Unexpected Loss in the Bagging Area: Managing Losses Associated with Self-Checkout

The use of self-scan and checkout (SCO) technologies has grown considerably in the past fifteen years, predominately but not exclusively in the grocery sector, where customer and product volumes and space-utilization issues make them a particularly appealing proposition. For many retailers it has provided a significant opportunity to reduce their core costs at a time of increasing competition, and as new iterations of the technology have evolved, there would seem to be a growing appetite amongst certain groups of users to prefer this mode of shopping. However, a fundamental component of the SCO proposition is the transfer of responsibility from the retailer’s staff to the consumer for the accurate scanning of products and ensuring correct payment is made. For many of those tasked with ensuring that retailers sell more products than they lose, this growing use of SCO systems has been viewed as a concern, not least in the difficulty in imposing strong enough controls over the way in which it may be used and abused.

A new report from the ECR Community Shrinkage and On-shelf Availability Group and an accompanying book provide new insights into this issue, charting the scale and extent of the losses retailers are experiencing from a range of SCO technologies. The research also provides a detailed review of the ways in which these losses might be best be controlled.

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The two-year study focused on quantifying the risks associated with three forms of SCO systems:

  • Fixed—The consumer scans at a designated machine/robot,
  • Scan and go—The consumer is provided with a scan gun by the retailer, and
  • Mobile scan and go—The consumer users their own mobile device to scan items.

The research is based on data collected from thirteen retail companies operating in the US and Europe and two SCO technology providers. Interviews were carried out with seventy-three key stakeholders from these companies, and eleven store visits were conducted to review the technologies in use. In addition, a range of data points were collected from participating retailers, including 140 million scan-and-go transactions, 17 million transaction audits, 486,000 items found not to have been scanned, video analytics of €72 billion ($83 billion USD) of fixed SCO transactions, and comparative shrinkage data from thousands of retail stores.

The study does not take into account the likely productivity savings retailers can accrue from using this technology nor any possible reductions in loss as a consequence of employing fewer staff for instance. This needs to be kept in mind when reviewing the data below. It is also worth noting the significant challenges the research faced in trying to collect, collate, and analyze data from retailers on the losses associated with SCO systems—the absence of quality data on this issue was profound and concerning. It certainly shone a spotlight on the current lack of prioritization in retailing to better understand the potentially negative consequences of their use. It would seem that, to date, retailers have been keen to feast upon the positives of SCO but less keen to understand the possible downsides in terms of an increase in retail losses.

Impact on Retail Losses: Fixed Self-Checkout Systems

Data comparing stores with and without fixed SCO found that levels of loss were higher in the former than the latter, with some grocery case studies recording losses in the region of 33 to 147 percent higher. One case study that focused on the difference between stores using SCO with and without a weight-checking system found that losses where there was no weight system were 147 percent higher than stores not using any SCO technology.

Utilization data (the value of transactions processed through SCO) showed that stores with higher rates had higher levels of shrinkage. Stores where 55 to 60 percent of transactions went through fixed SCO can expect their shrinkage losses to be 31 percent higher. Similarly, data looking at rates of loss and the number of SCO machines in use found that stores with higher numbers of machines also had higher rates of loss. Stores with the average number of SCO machines (for the case-study retailer) could also expect to see shrinkage losses 31 percent higher than an estimated industry average, while those utilizing an above-average number of machines could expect the rate of loss to be at least 60 percent higher or more.

Technology monitoring and video analysis data looking at €72 billion ($83 billion USD) of transactions found that nonscanning at fixed SCO machines accounted for 0.44 percent of SCO sales, amounting to 9.5 percent of all store-recorded shrinkage. The data suggested that nonscanning behaviors alone (not including misscanning, walk-aways, and so forth) are likely to add 0.45 basis points of loss per 1 percent of fixed SCO utilization.

Together, the various data sets strongly indicate that previous assumptions that fixed SCO does not generate additional losses for retailers are incorrect-the losses are real and, in some cases, significant. Based on the available evidence, it is estimated that for each 1 percent of fixed SCO utilization, a retail store should expect their shrinkage losses to increase by at least one basis point. This estimate does not consider other forms of loss that SCO systems are likely to be generating, such as lost margin and lost profits due to out-of-stocks caused by increased errors in stock-inventory records.

Given this, for a store with 25 percent of the value of transactions being processed through fixed SCO, it can probably expect its shrinkage losses to be about one-third higher than the average rate found in grocery retailing.

Impact on Retail Losses: Scan-and-Go Systems

Analysis of 140 million transactions found that the average utilization rate of this technology was still relatively low in the companies that agreed to share data—2.82 percent of the value of all transactions. Of this total, 12 percent or 17 million were subject to a partial rescan audit (only a small proportion of items are checked). Of those, 2.88 percent were found to contain at least one error, generating an overall inventory error rate of 0.52 percent of scan-and-go sales. When overscans (the consumers scans the same item more than once) were taken into account, the net loss was calculated as 0.31 percent of scan-and-go SCO sales, equivalent to a 0.7 basis point increase in losses for every 1 percent of utilization.

However, analysis of 20,000 random full rescan audits (every item is checked) provided by one case-study company paints a very different picture. It showed an overall error rate of 43.4 percent—1,407 percent higher than the partial rescan audit data. When this error rate is used to calculate net losses, it shows that the rate is as much as 4.68 percent of all scan-and-go SCO sales, generating a loss-to-utilization ratio of 10.4 basis points per 1 percent. Taken together, stores using this technology (at the utilization rate found in this study) could see significantly higher losses, perhaps as much as 40 percent higher.

Further analysis of full rescan audit data, using probability statistics, showed that as the size of shoppers’ baskets increased, then the likelihood of an error occurring also increased. When a shopper has fifty items in their basket, then there is a 60 percent chance they will make at least one error, while for those with 100 items there is almost a nine in ten chance they will make an error. One retailer shared data comparing stores with and without scan-and-go SCO, which showed that those with the technology had a rate of shrinkage 18 percent higher than those that did not.

Controlling Self-Checkout Systems: Keeping Shoppers Honest and Accurate

The research looked in detail at how these various types of SCO technologies might best be controlled in the short to medium term, focusing particularly on the amplification of risk, how to enhance capacity to detect errant behavior, and minimizing product-driven errors.

Controlling Fixed Self-Checkout

Guardianship. This was considered to be the most important factor by respondents to the research but also difficult to ensure compliance at store level. The key was ensuring suitable, properly trained, and motivated supervisors were used and that they were operating in an environment that facilitated rather than hindered their duties. Overall, respondents to this research thought the optimal supervisor-to-SCO machine ratio was 5:6, although this could flex depending upon the SCO environment in place.

Technology. Scan-verification technologies were most prevalent—weight-based checking and video analysis of customer scanning behaviors. The former was the most established, although opinions varied on its applicability with some deciding to turn it off because of its impact on the customer experience. Others had taken the decision to adapt and refine it to better fit their retail context and achieve an acceptable balance between risk amplification and minimizing customer friction. Given the challenges of controlling fixed SCO systems, the latter approach would seem a good option to adopt.

Product-verification technologies were not used at all in the case-study companies, although some were beginning to trial them. Designed to help mitigate misscanning errors and help speed up the checkout process, these technologies could make a real contribution to managing SCO losses and improving the customer experience, but as yet further work is required to make them a viable prospect.

Design. Developing effective ways to amplify risk and enhance detection in the SCO environment—creating zones of control—was found to be important. Key was the location of the SCO area within the store, how customers were channeled through this space, the location and sight lines of the SCO supervisor, and the use of risk amplifiers such as CCTV and signage.

Controlling Scan-and-Go and Mobile Self-Checkout Systems

In comparison with fixed SCO systems, scan-and-go and mobile SCO currently offer far fewer opportunities to amplify risk and enhance detection. The majority of current controls are focused on six process-based factors.

Robust User Identification. Ensuring that retailers had a clear, verifiable way of understanding who was registering to use their systems.

Establishing User Expectations. Retailers should only be offering this facility to those who clearly understood the “rules of the game”—that it is a privilege and not a right to access this way of shopping and that it comes with clearly defined expectations on the part of the retailer, including that a shopper will be audited on the first use.

Delivering Credible Audits. Delivering deterrence and detection of errant users through the use of consumer behavior-driven algorithms and utilizing capable guardians. The latter need to be supported with data-driven tools to ensure they are equipped to identify items most likely not to have been scanned.

Utilizing Fixed Payment Points. While current mobile scan-and-go SCO systems require the user to go to a fixed point to confirm payment, concerns were raised that developing iterations of mobile scan-and-go SCO will allow the user to pay on their mobile device at any location. This was considered extremely risky as it removes a key control point within the SCO shopping journey.

Communicating with Users. A number of respondents described ways in which they were considering the communication of risk-related messages to users, particularly with mobile scan-and-go SCO through the associated app.

Exit Control Strategies. Some retail companies already use or are thinking about introducing designated exit areas where mobile scan-and-go SCO users must go to leave the store. These often require the user to scan a code generated upon payment that opens the exit gate.

Minimizing Product-Driven Errors

Packaging and Barcode Issues. Respondents flagged up a range of issues relating to barcodes on some products that made them difficult to scan. Others were concerned about the use of multiple barcodes on the same product. Retailers should consider meeting with suppliers to review product design issues that may be contributing to SCO-related problems.

Set-Up Issues. A number of case-study companies recognized that errors within their own organizations were creating problems, particularly relating to the regular updating of product-inventory systems, especially when items were sourced locally.

Product-Protection Issues. Ensuring not only that tagged items were consistently detagged but also that scan-and-go and mobile SCO users were reliably informed about which items needed to be detagged was considered a real concern by respondents.

Controlling the SCO Environment Dynamically

Just as risk differs across the retail landscape, the use of strategies to manage SCO systems should also be tailored to the circumstances in which they are being used. Different operating environments may well require not only a different palette of interventions but also variable tolerance settings depending on the circumstances.

Compliance Is Key

Store teams need to be clearly guided on why agreed practices and policies relating to the control of SCO systems need to be rigorously and consistently enforced, such as the maximum number of fixed SCO units per supervisor. The provision of unambiguous data on the impact SCO-related losses are having on the business will be a key first step in achieving this goal.

Developing a Framework to Manage SCO in Retailing

The extent of the losses presented in this new research suggest that retail businesses, and their partners, need to rebalance their assessments of the benefits that can accrue from investing in SCO-related technologies. The ROI calculation needs to fully take account of what the negative impacts might be.

Using a variant of an existing loss prevention model, the research developed a framework for how retail businesses can go about developing an organization-wide approach to managing the risk associated with use of SCO systems, focusing on eleven key themes:

  • Ensuring there is senior management commitment focused on understanding all the outcomes of investing in SCO.
  • Developing cross-functional organizational ownership and embedded responsibility for the control of SCO.
  • Establishing a clear set of data management protocols to fully understand the impact of various types of SCO technologies on the business.
  • Prioritizing operational excellence in how SCO is developed and managed.
  • Committing to a program of innovation and experimentation to improve control.
  • Forging better collaboration between different retail functions and with SCO technology providers not only to understand the risk side of the SCO equation but also to develop and evaluate interventions that may help mitigate the identified risks.
  • Recognizing and prioritizing the role people can play in actively managing and controlling SCO systems.
  • Striving to develop SCO leadership that can articulate all aspects of its use within retailing, including not only the possible benefits but also the possible risks.
  • Ensuring that there is communication with all parts of the business on all aspects of SCO.
  • Delivering store management responsibility by providing them with data to understand the challenges, training, resources, and technological tools to create an environment that minimizes risk and incentivization to ensure that they remain compliant.

Taken together, the research concluded that these factors offer an approach to begin to develop a more coherent and coordinated strategy to better manage the risks associated with SCO systems in retailing, one that continues to recognize the benefits but also takes more account of the growing challenges that they now seem to be presenting. Certainly for those employed in loss prevention, this research will hopefully enable a much more joined-up and realistic assessment to take place in retail companies, one where their concerns are better heard and all the consequences of “choices” retail businesses make are properly taken into account.

For a free copy of the report, visit the ECR Shrinkage and On-shelf Availability website at ecr-shrink-group.com. For a copy of Professor Beck’s book on this research, search “Adrian Beck” on Amazon.com.

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