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Tackling challenges of retail sweethearting with AI and machine learning

Pathma Subramaniam
Pathma Subramaniam • 7 min read
Tackling challenges of retail sweethearting with AI and machine learning
The typical loss from pilferage can range from 1% to 5% of annual revenue, depending on the level of control retailers have over their outlets. Photo: Unsplash
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Pilferage and sweetheart­ing — the latter a term used to describe a form of employee theft or fraud — have long plagued the retail industry. Losses due to sweethearting can be challeng­ing to accurately quantify since many incidents go undetected or unreported.

“When an employee provides a customer with a discount, free item or another favour without following the right processes or getting permission from the supervisor, it is referred to as ‘sweethearting’ in the retail industry,” says Vernon Chua, CEO of Sycarda by Innergia Labs.

Sycarda, which stands for “systematic collection and anal­ysis of retail data”, is a data analysis and business intelli­gence platform that Innergia launched in 2018. The solution helps retailers and F&B service providers reduce costs and in­crease revenue through the in­sights gained from its real-time transaction data. Currently, it is used by more than 50 F&B operators, pharmacies, super­markets, convenience stores, hypermarkets, shopping malls and fast-moving consumer goods companies in Malaysia, Indone­sia, Thailand, the Philippines, Singapore, Hong Kong, Australia and the US.

In February, Chua entered into a memorandum of un­derstanding (MOU) with Sin­gapore-headquartered digital solutions provider Cue to pro­vide more comprehensive and effective retail solutions across Malaysia, Singapore, and even­tually the rest of Asia.

Sweethearting occurs in sev­eral ways, says Chua, who then cites some examples. “Like not scanning an item, unauthorised use of a voucher or coupon or tampering with the cash reg­ister. Although sweethearting is frequently carried out as a goodwill gesture towards the customer, it can cost the store money, especially when done without the knowledge of the business owner,” he says.

Chua continues: “Sweet­hearting can significantly affect retailers’ bottomlines, thus they frequently have regulations and processes in place to avoid and identify the practice. Grocery chains and convenience stores are the most impacted retailers, along with bookstores, which is surprising.”

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Although putting an esti­mate on the losses incurred is impossible — given that there are different methods of tracking and reporting such incidents — the typical loss from pilferage can range from 1% to 5% of annual revenue, depending on the level of control retailers have over their outlets, says Chua.

“In really poorly controlled environments, we have seen it go up all the way to 20%, but this is quite rare and it happened in a bookstore chain. The losses from pilfer­age can significantly impact an otherwise good business model,” he adds.

The social aspect of sweet­hearting in the retail industry also cannot be ignored as there are serious implications since it undermines trust and integrity within an organisation, says Zai­nudin Nordin, executive director of Cue Southeast Asia. Estab­lished in 2018, Cue uses big data and artificial intelligence (AI) to address different pain-points for businesses and showcase how the tools can be applied to improve decision-making processes. Its partners include Under Armour, LBX Pharmacy, Hyundai, emart24 and Tous Les Jours.

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Zainudin explains: “Obvi­ously, the people who do it interact with customers the most, and likely see it as a way of ensuring good business for themselves. The motivation can range from better tips to wide social connections within the community. A cashier might scan only three items but re­move the security tags on four, allowing the customer to walk out of the store, supposedly without consequences. He or she might even do it for a fel­low employee for any number of reasons, but ultimately, it puts everyone involved in a vulnerable position.”

He adds: “Many employ­ees may think these actions have minimal impact, but it is the most common form of theft in retail. According to some surveys, almost 70% of respondents actually admit to sweethearting.”

Following the MOU, Sycarda and Cue are currently piloting bespoke retail solutions to ad­dress pilferage and sweetheart­ing issues at a local grocery chain. The partners jointly developed the solutions using data analytics, visual AI and machine learning.

In this Q&A, Chua and Zai­nudin talk about how having better supply chain vigilance can improve business operations and customer experience, especially for small and medium enterpris­es (SMEs) where this problem often goes unaddressed.

Sweethearting can be difficult to detect. How were retailers addressing this issue before data-driven solutions were available?

Chua: We have clients who have tried to overcome this challenge manually. They purposely em­ploy an audit team whose sole job is to review the CCTV foot­age to catch suspicious behav­iour at their stores. But sweet­hearting is still challenging to detect as cashiers can pretend to scan items when they’re ac­tually not.

So, our solutions will help them automate the capture of sweethearting by comparing the number of items we count using video analytics and the number of items on the receipt, thereby eliminating the reliance on team members manually viewing the CCTV footage.

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Zainudin: Previous solutions have definitely not been cost-ef­fective. Some companies might address sweethearting directly, in, say, their monthly meetings or town halls, making it clear that there is a protocol for free­bies; but people who are deter­mined to do it or, again, have their own reasons, will simply find a way around whatever the company would implement. So, automating this kind of security is, essentially, the issue coming to a head.

Sweethearting is also described as a means to improve customer service and inflate satisfaction and loyalty by “hooking up” customers with merchandise and discounts. What is your take on this?

Zainudin: We’re very much aware that, in many cases, shopkeepers believe that they are securing better business, whether for the store or them­selves. We can empathise with that perspective. But again, most of these stores have policies in place for improving custom­er relations. There are proper channels for these things.

Chua: If offering discounts and favours is part of the business strategy, then it is acceptable. However, we are referring to unauthorised discounts and favours, which are an entirely different matter and result in financial loss.

Why is data analytics a good solution for curbing this long-standing problem?

Zainudin: It touches on many aspects of the retail journey. Data analytics would be as much of a preventive measure as it would be a reactive one, while also providing our clients with the necessary information to improve marketing and retail strategies, leading not only to a significant reduction in loss­es, but also to sustainable gains for the whole business.

Chua: By correlating sales data with CCTV images, we can identify fraudulent transactions more effectively and in real time, enabling retailers to react quickly and address any fraud­ulent behaviour. This method also provides clients with a better understanding of their customers’ purchasing patterns, leading to more cost-effective strategies in the long run. In addition, any efforts to reduce costs, especially in this season of inflation, can significantly benefit the retailer’s bottomline.

How does the Sycarda and Cue Group partnership address the challenges?

Chua: Through the correlation of sales data recorded by Sycar­da and vision analytics captured by Cue, we can efficiently de­tect and respond to fraudulent transactions in real time. This is particularly useful in day-to-day operations of convenience stores, where a customer may present five items for purchase, but the cashier only scans four items on the point-of-sale sys­tem, resulting in a discrepancy. With the aid of Cue’s vision an­alytics, the fifth item is captured, and a comparison can be made against the sales data captured by Sycarda. This will immedi­ately alert the supervisor, ena­bling him or her to react swiftly and address the issue of fraudulent behaviour.

Other use cases include cal­culating conversion rates; that is, calculating how many patrons who come into the store actually buy products or services from the store as opposed to just browsing.

How much will retailers save by using the solutions?

Chua: Based on our own case studies of how clients have uti­lised our platform to reduce their costs and [incidents of] pilferage as well as increase their reve­nue, we estimate that it will not be difficult for retailers to have a five to 10 times return on in­vestment on average by using these solutions.

This article first appeared in The Edge Malaysia, and has been edited for length

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