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Home » Blogs » Think Tank » Hyper-Automating the Retail Returns Process

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Hyper-Automating the Retail Returns Process

A WOMAN IN HER LIVING ROOM GESTURES IN DISMAY ON THE PHONE OVER AN OPEN SHIPPING BOX

Photo: iStock.com/Liubomyr Vorona

May 25, 2023
Guruprasad Nagaraja, SCB Contributor

The problem of omnichannel retail returns is one that must be addressed.

Returns currently account for about 16.5% of overall retail sales, and the amount of merchandise returned as a percentage of holiday sales surged by 17.9% in 2022.

Despite those numbers, many retailers are reluctant to tackle the problem. Yet there are significant benefits to be derived from automating the returns process, and orchestrating it for a better customer experience.

The following chart showcases a typical returns process that most retailers follow, using “returns to warehouse” as an example.

At a high-level, retailers employ a third-party logistics company to pick the items after the customer creates a return order on digital channels. Under optimal conditions, this could take between three and five working days for the 3PL to bring the items into the warehouse. 

Depending on the season, it could take the warehouse another three to five days to receive the returns and begin processing them, which includes matching the package with an air waybill (AWB) in the manifest, opening the package for quality control, and scanning the items as received. A refund is initiated only after 10 working days after the customer created a return order on their mobile app.

However, a lot of things can go wrong that could exponentially increase the processing time. The customer might have packed the wrong item; it could be damaged, or it could belong to another brand. Warehouse personnel have no means of reaching out to the customer for an explanation of these exceptions, leaving Customer Care to sort it out. Herein lies the issue of adhering to service-level agreements (SLAs) and standard operating procedures, with personnel processing the returns forced to put them on hold, and place them in a special area pending the customer’s decision.

Guru 1.png Figure 1. Drawn, difficult and delay-ridden retail returns process.

Coming back to the best possible scenario, it could take two to three days more for warehouse personnel to pick up the successfully processed items from the returns area, and take them back to the receiving dock. That, at last, is when items are checked back into the pool of available inventory for others to buy.

Banks, meanwhile, have their own SLAs for processing refunds, which typically ranges between two and four weeks. With about 10 days to initiate the refund, and another four weeks to process it, the retailer is usually failing to fulfill its promise to the customer. In some countries, retailers could be violating the e-commerce law with delayed refunds.

The returns process is lengthy for a reason: too many parties are involved. Transactions must meander through many applications and personnel in different departments, none of whom can take responsibility for orchestrating the process from end to end. The result is a huge backlog of unprocessed returns.

The following illustration lists all of the applications involved in the returns process, and the underlying gaps.

Guru 2.png Figure 2. Applications and gaps involved in processing returns.

Given the sheer magnitude of this problem, no amount of cursory fixes in the form of analytics, offers of free shipping, QR Codes or an increase in drop-off locations will solve it. Business, IT and executive leadership must come together to acquire a deep and ingrained understanding of the systems and processes that are in place. In addition, they should draw on technologies such as robotic process automation, artificial intelligence, machine learning and low code/no code platforms.

The following illustration shows the key “mantras” that make up an effective returns process.

Figure 3. Simple and elegant retail returns process after hyper-automation.

It’s the responsibility of the retailer to head off delays through seamless integration, and automate the search for e-mails and the processing of manifests. A simple app with well-orchestrated process flows, via low code/no code platforms, can enable returns personnel to choose the right kind of exception, and let the system take over. Retailers can use AI to interact with customers, solicit decisions and resolve exceptions. Customer decisions can in turn trigger notifications to banks for refunds, or retailers can resolve it with the bank in the background, and refund the customer immediately. Lastly, as soon as returns are processed, a new location can be tagged to the received inventory, which can then be made available for purchase.

Within four to six months, retailers can transform the returns process — provided that they’ve adopted “return on experience” as the sole metric for measuring their brand’s performance. It’s not too late to make “transformation of retail returns” part of their Strategy 2025. The alternative is an increase in unhappy customers, who will abandon the brand and share their experience through social media. In time, returns will become the iceberg that sinks the retailer’s Titanic.

Guruprasad Nagaraja is enterprise architect at Tietoevry.

Reverse Logistics Quality & Metrics Apparel E-Commerce/Omni-Channel Retail

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