With shoplifting currently hitting unprecedented levels, computer vision technology advances could help retailers not only tackle the issue of the day, but also provide the means to address the wider aspects of shrinkage.
By Guy Yair, Chief Revenue Officer at computer vision technology company, Trigo
The epidemic levels that shoplifting has recently reached, demonstrated by genuinely alarming statistics, have rightfully made mainstream headlines. An ongoing concern for retailers large and small, shoplifting goes far beyond the simple pilfering of goods; it has far-reaching consequences for the retail industry. Each stolen item represents not just the cost of the item itself, but also the associated expenses of tracking, reporting and potentially replacing the stolen goods.
According to figures from the British Retail Consortium (BRC), retail thefts increased by up to 68% across ten of the UK’s largest cities, with almost eight million incidents reported between March 2022 and March 2023, costing retailers almost £1bn.
Underscoring the extent of the issue, the UK retailer, Co-op, recently announced that it suffered a staggering £33 million (€38 million) loss in just six months due to shoplifting. These alarming statistics highlight a growing concern that is not exclusive to a single retailer or country.
In the USA, for example, the National Retail Federation (NRF) estimates that annual shrinkage costs the country’s retail sector close to $100 billion (€90 billion) across the West Coast.
Systemic Errors and Human Error
While shoplifting is a critical issue that is quite rightly making mainstream news, it is of course just one component of the overall problem of shrinkage faced by the retail industry. Other factors like vendor fraud, accidental theft, and human error all contribute to making shrinkage an ever-present thorn in the side for retailers large and small.
In the case of the latter, basic human errors, generally referred to as systemic errors, may include mis-scanning at the checkout or mistakes made with inventory and pricing, all of which can collectively amount to eye-watering financial losses for retailers. Indeed, recent discussions that Trigo had with a major UK retailer revealed that they lose £15 million (€17 million) annually solely to mis-scanning.
Beyond the aforementioned aspects of shrinkage, food waste is a pervasive issue that adds further woe to retailers across the globe.
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The inherent challenge around the process, timing, and manner in which fresh produce and goods nearing their expiration date are disposed of can result in financial losses, environmental concerns, and even reputational damage as retailers face the dilemma of managing their stock efficiently while also minimizing waste to ensure sustainable and responsible business practices.
Despite the availability of certain apps and software designed to address food waste, these primarily focus on managing the consequences of the issue, rather than tackling it at its core.
Computer Vision Technology
In light of these challenges, the retail industry is actively seeking innovative solutions to turn the supertanker around. This community understands that traditional measures are no longer sufficient to address the wide-ranging issues. The good news is that there is an emerging technology that can support retailers in their fight against the problems outlined above.
Driven by computer vision technology and artificial intelligence, this advancement eliminates the need for physical manned- or self-checkouts to enable fully automated stores that can significantly reduce shoplifting by digitally capturing every shopper-product interaction in the store.
Already attracting the attention of larger retailers, this frictionless technology offering not only delivers the tools needed to deter theft but also reduces spoilage more broadly thanks to real-time in-store data, while also enabling better stock visibility and predictive stock management.
The difference that such frictionless technologies can make in fiscal terms is potentially incredible, especially with regard to the earlier example of the UK retailer losing millions annually due to mis-scanning alone. Equally, when it comes to improving the accuracy of inventory management to minimize stock discrepancies, an improvement of just 1% for the retailer with a €32 billion annual turnover would equate to a saving of more than £32 million.
Needless to say, retailers operating in today’s industry face a plethora of both existing and new operational challenges, not to mention the ever-present battle to retain customer loyalty. Although unlikely to provide the silver bullet to completely solve any of the individual issues I’ve outlined, the type of transformational technology that I have described is beginning to provide the more forward-thinking retailers with a means of achieving demonstrable success.
