Given the depth and breadth of TRL, it is perhaps not surprising that some companies are reluctant to adopt this approach. Recent research looked to identify what were viewed as the main barriers to adopting TRL. The main challenge was found to be not necessarily a lack of relevant data, but more one of data availability, accessibility and collation – pulling the relevant data together to populate the TRL typology. A second issue was found to be the impact of organisational inertia and competing priorities: there are hundreds of years of legacy to deal with when it comes to changing how retail businesses understand, measure and control losses. In addition, responsibility for various types of loss can be scattered across an organisational structure, making it difficult to pull together a TRL strategy. Moreover, as retailing becomes more complex and challenging, other business developments may well be regarded as a more pressing priority. The key is ensuring that the overall value of adopting this approach is measured and communicated with senior management teams.
Those companies that have embarked on a TRL journey have identified 12 key issues to consider:
1) Get the C-suite Onboard: Like most significant change initiatives, senior management support is key – generating urgency, facilitating financial support and ensuring compliance – all are important in making a TRL-based strategy a success.
2) Develop a Business Case – Focus on the Size of the Prize: Making use of the available data and the organization’s appetite for change, build a strong business case that focusses on the financial benefits that might accrue from adopting a TRL-based approach.
3) Adopt an Incrementalistic Approach to TRL: The TRL typology should be viewed as a palette of possibilities that can be tailored to any given organizational context – start small and build gradually – it is very easy to take on more than is realistically manageable in the first instance.
4) Identify Quick Wins First: At the beginning, only focus on those areas of loss that are likely to generate successful outcomes and are readily deliverable – do not attempt too much too soon.
5) Organize for Utilizing TRL: Think about who will be accountable for delivering a TRL-driven approach, what resources might be required (particularly analytical) and how to leverage support from across the business.
6) Advocate for TRL – Act as Agents of Change: Pooling responsibility for the management of all the areas of loss covered in TRL is less than desirable. Ensure that those driving TRL act as ‘agents of change’ – collecting the data, prioritizing the work, and then recommending ameliorative actions to those best placed to deliver them.
7) Review Reporting Structures for TRL: While there is little standardization on lines of reporting across the loss prevention industry, given the breadth and scope of TRL, a number of respondents to this research argued strongly that the Finance function is best placed to provide overall co-ordination.
8) Prepare for Organizational Antagonism: The way in which TRL often cuts across a wide range of organizational responsibilities can cause the potential for functional disquiet based upon a perceived ‘land grab’ by those driving the TRL agenda. It is important, therefore, that an assessment of the likely reaction of those impacted by a TRL initiative is undertaken, with a view to taking pre-emptive actions to explain, reassure and support.
9) Think About the ‘Right’ Name for your TRL: While the phrase Total Retail Loss has become relatively well known in the global loss prevention community, it is important that individual organizations develop their own label for their TRL-inspired initiative, based upon their particular circumstances and context. For a number of respondents, moving to ‘Profit Protection’ was regarded as a useful moniker that accurately described what the TRL-inspired initiative was aiming to achieve.
10) Avoid Terminological Confusion: It is important that as a business embarks on a TRL-oriented journey, the language that is used is clear and focused – by all means continue to use the term ‘shrinkage’ as a proxy for unknown stock loss, but ensure that there is a clear distinction made between that and the broader loss picture that you are aiming to develop.
11) Use TRL as an Analytical Lens: As well as providing a broad ranging and overarching framework for assessing and managing retail losses, the TRL concept can also be used in a much more focused way to evaluate the likely impact of any planned innovation and change by a business. By stimulating a more comprehensive assessment of the likely impact across a broad palette of losses, the TRL model can enable a more realistic and balanced ROI to be calculated for any given innovation or retail change.
12) Remember Timing is Key: Finally, like most decisions in life and work, timing can play a huge factor in dictating the success or not of any given initiative. Reflect upon the current organizational climate and whether it is likely to be broadly receptive or not to the introduction of a TRL-based approach. Where the head winds are deemed to be too strong, and other priorities too dominant, then delay may well be right approach.
Recent research has begun to classify the different ways in which SCO systems can create losses for retailers. These are:
Non-scanning: this can happen in a number of ways including, passing the item across the Fixed SCO scan area ensuring the barcode cannot be read and placing it in the bagging area (when weight-based security systems (see below) are not present or are set to tolerate one or more items not being scanned), or placing it directly into a bag next to the bagging area.
Mis-scanning: there are two main ways in which this typically happens. In the first, the user places a particular item on the weigh scale, such as a kilo of grapes and then chooses a cheaper item from the list of options available, such as carrots or onions. The second form is the mis-representation of items of a similar weight but differing values.
Walk-aways/Non-payment: this form of loss occurs at Fixed SCO machines when a user has scanned some or all of their items correctly and triggers the completion of the transaction but does not make payment, simply walking away with the items.
Product switching: a variant of mis-scanning is also possible with Scan and Go. In this scenario the user scans a particular variant of a product but then places it back on the shelf and replaces it with a more expensive type.
Multiple Variety Errors: this form of error corrupts store inventory records, which over time could lead to out of stocks and an eventual loss in sales. In this situation, the user has selected a product which is available in a number of varieties or flavours, such as a tins of cat food – chicken, beef, fish etc. The consumer simply scans the same variety several times to speed up the process and places them in the bagging area.
Promotion Errors: similar to the previous scan error, this does not necessarily generate an immediate financial loss for the retailer but does corrupt inventory records. In this situation the promotion is a buy-one-get-one free offer where the user only scans one item because they assume the second one is free and therefore does not need scanning.
Barcode Switching: this form of loss occurs where a user obtains a different (usually cheaper priced) barcode for a product and scans the barcode as the product is moved across the Fixed SCO scan area.
Coupon Frauds: In this scenario the use of promotional coupons is abused by the user, typically by using the same coupon multiple times, leading to lost margin.
Double-scanning: This type of error is in many respects a double-edged sword for retailers. On the one hand, when a consumer accidentally scans the same item once or more, then they will be paid for the same product more than once, generating a significant profit. On the other hand, the same behaviour will also adversely impact on stock accuracy – store systems will potentially over order double-scanned items, which could lead to a range of adverse outcomes.
Up until recently, there has been little or no published research on the scale of losses associated with SCO systems. However, the 2018 ECR Report, available elsewhere on this website, is the first time estimates of losses were surmised. The study looked at losses for Fixed SCO and for Scan and Go systems:
Fixed SCO: 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 90% to 100% higher. One case study, 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% higher than stores not using any SCO technology.
Utilisation data (number of transactions processed through SCO) showed that stores with higher rates had higher levels of shrinkage. Stores where 55-60% of transactions went through Fixed SCO can expect their shrinkage losses to be 31% higher. Similarly, data looking at rates of loss and the number of SCO machines in use found that stores with higher numbers of machine also had higher rates of loss. Stores with the average number of SCO machines (for the case-study retailer), could expect to see shrinkage losses 31% higher than an estimated industry average, while those utilising an above average number of machines could expect the rate of loss to be at least 60% higher or more.
Technology monitoring and video analysis data looking at €72 billion of transactions found that non-scanning at Fixed SCO machines accounted for 0.44% of SCO sales, amounting to 9.5% of all store-recorded shrinkage. The data suggested that non-scanning behaviours alone (not including mis-scanning, walk-aways etc) are likely to add 0.5 Basis points of loss per 1% of Fixed SCO utilisation.
Together the various data sets strongly indicate that previous assumptions that Fixed SCO do not generate additional losses for retailers are incorrect – the losses are real and, in some cases, significant. Based upon the available evidence it is estimated that for each 1% of Fixed SCO utilisation, a retail store should expect their shrinkage losses to increase by at least 1 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. At this time, it is not possible to put a concrete figure on these losses.
Given this, for a store with 50% of transactions being processed through Fixed SCO, it can expect its shrinkage losses to be 77% higher than the average rate found in Grocery retailing. None of this data takes into account the likely productivity savings retailers can accrue from using this technology.
Scan and Go Systems: analysis of 140 million transactions, found that the average utilisation rate of this technology was still relatively low – 2.43% of all transactions. Of this total, 12% or 17 million were subject to a Partial Re-scan Audit (only a small proportion of items are checked). Of those, 2.87% were found to contain at least one error, generating an overall inventory error rate of 0.52% of Scan and Go sales. When over-scans were taken into account, the net loss was calculated as 0.31% of Scan and Go SCO Sales, equivalent to a 2 Basis point increase in losses for every 1% of utilisation.
However, analysis of 20,000 random Full Re-scan Audits (every item is checked) showed an overall error rate of 43.4% – 1,412% higher than the Partial Re-scan Audit data. When this error rate is used to calculate net losses, it shows that the rate is as much as 3.88% of all Scan and Go SCO sales, generating a Loss to Utilisation Ratio of 11 Basis points per 1%. Taken together, stores using this technology (at current utilisation rates) could see overall losses in the region of 3.3% of all sales, undoubtedly raising questions about the overall viability of this approach.
Further analysis of Full Re-scan 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 50 items in their basket, then there is a 60% chance they will make at least one error, while for those with 100 items there is almost a 9 in 10 chance they will make an error.
The ECR study also shared data from one retailer comparing stores with and without Scan and Go SCO, which showed that those with the technology had a rate of shrinkage 18% higher than those that did not, suggesting a Utilisation to Loss Ratio of 6 Basis points.
Recent research found that companies that were engaging with TRL did so for the following reasons: provided a better framework to capture all forms of retail losses; created opportunities to positively impact on business profitability; helped to ensure resources were more effectively targeted; enabled the loss prevention function to maintain relevance; created greater transparency and accountability; and helped to manage increasingly complex retail environments.
The TRL concept is designed to be flexible, capable of changing as the retail risk profile changes, along with retailers’ capacity to measure it. As such the first version of the TRL typology published in 2016 included 33 categories of loss, while the second version, published in 2018, had 42 categories. Although the concept suggests it covers all forms of loss, ‘Total’ Retail Loss, is in fact based upon only those categories of loss which are described as being Manageably Measurable and Meaningful to the retail utilising it. To review the current range of categories of loss included in the typology, visit the Total Retail Loss research pages elsewhere on this website.
The TRL concept is designed to be flexible, capable of changing as the retail risk profile changes, along with retailers’ capacity to measure it. As such the first version of the TRL typology published in 2016 included 33 categories of loss, while the second version, published in 2018, had 42 categories. Although the concept suggests it covers all forms of loss, ‘Total’ Retail Loss, is in fact based upon only those categories of loss which are described as being Manageably Measurable and Meaningful to the retail utilising it. To review the current range of categories of loss included in the typology, click here to visit the Total Retail Loss research or click here to view the latest blogs on Total Retail Loss.
While there is much more research required to understand how SCO supervisors can impact upon the levels of loss generated by SCO, the ECR research considered the following factors to be important:
Customer Engagement: making not only eye contact but also verbally interacting with the SCO users was considered important, but doing this in a way that was non-confrontational and service-focussed
Delivering Customer Training: using non-accusatorial techniques was considered an important skill for SCO supervisors to develop, to enable an errant shopper to not lose face yet at the same time recognise that they had been identified.
Customer Prioritisation: when SCO spaces get busy then the supervisory role becomes even more critical in managing customer expectations and keeping friction to a minimum.
Occupying the SCO Space: ensuring that supervisors occupied a central and visible location within the SCO environment was considered important in amplifying risk and improving their capacity to deal with alerts more quickly.
Having Awareness of Risk: because of the unique risk characteristics of SCO spaces, it was also deemed important to ensure that SCO supervisors were given sufficient training to understand what they should be specifically looking for and how to react accordingly.
Protecting the Brand: In some Fixed SCO environments, audits of customers using Scan and Go/Mobile SCO systems can also be carried out, and these events can often be viewed as an explicit personification of a retailer’s overt distrust of the user – this as a moment of tension for both the consumer and the SCO supervisor, particularly when un-scanned product is identified. It was felt that a well-trained SCO supervisor was critical at this moment.
Experience Counts: there was clear and unambiguous support for the notion that only experienced staff should be employed in SCO environments. In addition, emerging evidence suggests that SCO supervisors should be selected who are able to multi-task well and make good decisions when prioritising activities.
Keeping Customers Honest and Accurate: the SCO environment is potentially rich with opportunities for both malicious and non-malicious losses to occur, and so the role of the SCO supervisor is fundamentally about keeping the customer honest and accurate – to gently guide them away, through good customer service and vigilance, from the opportunities that they may be presented with to makes errors and/or abuse the system.
Probably the biggest difference with other measures of retail loss is the breadth and depth of the loss categories included in the TRL typology. It now includes 42 categories of loss broken down into four areas: retail stores; the retail supply chain; E-commerce activities and corporate. It then breaks these into categories where the cause of the loss is either known or unknown and then where the cause is known, it differentiates between those that are regarded as malicious or non-malicious in nature. As such, it is regarded as the most comprehensive and well-defined approach to understanding the cost of retail losses to date.
Because the level of losses associated with SCO have only recently begun to be understood, retailers are still developing their palette of options to try and manage them more effectively. The ECR research identified two key approaches: Minimising Product-driven Errors, and Amplifying Risk and Enhancing Detection:
Minimising Product-driven Errors: focussing upon ensuring that packaging and barcode issues do not generate scanning problems; reducing the number of product set-up issues which may make scanning difficult; and ensuring the removal/deactivation of product protection technologies is efficient and reliable.
Amplifying Risk and Enhancing Detection: the ECR research concluded that three components were important: Guardianship: ensuring there are suitable, properly trained and motivated SCO Supervisors operating in an environment which facilitates rather than hinders their duties; Technologies: A range of systems designed to identify discrepancies in weight versus what has been scanned by the consumer; automatically identify when a consumer has not properly scanned an items; and systems which can identify products to reduce the risk of mis-scanning; Design: developing effective ways to amplify risk and enhance detection in the SCO environment, such as creating Zones of Control.
The same research was also able to quantify some of the value that the participating retailers were prepared to share:
Increase in Sales: Seven of the 10 case studies shared data showing a sales improvement in the range of 1.5% to 5.5%. For SKUs identified by RFID systems as being out of stock, the growth was even higher. Based upon this data, the 10 companies taking part in the study may have realised an RFID-driven sales uplift of between €1.4 and €5.2 billion.
Improved Inventory Accuracy: Companies typically had an improvement from 65%-75% to 93%-99%.
Stock Availability: Some of the companies taking part were now findings SKU availability in the high 90% region.
Reduced Stock Holding: One-half of the case-study companies shared data on this measure, indicating a stock reduction of between 2% and 13%.
Lower Stock Loss: One company suggested that their shrinkage losses had been reduced by 15%.
Reduced Staff Costs: One company had measured a saving equivalent to 4% of their store staffing costs, which if rolled out across the case-study companies would be in the region of €378 million.
Return on Investment: All 10 companies were unequivocal in their assertion that the ROI had been achieved, and based upon their trial experiences, further roll out across the business was fully justified and embraced by the rest of the business, often with considerable enthusiasm and optimism.
A recent review of how retailers are using TRL showed that few if any have yet to embrace an approach which commits to using all of these categories in their loss prevention strategy. Even the 10% of companies that declared they had ‘fully embraced the concept’ were far from populating all of the categories with a value of loss.
What is much more evident is a tailored approach to using this typology – companies reflecting upon their current capabilities, priorities, resource availability, organisational culture and appetite for change, and then creating their own, often more limited version of the TRL typology. They are selecting and, in some cases, adding categories of loss that work best for them in the current circumstances in which they find themselves. It is an approach that is eminently sensible – using the TRL typology as an adaptable resource and not an ideological straitjacket – something which can be used to trigger a broadening of understanding, taking an organisation beyond the moribund strictures of only thinking about loss as a function of unknown stock loss/shrinkage.
There are no text book or standard accounting answers to this question. Typically, what would be included, and in monetary value, and valued at the cost of goods, would be the following forms of losses which are typically well recorded and include; damaged products, products spoiled, or products past their expiry date that are donated to charity, to store colleagues, to animal feed or just thrown in the bin for incineration. But then there are the losses that are NOT recorded well, these include theft, damages and spoilage not recorded, errors in the system that include recipe mistakes, plus audit and POS errors. The below are some of the typical "buckets" of food waste.
The above causes are all included in the number often referred to shrink (in USA) or more completely, known and unknown losses.
In addition, some retailers would measure their waste in tonnes, or in CO2 emissions, and track and measure the percentage of their waste that is kept within the human and animal food chain, and by default not sent to land fill. This answer is not meant to be exhaustive, a good source for a more comprehensive answer (160 pages) can be found in the CGF Food Loss and Waste Accounting and Reporting Standard
Consensus is actually very hard to find on what the term ‘shrink’ or ‘shrinkage’ means and what should be included and excluded when it is being calculated. Some authors regard it as a catch all for a wide range of losses suffered by retailers, including both crime-related events such as staff and customer theft, and errors incurred as part of the process of retailing, such as incorrect pricing, changes in price, damaged products and food items going out of date, while others only seem to use it to refer to variance in the value of expected and actual inventory.
Most of the published surveys and reports on shrinkage typically break it down into four areas of loss: employee/internal theft; customer/external theft; administrative/paperwork error; and vendor/supplier fraud. These categories, and the associated guesstimates of their significance, have dominated the reporting of shrinkage for decades. While the first two: internal and external theft, can be readily understood and defined, the latter two are much more difficult to categories. As detailed above, administrative error is a catch all phrase that can include a wide range of retail costs, while vendor supplier fraud is a notoriously difficult category to try and identify and measure with any precision. While there is a simple elegance to these four categories of loss, it is questionable whether they are still appropriate/useful in 21st Century retailing, particularly with the rise of online shopping and other retail developments.
The origins of the word ‘shrinkage’ seems to have been traced back to the UK Co-operative Movement in the 1860s and from there it began to be adopted in other countries as a term to describe the difference between expected and actual retail sales, based upon a valuation of delivered inventory compared with actual inventory in the business. Other writers refer to ‘shortages’, ‘inventory shrink’, ‘inventory shortage’, ‘retail inventory loss’, or simply ‘loss’ rather than ‘shrinkage’ although they all seem to be essentially trying to describe the same sort of thing. So, it is a longstanding and enduring term used to describe a varying basket of retail losses.
Retailers are primarily, but not exclusively, interested in using RFID to identify products across their supply chains to improve the accuracy of their stock inventories. Thus far, most retail users of RFID have employed RFID to enable products in retail stores to be accurately identified and counted more quickly and on a more regular basis. Some retailers use RFID to track the shipment of goods from suppliers and within their own organisations. In addition, RFID can be used to monitor the movement of other retail assets such as pallets and delivery crates as well as promotional materials. For the most part, retail users of RFID seek to have the taggant attached to their products when they are manufactured (known as source tagging) as it is typically a more reliable and cost effective method than applying it within the retail supply chain or at a retail store. Retailers will then make use of fixed and handheld readers to identify their stock at various locations, such as in a warehouse, entering the back of a store, and when it is on a store shelf. Key to the use of RFID is a database management system that enables the unique product codes to be associated with any given item. These systems can provide powerful business intelligence such as the location of any given product and its current status (such as sold or unsold).
Probably yes, but it is often very unclear from the existing definitions and descriptions of shrinkage the extent to which both known losses, where the cause of the loss is apparent, and unknown losses, where no clear identifiable cause can be identified, are included. It would seem that virtually all published definitions and calculations rely heavily upon the difference between expected and actual stock levels/values, which, depending upon when the stock audit took place, will rarely if ever provide any meaningful understanding as to the root causes of the loss. In some circumstances, the loss could have occurred almost a year ago – did the missing item ever arrive, was it thrown away but not recorded as such, did a member of staff steal it, was it taken by a customer, did a member of staff not scan the item at the checkout? The possible reasons for the loss are many and varied but what is usually very clear is that the cause of loss is unknown and remains so despite the best intentions of those who may be tasked to speculate about possible reasons.
But, as can be seen above, agreeing if and what potentially known losses could be included in a shrinkage definition is not clear cut and some of the words and phrases used (administrative errors, process failures etc.) are at best vague catch all terms which could incorporate (or not) a varied list of possible losses which, depending upon the type of retailer, could significantly impact upon the size of the overall shrinkage number. However, for the most part, and for most retailers, the term shrink or shrinkage is largely used to describe those losses where there is no apparent evidence as to WHY the loss occurred – the reason is not clear and therefore they should be correctly described as losses where the cause is unknown.
Advocates of the Total Retail Loss concept would argue that due to ongoing and irrevocable variances in how the term shrink or shrinkage is defined and used by retail businesses around the world, and the significant changes in the way in which retailing now operates, it is a term no longer fit for purpose, or at the very least should be replaced with the term ‘unknown stock loss’ as this better describes what it is typically measuring. However, it is a term with a long history and therefore it is likely to be used for a long time to come.
When it comes to defining shrink or shrinkage there is much variance and little agreement within the world of retailing. For instance, some researchers describe it as ‘the difference between book inventory (what the records reflect we have) and actual physical inventory as determined by the process of taking one’s inventory of goods on hand (what we count and know we actually have)’.
However, another author defines it more specifically as ‘the amount of merchandise that disappears due to internal theft, shoplifting, damage, mis-weighing or mis-measuring and paperwork errors’, while another researcher focuses more on the value of goods and considers it to be ‘the disparity between the financial value of stock acquired and sold and the financial value of stock left on the shelves’. Yet another writer offers more detail by attempting to define the elements that are non-crime, such as ‘error’, which is regarded as ‘a result of inaccurate decisions or failures’ which include mispricing goods, not accounting for them properly, not reclaiming effectively from suppliers and under/over delivery of merchandise with the wrong specification. This writer also talks about ‘processing losses’, which are instances where it may be ‘impossible to sell every item of inventory at the authorized price’, and ‘waste’ (price reductions due to product deterioration and damage) being part of shrinkage. Together these non-crime losses are grouped together under the general heading of administrative/internal error.
Finally, some researchers have developed probably the broadest definition of shrinkage to date: ‘intended sales income that was not and cannot be realized’, looking at the issue primarily as one focused on the lost profit opportunity of the merchandise brought in to a retail business. They view any loss in the intended profit (however that may be calculated) as a loss to the business, although they tend to rely upon what has been described as the ‘four buckets of shrinkage’ to categorise their losses (see below).
So, as can be seen, there is little or no general agreement on how the term shrink or shrinkage should be defined beyond a general sense that it is largely measuring the difference between the volume or value of stock that a retailer thinks they have and what they actually have.
The inadequacies of the existing and widely used term shrink or shrinkage can be found elsewhere in this Q&A section of the website. Generally speaking, the advocates of the TRL concept argue that the incredible growth in the complexity of retailing, combined with a vastly more broad ranging risk landscape and capacity to better measure and understand that landscape, increasingly means that the rather one-dimensional measure of loss offered by the term shrink or shrinkage, is simply no longer fit for purpose or sufficient to enable retail businesses to respond to, and manage, the losses that negatively affect profitability and the customer experience.
Recent research by the ECR Retail Loss Group identified the following reasons why retailers were investing in RFID:
Driving Sales: The primary goal of investing in RFID was to deliver improvements in inventory visibility and accuracy, which in turn would grow sales.
Optimising Stock Holding: Respondents also recognised the potential of RFID to enable them to optimise their stock holding, reducing capital outlay and improving staff productivity.
Fewer Markdowns: Most case-study companies regarded RFID as a key tool in helping to reduce the amount of stock they offered at discounted prices.
Helping to Drive Innovation and Business Efficiencies: RFID was frequently viewed as part of a broader organisational change project focussed on putting enabling technologies in place to drive transformational change to achieve future success.
Recognising the Omni Channel Imperative: This technology was viewed as a key driver in developing the capacity to deliver a profitable omni-channel consumer experience – in effect the organisational ‘glue’ that will hold together much of the architecture of 21st Century retailing.
Click here for the report
Numerous retailers around the world are now trialling technologies to try and identify when a consumer has not scanned an item. The most common is a weight-based security check where the system monitors the weight of all the items placed in the checkout area and compares that with the weight of all the items that have been scanned. If an item has not been scanned but placed in the checkout area, it will in theory trigger an alert. While regarded by many as a good form of security, they can generate a considerable number of false interventions, particularly if the weight-based product database is not kept up to date.
Retailers are also trying video-based systems to identify scan avoidance. Using overhead cameras, the system tracks the movement of products across and around the scan area and compares that with product registrations on the Electronic Point of Sale (EPOS) system. If an item is ‘seen’ to move across the scan area but is not recorded on the EPOS system, then an alarm can be triggered. This is challenging technology to make work accurately and early iterations often generated high levels of false positives and negatives. However, providers of more recent versions of this technology claim that the level of accuracy is now much improved and can be used to prompt users to rescan items which have not been registered on the EPOS system without recourse to generating a response from a member of staff.
How you put a value on shrinkage also generates a significant amount of variance within the retail community, although most shrinkage surveys are explicit in requesting that data be provided at retail prices, calculated as a percentage of sales turnover. Some authors suggest that the majority of retailers calculate their shrinkage at retail prices, with between 20% and 40% using cost price or a combination of cost and retail prices. Using retail value typically generates a much bigger shrinkage number, which can be useful for drawing attention to the problem (internally and externally), and factors in the potential impact of loss on retail margin, as well as compensating for some of the consequential costs of shrinkage (additional transportation, staff time etc.). However, it can generate a misleading number – changes to the retail price can mask known shrinkage problems (such as the impact of price increases on the value of current and previous stock holdings), or the difficulty of calculating the retail price of a product in a sector that is highly driven by sales and discounting.
A relatively common way in which consumers can abuse SCO systems is to misrepresent what a product is when it is being weighed – the ‘grapes for onion’ scam. Here the consumer places, say a bag of grapes on the weigh scale, but ‘tells’ the system they are in fact onions, which are much cheaper than grapes. Some retailers are beginning to try technologies that will ‘identify’ what the product is that is placed on the weight scale, or in some circumstances what it is not. In this example, the system ‘knows’ what onions look like and so when the user presses this option, the system generates an alert to say it hasn’t ‘seen’ onions. Again, this is challenging technology to get to work in a complex environment, especially when a store could have as many as 50,000 different items and there is little tolerance for delay while scanning.
When first introduced the initial driver for many adopters was undoubtedly labour saving and increased productivity, with much of that saving being associated with the introduction of fixed self checkouts (SCO ) systems, which had the capacity to remove a considerable amount of labour from the traditional staffed checkout model. However, the retail picture has evolved considerably, and the use of SCO systems is now increasingly viewed as part of a broader picture of offering greater consumer choice. In many respects what can be seen is the evolution of a ‘push’ and ‘pull’ approach to the use of SCO technologies in retailing. In the first instance, retailers quickly realised that it provided an incredibly effective way to reduce their staffing costs – one of the largest outgoings a retail business faces, but as the technology became more established and some consumers began to prefer it as a way to shop, then it has emerged as an increasingly expected and indeed essential option within the modern retail space.
Grocery retailers in particular have been using a range of technologies for many years to enable consumers to take greater control over the checkout and pay process of the shopping journey. These technologies, which are called different things in different markets, such as: Self-checkouts (SCO), Assisted Self-checkouts, Self-checkout Systems, Self-service Checkouts, and Scan and Payment Systems, were first seen in the late 1980s/early 1990s although their use has only really become much more extensive in the last 5-7 years. The technology essentially gives responsibility for the scanning of items that wish to be purchased to the consumer, including in some circumstances, weighing fresh food. In addition, the consumer is then given the responsibility to make the payment for the products that they have scanned.
It is hard to get reliable data on the extent to which retailers are using Self-checkout technologies. The most common type currently in use is Fixed Self-checkouts, followed by Scan and Go systems and then Mobile Scan and Go and Amazon Go style technologies. The Grocery sector, where customer and product volumes, and space utilisation issues make it a particularly appealing proposition, are by far and away the sector most likely to use this technology thus far. However, other types of retailing are also beginning to use SCO, including the Home Improvement sector, some apparel retailers and convenience stores.
Total Retail Loss (TRL) is a concept that adopts a broad ranging and inclusive approach to understanding and categorising all the manageably measurable forms of loss that a retail business might experience across the entire organisation. Based upon years of research, it was coined by the academic Professor Adrian Beck and originally published in a series of research reports published both by the ECR Retail Loss Group and the Retail Industry Leaders Association in the US in 2016. It sets out a clear definition of what is meant by the term ‘retail loss’: Events and outcomes that negatively impact retail profitability and make no positive, identifiable and intrinsic contribution to generating income. It contrasts this with what are regarded as retail costs: Expenditure on activities and investments that are considered to make some form of recognizable contribution to generating current or future retail income. In addition, it identifies a subset of retail costs called ‘margin eroders’, which have often been included by some in their definition of shrink or shrinkage: planned and unplanned activities and behaviours which, strictly speaking, negatively impact upon overall retail profitability, but nevertheless, can be seen as having a beneficial role to play in helping the business generate current and future profits.
It is important to note that TRL is primarily designed to enable the ‘value’ of retail losses to be calculated and not necessarily the number of events – where an associated ‘value’ cannot be calculated or there is no loss of value associated with an incident, this is not included. For instance, if a shoplifter is apprehended leaving a retail store and the goods they were attempting to steal are successfully recovered and can be sold at full value at a later date, there is no financial loss associated with this incident. That is not to say that the retailer may still want to record the fact that an attempted theft took place and was successfully dealt with, but that it would not be recorded in the TRL concept. In this respect TRL is exclusively focused upon recording the value of retail losses and not their prevalence.
Beyond an ongoing lack of agreement about an industry-wide definition for shrink or shrinkage, which makes efforts at benchmarking deeply flawed, critics of the term argue that three major changes in the world of retailing mean that it is increasingly an unsatisfactory way to understand and describe the losses experienced by retailers. The first is the growing complexity of the retail industry – when the term was first used in the 1860s, retailing was a relatively simple process – counter-based service with little consumer interaction with the product. Fast forward 150 years of more and retailing is a profoundly different business – online, self-selection, self-scan, vast and complex supply chains to name but a few of the changes. Secondly, the range of risks faced by retailers has changed dramatically since the term shrink or shrinkage was first used – theft of products by customers is now but one of a welter of issues that retailers have to manage, such as fraud, violence, counterfeit, product contamination, cash loss, margin erosion, to name but a few. Finally, retailers now have a much wider and deeper pool of business data to draw upon to understand how a range of losses are affecting their organisation than when the term shrink or shrinkage was first coined. So, taken together, the incredible growth in the complexity of retailing, combined with a vastly more broad ranging risk landscape and capacity to better measure and understand that landscape, increasingly means that the rather one-dimensional measure of loss offered by the term shrink or shrinkage, is seen by some as no longer fit for purpose.
The retail sector is not short of surveys trying to ascertain the scale and nature of the shrinkage problem it faces. In the US there is the longstanding National Retail Security Survey, while more globally there has been various sweeps of the Global Retail Theft Barometer, covering a varying number of countries. In addition, many surveys have been undertaken over the years covering particular retail sectors and a range of different countries. Virtually all of these surveys rely upon respondents providing a ‘shrinkage’ figure with varying degrees of explanation about what should be included and excluded from this number. For instance, in the past the National Retail Security Survey (NRSS) asked for: ‘your firms fiscal inventory shrinkage (excluding damages and spoilage)’, while the 2008 version of the Global Retail Theft Barometer asked for the ‘Corporation’s shrinkage or stockloss for 2007-2008 financial year (or most recent year) as a percentage of turnover)’. It then goes on to ask a further question about whether wastage/or spoilage was included in this figure and if it was to provide this, presumably as a percentage of turnover (although it is not clear). Both surveys then request that the respondent provide a best guess or estimate of the likely causes of this unknown loss using the typical four buckets of shrinkage outlined above, although for the NRSS, the category of ‘Administrative and paperwork error’ obviously now excludes damages and spoilage, and there is also an option for respondents to choose ‘unknown loss’ as an explanation of their unknown loss!
As detailed above, given that most definitions of shrinkage are based upon data derived from variance in expected and actual stock holding, the data is almost always a measure of unknown loss. From these estimates the surveys then calculate the apparent causes of loss, with some carefully tracking and micro analyzing annual changes and differences between countries and retails sectors based upon this data. Some authors have been highly critical of this approach. One said: Attributing known losses to these [loss] classifications is fairly straightforward. The problem arises with the inclination of business and academia to apportion a value for total shrinkage, i.e. known and unknown shrinkage, to these categories. Instead of an honest answer along the lines of: Retailing is a complex business, there are many mechanisms through which shrinkage can occur and we don’t know which ones apply in this instance, there is a tendency to use judgement/estimation/guess work to apportion unknown shrinkage to each category. Despite the fundamental weakness, this erratic approach is the default mechanism all too often used to inform management thinking and direct investments in loss prevention solutions when faced by a lack of hard data.
Others have highlighted similar problems: [the data] can only been seen as a measurement of how respondents currently feel about each of the factors they are requested to make estimations about – they are socially constructed and more than likely a distorted picture of the problem based upon personal prejudice.
Without doubt, some of these surveys have played an important role in helping the loss prevention industry understand how it is thinking about the problem of loss. Other parts of these surveys, which for instance, focus upon the extent of the use of various approaches to managing loss, have been important in providing benchmark data. But the rapidly changing retail landscape, together with the way in which retailing is not only experiencing a broader range of losses, but is also growing its capacity to collect and analyze data on them, would suggest that a new approach to benchmarking retail losses may well now be required.
A fundamental component of the SCO proposition is the transference of responsibility for the accurate scanning of products and ensuring correct payment is made from staff employed by the retailer to the consumer. In many respects this is a radical leap of faith in the capacity of the consumer to do this both accurately and honestly. Since the very early days of retailing, incidents of customers stealing product have been recorded and indeed a whole industry has been established trying to manage this problem as incremental changes in the retail environment have increased the risk of losses occurring. For many of those tasked with ensuring that retailers sell more products than they lose, the emergence of SCO technologies 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.
While there is now a wide range of types of SCO technology available, there are essentially three main forms:
Fixed self-scan machines or robots: this is where the consumer brings their chosen products to a fixed point in the store and proceeds to scan them either using the barcodes present on the items or by choosing the item type from a list of possible options provided by the machine displayed on an interactive screen. The consumer can then pay for their items either with cash or by some form of payment card.
Scan and Go Systems: this is where the consumer is provided with a ‘scan device by the retailer which can be used while shopping to scan the barcodes of items they wish to purchase. At the end of the shopping journey, the user is then required to go to a fixed point and dock their scan device in a terminal, which then processes the transaction and takes payment from the consumer.
Mobile Scan and Go Systems: the third main variant in use now, and one that has only recently begun to be offered by retailers, is similar to the Scan and Go system described above except that instead of using a scan device provided by the retailer, the consumer uses their own mobile device, utilising a bespoke App provided by the retailer (or a third party), and the camera functionality built into the device, to scan and record products they wish to purchase. This also provides the option for the consumer to pay for their items anywhere in the store via their mobile device.
Other forms of SCO technologies are available, with new approaches being developed all the time, including the use of RFID. More recently the Amazon Go system, which was unveiled towards the end of 2016 in their Seattle Headquarters store in the US, uses a network of cameras, sensors and weight pads to enable a consumer to pick up any items and exit the store without any need for barcode scanning or interaction with a payment system. The prospective consumer needs to be registered with Amazon and to have downloaded a bespoke App before entering the store. Upon arrival, the user has to scan a unique code generated by the App on their mobile device to gain access to the store, and then they are free to select items and then simply leave the store, receiving an electronic receipt within 20 minutes. A number of other companies are also beginning to offer technologies similar to this approach
RFID is an acronym for Radio Frequency Identification. It is a technology which makes use of some form of taggant attached to an antennae (such as a label or physical tag) to encode data that uniquely identifies the item to which it is attached. This data can then be captured via radio waves by different types of powered reader devices. While similar in purpose to a barcode, RFID is seen to have at least two big advantages – the ability to identify objects uniquely (such as via an Electronic Product Code) and the capacity to do this without the need for line-of-sight (unlike a barcode). It is a technology that is used in a number of different settings, such as libraries, collecting road tolls, tracking and identifying animals to name but a few. Its use within retail can be tracked back to the late 1990s/early 2000 when initiatives such as the MIT AUTOID Centre began to develop standards and technologies suitable for use on a wide range of retail products.
The ECR research found that retailers were looking at the following areas as potential areas for further developing their use of RFID:
Using the technology in fitting rooms and with ‘Magic Mirrors’; greater use of RFID along the entire supply chain; broadening coverage across more SKUs and locations; improving data collection interfaces and data integration in the business; improving tags, in particular how they are attached to various products; exploring how overhead readers may be used in the future; delivering checkout-less stores; and creating seamless merchandise visibility with a range of technologies beyond just RFID.
One of the great challenges of managing retail loss is the lack of precise data on its causes, making the development of ameliorative actions more akin to guesswork than calculated intervention. The reason why the causes of most losses remain unknown is due to the way in which loss or ‘shrink’ data is often generated.
Typically, a retailer’s shrink number will be calculated when periodic physical stock audits are undertaken, which reveal the difference between the amount of stock (either in terms of value or number of items) the system thinks the business should have on hand (based upon the difference between the amount of stock acquired versus the amount sold through checkouts), and what is actually present. The discrepancy is ‘shrink’, often expressed as a percentage of the total amount. So, a company that buys 100 units and sells 80, with 10 remaining in stock has a shrink rate of 10% – 10 items have gone missing. Because there is very often a time lag between when an item has gone missing and when a physical audit takes place that recognises the loss (for those undertaking annual audits, it could be up to a year), it can be very difficult to know why it happened. Did the item ever arrive at the store? Was it returned to the supply chain but the transfer not recorded? Did a customer steal it? Did a member of staff steal it? There are many reasons why losses may occur but very often because of the data time lag, ascertaining the root cause is almost impossible. Given this, the potential for RFID systems to generate stock level data much more frequently and potentially enable awareness of product location, could mean that those responsible for loss prevention should have better quality data to understand how losses are affecting a retail business and build better strategies accordingly.
In addition, some retailers are now beginning to use their RFID systems to identify when a Returns Fraud is occurring. This happens when a thief returns an item that was originally stolen for a refund. Because existing barcode technologies do not record whether any given product has been sold or not (it simply identifies it as a particular type of product), then thieves can exploit the refund process and request cash or credit for items they did not originally purchase. The benefit of RFID is that because each product is uniquely identified, and its status potentially recorded in a database, then a member of staff working on a refund desk can be in a much clearer position to decide as to whether it is appropriate or not to issue a refund.
In a similar vein, some retailers have been using their RFID systems to generate an alert when an unpurchased product leaves a store (operating in a similar way to EAS tags, described elsewhere in this FAQ). Again, the big advantage of RFID in this scenario is that there is the potential for the alarm responder to be made aware of which particular product has triggered the alarm, something that most existing EAS systems cannot achieve. This then makes the stop and enquire process much quicker and more focussed. However, some retailers that have tried using this functionality of RFID have run into difficulties around read accuracy for certain types of tag, and of course, where the tag is merely a paper label, then the thief can simply remove the tag before exiting the store.
Finally, some retailers have argued that they purposefully do not want their RFID tags to be viewed as a security tag – the primary benefit of RFID to them is to improve stock accuracy and so this could be compromised if thieves begin to actively remove tags in order to evade detection. This can of course be dealt with to a certain extent by the application of hard tag RFID technologies, but this brings with it additional tag application and management costs that could undermine the ROI business case for introducing RFID in the first place.
Introduced in the 1970's, originally in lending libraries to stop the theft of books, EAS has evolved and is now considered the technology that offers the very first line of defence against shop theft and with the exception of the supermarkets channel, EAS pedestals can be found at the exit and entrance of most hypermarkets, home improvement retailers, drug stores, apparel and fashion stores, department stores and specialty such as Auto-parts.
In terms of technology, in the first instance came Electro Magnetic tags, these were strips of metal that neatly sat inside books. Today, only two EAS technologies are present, Acousto Magnetic (AM), and Radio Frequency (RF). Each has their advantages and disadvantages, with each retailer making their own decisions. In the US for example, Walmart chose AM, Target chose RF. In the UK, Boots chose AM, Tesco chose RF. In some countries, and channels, for example French grocery retailers, the majority, if not all, chose RF.
EAS can be applied at the source of production (source tagging) or in the store. When applying at the source, soft tags are preferred as they are easier and simpler to apply to bottles, health & beauty products, meat, etc. Soft tags are disposable and will go home with the shopper [deactivated]
On the other hand, hard tags (for bottles, attached to safer cases, for clothes, etc) are more pre-disposed to a local application given their size and the need to recycle this more expensive hard tag. However, the apparel retail sector have identified a recycling programme, whereby hard tags are applied in the garment factories, shipped to stores and then returned to the garment factories.
One final step in the evolution of EAS has been the recognition of its limitations, and the industry is becoming much clearer that EAS is primarily aimed for, and most successful at deterring the opportunist thief, as opposed to the so called professional thief stealing for resale. To this end, when the industry thinks about soft tags, and source tagging, it has turned its attention to carrying messages on products that have EAS protection, that signal to the opportunist that these products have a security tag included.
Typically, for audit, financial and compliance reasons, the entire inventory located in physical stores and distribution centres should be "counted" once a year to ensure that the book stock records match / are adjusted to reflected the actual quantity in these locations..
Retailers can either choose to complete this undertaking using their own internal team, either a specialist audit team or the store or DC team themselves. Alternatively, they can use a third party such as RGIS, who will undertake the audits on their behalf and to their brief.
A hybrid approach is also available where stores will be supervised by / borrow the equipment of a third party specialist.
EAS is a means by which retailers can determine whether an item leaving a store has been paid for or not. If the item has been paid for, then either the soft EAS tag would have been deactivated at the point of sales by the scanner, or the hard tag, sometimes included in a safer case box, will have been removed. If the item has not been paid for [and deactivated] or hard tag removed, then the pedestals at the exit will emit an alarm that will draw the attention of store associates and store guards who can assist the customer and identify the items not paid for / causing the pedestals to alarm.
Specifically, inventory record accuracy considers whether the physical quantity found of a sku matches exactly the quantity recorded on the system at any point in time. For example, if the system record suggests that there are twelve cases of a sku, for example Gillette MACH3 4 count, but the auditors only find five cases, or they find thirteen cases, in both examples, the record is deemed to be inaccurate.
Complexity is added when the measure is viewed through the lens of value Vs item integrity. Here, retailers can be more interested in the net negative value of the variance, often called out as unknown loss or shrink.
Further ambiguity is added when interpretations are made on how to measure the variance, with organisations adapting metrics that define accuracy as a percentage found within a zone of +/- 2 units, or a monetary value.
The ECR Retail Loss Group believes that inventory record integrity, either the system and the physical inventory match exactly or they don't.
The ECR Retail Loss Group chooses to define Inventory record accuracy as the percentage of inventory records in any given location where the physical quantity exactly matches the quantity stated in the inventory system, or as some call it, the perpetual inventory record. Retailers acquire this data through an audit of the inventory where either the retailers staff or a third party conduct a physical count of the inventory they find in the store. Using this method, the retailers would count the number of inventory records with a variance, and compare them to the total number of inventory records in that location. In the ECR research, only 40% of inventory records were found to have an exact match.
Shrink or unknown loss is a number that can also be derived from the same audit data. Shrink or unknown loss is the variance between the total value of the inventory expected to be in the location and the actual quantity found at the count. The value of this variance, typically a negative, is then expressed as a percentage of total retail sales for the period between the time of the previous audit and this audit. Typically this variance is valued at between 1-3% of sales valued at retail.
So the differences are:
What they share are the reasons that explain the variances, wrong deliveries, pick errors, loss and theft in transit, receiving mistakes at the store, misplacement in the back room, damage and spoilages not recorded, wrong counting, theft from staff, third party vendors and non paying customers, errors at EPOS, errors with returns and wrong transfers. There are more reasons but broadly, the causes are the same.
Strictly no, a loss should be seen as a loss to the business where that loss has no intrinsic value to the organisation. In the case of markdowns, they serve a purpose which is to accelerate the sale of items close to their expiry date, the value therefore is to recover some value and profit from these items rather than donating, re-purposing or throwing away. However, again there are no standards, some retailers will have the budget for markdowns sit with the buyer and not be in the control of stores, and then there are others where the store and store operations will own the budget for markdowns.
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