Introducing Total Retail Loss: Can It Offer a More Meaningful ROI for RFID?

New research explores what shrinkage and other known losses mean for radio frequency identification—and for measuring the technology's impact on the industry.
Published: December 4, 2016

Back in the early days of the development of radio frequency identification and the Internet of Things, when both developers and potential users were trying to formulate return-on-investment (ROI) cases, one of the recurring themes was that RFID could make a significant difference in the realm of shrinkage management. In particular, it was frequently thought that it would help to significantly limit the ability of thieves to take products out of stores without being identified, as well as curtail problems of returns fraud, as the status of the product (bought or not bought) would be clearly identifiable. Fast-forward to today, and it is rare to see any of the recent successful trials and rollouts of RFID making much of an impact upon shrinkage rates—some do, but few claim it to be the primary reason why they embarked on introducing the technology.

Given the apparent cost of shrinkage to retail businesses, with some estimates suggesting it to be a $123 billion global problem, why does it not appear to feature highly, if at all, in many of the RFID business cases made public to date?

It is likely that among the main reasons are the ongoing ambiguity concerning the actual definition of shrinkage and the significant difficulties in providing any reliable measures of its true causes. Recent research has shown that there is no clear industry standard regarding what should be included or excluded when the term “shrinkage” is used—it is a catch-all term, varying hugely from one retailer to the next. The reality is that most retailers’ shrinkage numbers are primarily based upon a calculation of the difference between expected and actual inventory values, generated by relatively infrequent physical stock counts. What then typically happens is that this “unknown cause” loss number is subsequently apportioned to one of four buckets of loss: external theft, internal theft, inter-company fraud and administrative error or process failures, with the proportions based more upon personal prejudice and guess work than actual reality.

It is also the case that the location of this data-collection process is primarily in retail stores, with few companies offering much detail about the losses they incur in other parts of their business. This, in some circumstances, creates the problem of stores inheriting the losses that occur elsewhere. For instance, if a distribution center mistakenly under-delivers to a given shop, then this loss, if not realized, will eventually appear in that store’s shrinkage number.

What this has meant is that using the measure of shrinkage to understand the impact of any store intervention is riven with difficulty: Did the supposed loss happen in the store at all? If it did, how do we know what the cause might have been? Was it stolen by a staff member or a customer? Was it simply damaged, had it gone out of date and not been recorded by employees when it was thrown away, or was it simply due to the inability of workers to count stock properly at audit time? The possible causes are many and varied, and unpicking how the use of RFID might impact upon this number is extremely difficult—its level of imprecision and lack of transparency seriously undermine its ability to be used as an effective evaluation measure.

Given these challenges, the Retail Industry Leaders Association (RILA)’s Asset Protection Leaders Council (APLC), together with the ECR Community Shrinkage and On-shelf Availability Group, commissioned research to begin to develop a more meaningful and forward-looking definition and typology of retail loss. The recently published research puts forward a much broader organization-wide approach to thinking about loss, taking it beyond just the loss of stock and encompassing other elements, such as the loss of cash and retail margin. It also reaches far beyond the confines of the physical store itself, recognizing that losses occur in supply chains, the virtual retail space of e-commerce and across the corporate components of the business as well.

In addition, the research makes a crucial distinction between what should be considered a loss and what should be regarded as margin eroders—events that impact upon overall business profitability, but are viewed as part of the costs of doing business. The Total Retail Loss Typology puts forward 35 categories of loss, the majority of which fall under the heading of known losses, and eschews any attempts to categorize unknown losses.

So what might this mean for RFID and measuring its impact? To date, developing any form of ROI that relies upon having an impact on store shrinkage is likely to be problematic. The complete lack of transparency in this number makes mapping any form of intervention mechanisms that RFID may trigger almost impossible, particularly when personal prejudices are used to make assumptions about the supposed causes of the loss. What the Total Retail Loss Typology can begin to offer is a range of much more identifiable and discrete categories of loss that could be used to track RFID’s impact—it would move away from trying to measure its impact upon a bucket of unknown loss to one much more focussed on a series of known and measurable losses.

It also worth reflecting on how the greater transparency and data visibility that come from tracking stock via RFID might be used to populate the known categories in the Total Retail Loss Typology. Introducing the capacity to know the location of stock at any given time is likely to reduce the amount of loss that would have traditionally been dumped in the shrinkage (unknown loss) bucket. This, in turn, will enable the business to better understand where losses are actually happening and, therefore, make more informed decisions about how to utilize available resources to manage them more effectively.

During the next few years, it will be interesting to see not only how retailers that start embracing the Total Retail Loss Typology use it to develop more overarching RFID ROI cases, but also how they utilize the ensuing data to better understand their overall retail loss landscape. It could finally be time for RFID to begin delivering on those early assumptions and start to measurably make a difference in reducing retail losses.

Adrian Beck is currently a professor of criminology at the University of Leicester, where until recently he was the head of the Department of Criminology. He is also the academic advisor to the influential ECR Community Shrinkage and On-shelf Availability Group, and recently completed a major research project for the Retail Industry Leaders Association in the United States. He can be contacted at bna@le.ac.uk.