The following describes a cornerstone theory of judgment and decision making that has tremendously important implications in loss prevention. The elaboration likelihood model (ELM) of persuasion, developed by Petty and Cacioppo, postulates a dual-process manner in which decision makers take in and process information.
Bottom line for LP: Even if offenders honestly aren’t able to report that they consciously noticed a deterrent designed to stop theft by shoplifting, the presence of one still may have affected their behavior and decision-making processes. Likewise, even if a customer says they didn’t notice or weren’t bothered by an LP measure, it still may affect their shopping experience. Observation of behavioral data (watching outcomes) is superior to first-hand accounts (asking opinions) for this and other reasons.
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Understanding the intricacies of the decision process is paramount if one wishes to alter that process. Otherwise, you’re simply inputting changes into a black box and observing each output with no real understanding of how the strings are being pulled, what mechanism is responsible for any changes seen, and/or how to adjust or replicate the changes.
The ELM model is highly regarded as a theory of attitude change and offers valuable insight on how decision-makers take in and process relevant information. It posits two distinct routes to information processing, and therefore two routes to influencing decisions.
When presented with stimuli, we do an initial sweep and determine what deserves our attention and cognitive resources. Think of a drive home from work that you’ve done so may times that you take it in auto-pilot, where you’d be unable to tell me any specifics of what you saw on the way home that day.
Another classic example is finding ourselves humming a song and wondering why. We didn’t attend to a song while it played on the radio earlier that day, and if you asked us if we’d heard it that day, we’d say no. That song has been processed through our peripheral route and affected our behavior despite never being centrally or consciously processed.
In the case of LP, offenders may not realize that they’ve seen and been deterred by a loss prevention measure, a clean parking lot, the police officer they saw three blocks from arriving at the store, or any other subtle stimulus. They’re not able to identify these stimuli as having had an effect on them because they were processed through a peripheral route.
This finding is one of the major reasons that the social science and business fields strongly prefer observing behavior to asking about behavior. Asking misses out on this important category of influencers.
Central route processing occurs when a stimulus catches our attention and is determined to be worthy of our cognitive resources. At this point, we’ve noticed the stimulus, and it enters our conscious thoughts. Most anything that you would consider an influencer of decisions has probably entered through the central route.
Offenders are aware of messages received via central route-processing. Everything they tell you affected their decision did so through the central route. This process and subject has been well studied in the LP industry as one significant way to stop theft by shoplifting.
Implication: Stop Theft by Shoplifting via Cues Aimed at the Peripheral Route
Peripheral-route processed stimuli are important drivers of decisions and need to receive further attention in the LP world. They’re often the same deterrents or process changes that we’ve put in place and currently believe to have minimal effect on customers or offenders due to lack of expressed feedback from those groups.
Just because a shoplifter reports, and in fact believes, that they didn’t notice or were unaffected by a security measure or incidental environmental factor, does not mean it did not affect them. It simply means that it was not processed centrally.
Similarly, just because customers don’t notice and report not being put off by LP does not mean that this is truly the case, even if the customer believes it to be. Measuring behavior is the only reliable way to get the full scope of a treatment’s effect. Sales, shrink, behavioral incidence data of retail theft events, dwell time data, and conversion data are paramount for research in loss prevention. Video analytics to code and understand behavioral outcomes is a growing and exciting data source.