Retailers are facing a growing strategic crisis as global product returns surge past US$1 trillion, straining operations, eroding margins and frustrating customers. With consumers increasingly treating returns as a routine part of shopping – and pushing back hard against stricter policies – Trevor Jordaan, Industry Strategy Director at Blue Yonder, explores how retailers must rethink their approach.
Throughout the global retail ecosystem, product returns have become a strategic issue. Savills research revealed that customers were expected to return US$1 trillion in goods globally this year.
While a significant proportion of returns is due to products reaching consumers in a defective or damaged condition, or in the wrong size, consumer culture has evolved to the point where returns are now a routine part of the shopping process, with many customers ordering items they do not intend to keep.
It is a situation that is putting retailers in an increasingly difficult position. Despite returns policies varying from one retailer to another, there is a level of obligation across the board. On a practical level, however, returns impose significant costs and operational overheads. Every item sent back must be received, inspected, rerouted and reprocessed, often moving through disconnected systems that slow down the process.
For many organisations, the sheer volume of returns creates a heavy administrative load and the longer products sit in the returns chain, the more value they lose — especially in fast-moving categories. As a result, many retailers are re-examining their returns policies to minimise the number of products returned. This includes increased return fees, more return rejections, reducing or eliminating ‘keep it’ returns and implementing much stricter return windows and eligibility rules.
While changing returns policies may make business sense at first, consumers are increasingly pushing back against anything that adds complexity or limits their options. Recent industry research revealed that 84% of global consumers say they would stop shopping at their favourite retailer if returns policies become stricter. Additionally, 66% are deterred from making a purchase when policies tighten, while 53% believe stricter policies are inconvenient and unfair. Retailers therefore need to consider their options carefully — not least because 50% of consumers say returns fees are the most inconvenient aspect of tighter policies.
Something has to give
From the retailer’s perspective, the current situation is increasingly unsustainable. At any given moment, millions of pounds’ worth of inventory is held by customers, creating blind spots that distort demand signals and inventory decisions. When returned items move through disconnected systems, they are often invisible to planning teams. This lack of visibility can easily lead to overbuying, as planners compensate for stock they believe has been sold but is actually in transit for return.
For example, if systems show 100 units sold without accounting for the 30 units in return transit, planners are left chasing ‘ghost demand’. This results in a repeated pattern: excessive purchases, swelling inventory and margin erosion, with sellable items often sitting unseen in the returns chain while customers elsewhere face shortages.
So, what can be done to address the impasse between business objectives and consumer demand? For many retailers, the first requirement is a change in mindset — viewing returns as a strategic inventory stream rather than merely a reverse logistics process.
In this context, technology infrastructure and returns processes should be aligned to integrate returns data across all systems, enabling more intelligent forecasting and faster, more precise replenishment. Ideally, real-time visibility enables returned items to be allocated immediately, preventing stockouts in other locations.
AI tools are also playing an increasingly valuable role by directing returns to the location with the highest demand rather than defaulting to a central warehouse. For example, a jacket returned in one city can be routed to another region with stronger demand. This level of integrated visibility can help retailers cut inventory levels by up to 30% and improve promise accuracy.
Returns data already contains signals about actual customer demand that traditional sales data misses, with AI offering a route to unlocking new insights. For example, high return rates for specific sizes, colours or product types can highlight sizing inconsistencies. Similarly, items returned for comparable reasons can expose quality issues in certain SKUs or supplier batches, while geographic return patterns also reflect regional preferences, helping refine allocation decisions.
The underlying point is that returns forecasting can become as important as forward demand forecasting, especially for seasonal merchandise. By establishing these capabilities, transformational process improvements become far more achievable, giving retailers the ability to make better buying decisions and avoid unnecessary stock accumulation. Looking ahead, there is genuine potential to deliver a win-win — where retailers operate more efficiently while consumers continue to receive the returns experience they expect.
