Types of shrinkage in retail

What are the types of shrinkage in retail

Retail shrink, or shrinkage occurs when a store has fewer items in stock than recorded in inventory. This complex issue affects retailers in several ways, with multiple sources contributing to shrinkage, including: Shoplifting; Employee (internal) theft; Administrative errors and Operational losses

This blog focuses on these four areas to highlight the most significant challenges retailers face in managing inventory, and how advanced computer vision technologies can tackle some of the underlying causes of shrink.

Shoplifting

Theft and fraud in supermarkets has risen to a 20-year high, representing £4.7 billion in losses in the UK alone, and over $112 billion in the US according to the NRF 2023 security survey.

First-generation self-checkouts have contributed to the rise in shrinkage. These early models rely on weigh scales to detect discrepancies, often leading to false alerts. For instance, if a customer scans several heavy items and then a lighter one, the weight difference might not register, causing the system to block. These weigh scale scenarios frustrate customers and keeps attendants busy clearing issues—often without understanding the root cause. The need to keep customers moving can result in missed opportunities to investigate, leading to both accidental and intentional theft. Some customers may not realize they’ve made a mistake, while others rely on overwhelmed attendants prioritizing transaction flow over checking for fraud.

In addition to shoplifting,  there is also Organised Retail Crime (ORC) to consider. ORC gangs typically concentrate on mass theft of high value retail items, for example infant formula, razor blades, electrical goods and batteries. Retailers are going to ever increasing lengths to prevent these items from being stolen with security tags, anti-theft boxes and making certain items only available from behind the counter.  As retailers experiment with different anti-theft devices designed to deter theft, their impact, particularly on customer experience, causes frustration – for example, Tesco security mesh cages were described as ‘overkill’ for the many customers looking to get their shopping and leave as quickly as possible.

The challenge with these devices is that they deter paying customers from buying items in store, creating numerous friction points in the physical retail environment at a time when customers are demanding ever more seamless transactions. For the determined shoplifter there will always be new attempts to steal products. For the frustrated customer however, these additional barriers can drive them to another competitor or to online grocery shopping.

Employees

The cost of internal or employee theft rose to £3.3 billion in the UK in 2024, accounting for 40% of retail theft, in the US, employee theft cost $32 billion in 2022.  Common types of employee theft and fraud include sweethearting (when employees offer discounts or free items at the checkout, often to friends or family), fraudulent refunds, and merchandise theft. As physical retail has adapted to e-commerce demands, opportunities for employees to steal or commit fraud have evolved, with click-and-collect packages reportedly seen as a ‘lucky dip’ for one interviewed shop worker, and high-value stock readily accessible, this challenge is felt from grocery through to luxury retail.

Addressing internal employee theft is challenging, especially given the challenges retailers face when recruiting. In 2024, 85% of retailers reported difficulty recruiting staff, and 71% reported being understaffed on to three days per week. Replacing employees disciplined or dismissed for theft can be slow and may not prevent similar types of behaviour in new hires.

Retailers also face a delicate balance: protecting stock without harming their reputation or increasing employee stress. At a time when violent or abusive incidents against retail workers are reported at over 1,300 per day, maintaining a safe, supportive environment is crucial.

Administrative errors

Administrative errors contribute significantly to inventory shrink, accounting for over 27% of losses in the US. Retailers handle thousands of products daily, and with complex processes in place, errors such as miscounting deliveries or mispricing popular items cost the industry over $30 billion in the US alone. The average retail business spends nearly 300 hours every year on administrative tasks – from managing invoices and stock replenishment to processing returns – highlighting both the volume of manual work, and the potential for costly mistakes.

While technology in inventory management has advanced, there is still plenty of room for improvement. Solutions such as automated inventory tracking, digital shelf labels, and AI validation of planograms can streamline processes and reduce errors. The retail automation industry is forecast to reach $33 billion by 2030, more than doubling its current value. This growth demonstrates the value retailers can unlock through automation. In areas where automation isn’t yet implemented, training employees on best practices for inventory management, including accurate counting and proper storage can help improve accuracy and reduce preventable losses.

Operational losses

For many retailers, this is an area that they simply accept as part of the price of having customers in store – broken products, damaged produce, misplaced items and unsold products that reach their best before all hit the retail bottom line. Yet, as shoplifting incidents increase, so does the cost of damage to property, and the additional devices and technologies retailers turn to in a bid to stem losses. These additional security measures are believed to add a £0.06 tax on every transaction customers make in UK stores.

Another key area of operational loss comes from food spoilage, costing retailers millions every year. Globally the cost of food wastage is over £2.9 trillion and retailers are increasingly under pressure to reduce their impact and reduce losses, whilst also facing higher demand from customers for fresh produce. Some have implemented forecast-based automation store replenishment, but this can be hampered by inventory errors elsewhere – for example should customers choose the wrong type of apple when using the self-checkout. At scale this can lead to over-ordering of some produce and out of stocks elsewhere.

How to prevent different types of retail shrinkage?

Tackling shrinkage while maintaining a positive customer experience requires a proactive and data-driven approach. Every store has unique challenges, from layout considerations to customer demographics, so tailoring loss prevention strategies to specific needs is essential.

Here are some effective actions retailers can take, with the benefits advanced technologies offer in addressing various shrink types:

• Enhance self-checkout security: AI-powered self-checkout solutions can reduce shrink by detecting and alerting to potential fraud or missed scans in real-time, creating an efficient checkout process which minimizes losses without disrupting customer flow.

Want to know more? The self-checkout security guide explains the common types of theft and fraud at self-checkout, and how computer vision can reduce losses and improve customer experience

• Assisted Checkout: By leveraging the advanced computer vision AI capabilities of self-checkout, such as shrink detection and fresh produce recognition, and applying them to manned or partially assisted checkouts retailers are able to detect patterns of internal theft, like sweethearting, as well as accelerate the checkout process by reducing the time it takes to find and key in produce item codes.
• CCTV with computer vision AI: Less than 1% of all recorded CCTV footage is monitored live, making it challenging to identify fraudulent activity in busy stores in real-time. Shoplifters working in groups take advantage of this, working together to create distractions, filling baskets and leaving them for other members to walk away with, and many other tactics. AI-enhanced CCTV enables retailers to stay on top of where stock is, tracking high-value items from selection to payment, alerting staff if items are concealed or other types of behaviour associated with theft, enabling proactive assistance and reducing losses.
• Improve accuracy in non-barcoded item selection: AI-based fresh produce recognition helps customers accurately select items, reducing costly errors when products are misidentified, and streamlines the customer experience.
• Consider re-assessing store layout: understanding how your stores operate on a day to day basis is crucial, design layouts which may be aesthetically pleasing can have a big impact practically on the shrinkage a store sees, with seasoned shoplifters making use of known blindspots and other layout issues that can provide cover for theft and fraud.
• Employee training: regular training ensures employees feel valued and developed in their role, helping to build company loyalty, in addition refreshers on loss prevention policies can help curb issues such as sweethearting or improper discounting.

Combining these targeted actions with advanced computer vision AI solutions and data insights helps retailers significantly cut down on shrinkage while maintaining a seamless customer experience. With the right technology in place, stores can optimize security, reduce losses and better understand in-store shrink patterns at a granular level.