco, requested a term to describe what and how ink tags, and other newly developed metal clamps for eyewear, wallets, earrings, and other jewelry, functioned to reduce theft.
Benefit denial seemed to succinctly describe the protective mechanism of action. The term is essentially defined as: stolen goods protected with benefit denial will not benefit the thief, since the goods will not work unless purchased. For example, illicit removal of ink tags results in the spraying of dye on the protected garment, thus reducing self-use or conversion to cash. Similarly, the metal clamps damage the items enough to deny thieves and fences any benefit unless removed as part of a purchase.
Retailers and security technology companies adopted the benefit-denial term. Likewise, Clarke placed the benefit-denial concept into the rapidly evolving situational crime prevention matrix so criminologists and practitioners would be able to further develop and test this relatively new crime prevention concept.
Other, more contemporary benefit-denial techniques include smartphones that don’t work until being activated after purchase, car stereos that don’t function if the faceplate is removed, and—an oft-cited example—special hotel hangers with small hooks or ball tops that require special racks. In this low-tech example, benefit denial does not make stealing hangers riskier or more difficult; rather they make it less rewarding unless the thief steals the rack as well or sells the hangers to other hotels.
Some retailers now combine benefit denial with the threat of detection (increasing the risk) by combining ink and EAS tags on high-loss clothing items.
The goal of retail is to profitably sell merchandise. The goal of loss prevention is to support that objective in part by creating the ability to sell more while losing less. Open or self-serve merchandise access means more sales and better shopper-retailer relationships.
Increasingly, senior retail executives realize theft and the fear of theft by store-level managers drives much of modern retailing. Fearful managers striving for year-end bonuses may tend to lock up, hide, or only put out small quantities of items thereby reducing sales. Benefit-denial technologies hold the promise of much more open selling of even high-value items.
Next Steps for Retail Crime Prevention
As loss prevention and law enforcement move to the evidence-based model, more retail crime prevention innovations, including benefit-denial concepts, should emerge, creating the conditions for selling more while losing less in a safer environment.
Benefit denial is not the total product protection answer for all assets in all places. Many store locations are daily exposed to huge theft risk due to surrounding criminogenic conditions. In other situations, managers may be less than competent or not committed to strong, ongoing asset protection efforts. Situations like these will require extra help.
Benefit-denial technologies and other emerging solutions will need to work with existing countermeasures, such as protective packaging, keepers and wraps, special pegs and display fixtures, electronic surveillance and notification, RFID, smart and open store layout and design, and a myriad of other technologies and tactics.
But at this point, it is encouraging to see that both growing evidence and crime prevention theory all point to the promise of selling more and losing less by making theft less rewarding with benefit-denial technologies.
This article was originally published in 2012 and was updated March 7, 2018.