With decades of experience navigating the complexities of global supply chains, Rohit Laila has witnessed the industry shift from a pure focus on speed-to-market to a more nuanced understanding of value recovery. As a leader who has bridged the gap between traditional logistics and cutting-edge innovation, Laila views the current state of retail through a lens of economic efficiency. He argues that the industry has reached a tipping point where the “back-room” process of handling returns is now a primary driver of corporate strategy. This conversation explores the transformation of reverse logistics into a sophisticated decision system, the critical importance of reducing decision latency, and the ways in which companies can reclaim lost margins by treating every returned item as a depreciating asset rather than a warehouse nuisance.
With online return rates currently hovering near 20% and the total volume of returns approaching a staggering $850 billion, how has the perception of reverse logistics shifted from a simple warehouse task to a major economic influence?
The sheer scale of the situation has forced a radical change in how we view the loading dock. When we look at the National Retail Federation’s projections showing U.S. retail returns hitting $849.9 billion, we are no longer talking about a minor operational headache; we are talking about an economic system that is large enough to dictate the health of a company’s working capital. At an online return rate of 19.3%, returns are influencing everything from labor allocation and transportation schedules to high-level fraud prevention and customer loyalty programs. For a long time, the industry framed this as a simple matter of moving boxes back to a center, but we now realize it is a margin battleground. If you don’t manage this volume correctly, the sheer weight of stranded inventory can sink your profitability, making it one of the most significant variables in modern retail math.
You’ve mentioned that the industry often frames the returns problem incorrectly by focusing on transportation. Why is the concept of “time-to-disposition” actually the most critical factor for a retailer’s bottom line?
The fundamental mistake is treating a return like a simple freight problem when it is actually a race against depreciation. Think about a high-value product, say a $300 item, that arrives back at a facility; at that exact moment, its value is in limbo and could range from the full $300 price tag down to a $100 liquidation unit or even zero if it’s destined for waste. Until a system or a person makes a definitive choice on whether it’s an open-box asset worth $240 or a refurbished unit worth $180, that item is economically frozen and losing value every hour. We see this most clearly in fashion or electronics where seasonal shifts and aging technology mean that a ten-day delay in making a decision is far more costly than the shipping fee itself. The real goal isn’t just moving the item efficiently; it is reducing decision latency so that a product that could have been resold on day two isn’t sitting in a “returns cage” until day twenty.
Many organizations try to manage returns by simply reversing their outbound fulfillment processes. Why is this approach fundamentally flawed, and how are companies like IKEA or Best Buy leading a different path?
The forward and reverse networks are night and day because a forward shipment starts with a known quantity, a set destination, and a clear customer commitment. In contrast, every return begins with a cloud of uncertainty regarding the product’s condition, the reason for its return, and the best path for its future sale. During recent discussions at NRF Rev, it became clear that the best players are building entirely separate operating models that prioritize value recovery over unit processing. IKEA, for example, has moved toward expanded buyback and spare-parts programs that keep items out of the waste stream and back in the hands of consumers. Best Buy has also shown leadership by using customer data to change how they merchandise open-box products, treating them as viable inventory rather than a pile of damaged goods. These companies understand that the physical move is just one small piece of a much larger decision-making puzzle.
If cost-per-return is no longer the “North Star” for measuring success, what metrics should supply chain leaders be prioritizing to truly understand their recovery value?
While keeping costs low is always a goal, focusing solely on the $8 or $11 it takes to process a unit can lead you to make very poor economic choices. If Operation A processes a return for $8 but takes nearly two weeks to decide its fate, they are likely losing significant value compared to Operation B, which might spend $11 but recovers $35 more in resale value by making a decision within twenty-four hours. We need to move toward a scorecard that tracks the time from return initiation to the final disposition decision and the percentage of inventory successfully recovered for primary sale. We should also be looking at markdown avoidance and the number of days inventory remains economically unavailable to the market. When you measure success by the total value recovered and the retention of the customer after the return, you start to see the true impact on the company’s margin.
How is the scale of modern returns starting to merge with mainstream supply chain planning and inventory policy?
Planners can no longer afford to treat the return stream as an invisible ghost in their data; it must be integrated into the core inventory policy. When you have hundreds of units of a specific product on their way back to various centers, it makes no sense to trigger a replenishment order from a supplier without visibility into how many of those returns will be sellable. We are seeing the traditional walls between warehouse management, order management, and planning systems start to crumble because a disposition decision requires data from all of them. Retailers have to ask if there is local demand for a returned item before they spend money shipping it back to a central hub. Once returns reach this magnitude, they aren’t just operational trivia—they are a critical component of how we manage global stock levels and working capital.
With fraud now accounting for a significant portion of returns, how can retailers protect themselves without creating a negative experience for their most loyal customers?
The reality is that about 9% of returns are fraudulent, and as organized schemes become more adaptive, the temptation is to simply tighten the rules for everyone. However, a blanket policy change is a blunt instrument that often punishes your most profitable, honest customers and can drive them away to competitors. The solution lies in making the return process more granular and segmented, treating a known customer with a low-risk product differently than an anonymous, high-risk transaction. If a customer returns an unopened item within hours of purchase, that should follow a “fast track” compared to a high-value electronics return with a serial-number mismatch. By using data to determine how much trust to place in each transaction, companies can mitigate fraud losses while still providing the seamless experience that modern shoppers expect.
As recommerce and secondary markets continue to grow, how does this change the traditional “pathways” for a returned product?
In the past, a retailer usually had a very limited menu of options: they could restock it, send it back to the vendor, or just liquidate it for pennies on the dollar. Today, the rise of refurbishment, repair, and secondary resale markets has turned the return into the potential beginning of a second commercial cycle. This complexity increases the need for high-quality data regarding product condition and secondary market pricing to ensure the best recovery path is chosen. It’s no longer just about getting rid of “bad” inventory; it’s about identifying which items can be refurbished to a “like-new” state and sold through specialized channels. We are entering an era where recommerce systems must be tightly connected to pricing and inventory availability, as a return is no longer an exception—it’s a new sales opportunity.
What is your forecast for the future of the “closed-loop” supply chain?
I believe we are moving toward a future where the strongest companies will operate what I call a “supply chain learning system” rather than a simple logistics network. The goal is to create a loop where every return provides a diagnosis—was the product description wrong, was the sizing inconsistent, or was there a recurring quality issue with a specific supplier? If we take that information and use it to correct the root cause in the forward process, we stop paying to learn the same expensive lesson over and over again. My forecast is that within the next few years, the distinction between forward and reverse logistics will blur into a single, circular flow of value. The winners will be those who can make the fastest disposition decisions and use the data from what came back to ensure that the next item going out never has to return at all.
