New methods, technology turn reverse logistics woes into an opportunity, Supply Chain Dive

New methods, technology turn reverse logistics woes into an opportunity. Dive Brief: With the average retailer realizing 30% of annual sales during the holidays, coupled with a 24% return rate, technology now plays an important role in minimizing these reverse supply chain costs, Retail Info Systems News reported last week. Multiple methods exist to optimize the return management process, which includes repair, refurbish and resell versus direct customer pick-up; return and restock or even disposal, resulting in write-offs. Reverse logistics, or the process of regaining value from an item that's returned is an expensive process, and companies are exploring ways to extract value in a process that many companies struggle to manage, which ultimately hurts the bottom line. Dive Insight: Returns, while never the preference of retailers, are a necessary component of the sale of goods. As consumers continue to be more exacting in their expectations of product, reverse logistics management is essential to remain competitive. Through proper management, returns can morph into a positive factor for retailers, if they're viewed as an opportunity rather than simply wasted effort. Further, returns can provide vital information that will ultimately aid in streamlining the company's operations. The main issue with returns, of course, is mining for value in what is, at least at the outset, a lost sale. Rather than junking or marking down a returned item, accurately assessing its place within the reverse logistics process is a potential means of creating value, but companies must find that value first. And, while traditional methods of in-house processing still exist, many start-ups now exist to make the process not only easier but more lucrative. This is the space that new technology and tech start-ups can enter to help retailers find hidden value. New companies such as Optoro, which focuses primarily on optimized reverse logistics process, applies algorithm-based analytics to determine the best way a retailer can recoup lost sales, and potentially even spur consumers to make additional purchases.