How to Reduce Shrink by Flagging Sales Reducing ActivitiesRetail
As retailers search for new ways to engage with customers, they are also seeking new ways to detect formerly hidden losses. These losses, known as Sales Reducing Activities (SRAs) include activities that:
- Indicate fraud and/or unintentional loss
- Are detectable using analytics
- Can be controlled or reduced through changes in policy, procedures, or systems
- Reduce shrink when remediated
Protecting profits is critical for retail success. What should retailers look for to control SRAs in their organization?
Which Sales Reducing Activities Lead to Loss?
Transactional applications are the brains that link inventory, pricing, loyalty programs, and operations systems together. SRAs result when inaccurate adjustments occur at physical and e-commerce checkout. These SRAs include price adjustments, line voids, refunds, manual entries, coupons, tax overrides, and similar transaction alterations. These reductions may be fraudulent or unintentional but result in a loss of retail profits.
For instance, loss from dishonest employees can be especially damaging to any business. According to a 2020 Hayes International study, the average loss associated with dishonest employees was $1,219 per incident, nearly four times the value of a shoplifting incident ($310 per case). Theft from dishonest employees was up 3.8% in 2020 over the previous year, making shoplifting and dishonest employee issues a prime target for SRA identification. However, fraud and dishonesty are not always the reason for an SRA. The retailer themselves may be at fault.
For retailers, product pricing is dynamic, reflecting supply, promotion, location, and other factors. However, over half (53%) of shoppers report they sometimes or frequently notice a difference between the shelf price and what the retailer charges at the register. Often, retailers may issue weekly price changes, and in today’s challenging labor market, store leaders and associates have difficulty keeping up. This price verification gap results not only in losses at the register but potentially in compliance with local regulations. For instance, in Michigan, state law dictates that shoppers are entitled to a refund that includes a “bonus” of 10 times the difference, making the SRA 10X more damaging to the retailer’s bottom line.
Analytics reveals SRAs that include both customer and employee fraud. For example, customers who attempt “friendly fraud” by asking for a refund but not returning merchandise can now be identified through the number of transactions, credit card numbers, or addresses associated with the customer. Likewise, analytics can also detect e-commerce return fraud that includes shipping replacement items to the employee’s home address. Coupon, markdown, and employee discount abuse are also core issues that analytics reveal, helping retailers to recover lost profits and prevent future SRAs.
The Role of Analytics in Identifying SRAs
SRAs require more than observation but must use analytics that includes exception-based reporting (EBR) to identify potential trends.
Transaction systems offer a goldmine of information in each transaction, and EBR analytics can target SRAs and other risk variables. These analytics offer clues to the core problem that may exist at a particular store, product, or employee. Using trend analysis, skilled LP experts combine SRA data with other factors to identify the highest risk areas. For instance, students at the University of Texas at Austin were able to identify a strong relationship between SRAs and fraud for one retailer, segmenting the 20% of store locations at the highest risk. This type of analysis shows a correlation to overall shrink with transactions that include SRAs.
However, fraud isn’t always the primary issue. In some cases, a retailer’s systems or processes may be the core problem. For example, employees may use workarounds that make transactions easier for them and the customer. These workarounds result in unintentional or process-driven SRAs that are up to the retailer to correct by streamlining workflows, offering additional training, or upgrading systems.
Systems can also lead to SRA incidents. Today, retailers depend on POS systems that are starting to show their age, with 41% of retailers using traditional POS hardware that is more than five years old. Less than 20% of retailers have POS software that is less than two years old. As retailers look to invest in advanced POS systems that support omnichannel, mobile POS, and cloud-based tools, they also deal with aging hardware and software systems that can prove problematic.
SRA Fixes that Enhance Profits
The 2020 NRF National Retail Security Survey revealed that retailers are increasing their analytics arsenal by upgrading POS systems and adding refund history tracking tools. Top strategic priorities also include fighting e-commerce fraud and returns/refund fraud. For FY 2019, 18.2% of retailers reported >3% shrink, with an overall average of 1.62%, a significant increase since 2016.
The NRF survey also indicated that awareness and training are critical parts of LP programs, with over 95% of retailers discussing LP awareness during new hire orientation. Retailers engage employees with clear codes of conduct, offer anonymous telephone hotlines, and post public bulletin board notices to increase LP awareness. Internet-based training and videos are now used by 78% of retailers, and over half use honesty incentives that include cash and gifts. In-store employee LP committees exist for 40% of retailers, showing their commitment to fighting fraud by engaging employees.
But do these techniques work? One specialty retailer attempted to address a price override issue across the enterprise, using awareness and training programs. By adding analytics, they were able to identify district, store, and cashier-level exceptions that specifically identified brand and pricing inaccuracies. Using this approach, they reduced their SRA, benefitting from a $123,000 margin increase within 30 days and later reduced enterprise-wide promotions abuse by 40%.
As retail evolves and the checkout process migrates from the cashier to the customer, monitoring SRA’s is more important than ever. The potential for fraud and process errors vastly increases when the person checking out isn’t trained to do so. Nearly one in five shoppers will admit to having stolen something from a self-checkout lane either intentionally or unintentionally. By monitoring SRAs in these lanes, retailers can minimize losses associated with mistakes, theft, and fraud in self-checkout lanes.
Protecting profits is critical in today’s competitive retail landscape. Analytics can identify specific SRAs that drain profits, leading to specific corrective action that leads to quick results.
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