One of the greatest challenges to warehouse management isn’t getting product out the door but handling it when it comes back.
I was 16 in 1967, when I began to work summers in my father’s natural foods warehouse. That first year, I got assigned to the worst job in the entire warehouse. The aptly named “bug room” was a dank, dark and smelly, bunker-like hold, filled with broken jars of sticky molasses, weevil-infested flour, moldy vitamins and hundreds of other returned goods in various states of ickiness. My task was to log each and every item, make various marks on a clipboard and turn in papers to whoever was monitoring inventory.
Lost revenue from returns totals an eye-popping $600 billion annually worldwide, according to various research studies. Put that in perspective: Americans spent $1 trillion during the last holiday season. Returns average 8% of totals, which would mean Americans shipped back some $80 billion worth of goods from that period alone.
Reverse Logistics Trails Forward Logistics
Despite these alarming statistics, technology around reverse logistics has trailed behind forward logistics.
Reasons for the historic lag are many: Retailers have, until recently, looked at returns as almost solely a cost of business, not a potential revenue source. Getting goods back from the customer is more convoluted, expensive and time consuming than shipping to the customer. It usually requires some kind of interaction with customer service, then a trip to the post office or drop shipping center with a box that may or may not be properly wrapped and secured.
The whole process at the warehouse also is much more complicated than forward logistics. Where the particular item heads is a function of its condition, resale value, what its return means to inventory as a whole. Determining the condition of an item is a labor-intensive activity, which, by its very nature, is hard to automate.
With so many challenges, many retailers have defaulted to the quickest and easiest approach: Simply toss return goods, or outsource returns to a third-party provider and wash their hands of the entire process.
“It’s natural for the retailer to focus on selling their product first and not putting the same emphasis on the returns process because it represents a smaller percentage of the revenue in their business,” said Michael Manzione, president and CEO of Rakuten Super Logistics, the US fulfillment arm of a Tokyo-based ecommerce company. “What they typically miss is that this can be the difference in their profit and loss for the year, those smaller details like returns.”
A growing number of technology providers has begun to concentrate on the returns process, with much of the impetus coming from advanced software systems. Others are laying the groundwork for future technology breakthroughs. Robotics and machine learning will take longer to develop, but are definitely on the horizon.
Those in the industry believe this technology drive will only accelerate in the months and years ahead and impact all aspects of the returns supply chain, from transport to recycling, restocking to reselling.
“There definitely has been a technology lag,” said Emma Hawkins, London-based associate director of the logistics consultancy arm of real estate giant JLL. “But it’s quickly catching up [to forward logistics], and that’s purely driven by the need to meet that consumer expectation of being able to return. Our behavior is changing. We buy to return.”
Visibility is one watchword that’s often tossed around. Just having better knowledge of where an item is at any point in time is essential. That’s become standard in forward logistics, but hasn’t been nearly as developed in reverse logistics. Technology is necessary.
“Anybody who is handling distribution needs had better visibility into returns that are coming back,” said Kirk Waldrop, vice president, supply chain operations for the supply chain consultancy, Chainalytics. It starts with the customer’s decision to send something back. “More often than not there’s not a robust process or technology in place for customers to setup a return authorization,” said Waldrop.
Some of the breakthroughs are coming from existing technology that can be repurposed for reverse logistics, said Brian Thompson, chief commercial officer at SMC3, a data and technology provider for the trucking industry. “There is better connectivity between shippers, retailers and carriers,” said Thompson, citing transportation management systems, which assist in scheduling, dispatching, and track and tracing. “All of those things are starting to generate some additional interest on the reverse logistics businesses.”
Streamlining returns is necessary for recovering more value from those items, said Manzione, who added that for many retailers, there are months between the time a product is returned and it’s processed, by which time it holds little value. “Think of the disruption to the supply chains in terms of inventory levels and how the time is lost between selling the product having a return determining its value to return back into inventory reselling and the actual sale again for the second time,” he said. “The shorter you can make that time, the better your chances are of recovering some of those lost dollars.”
Big Data and Costly Returns
Just as advanced data analytics are proving more and more valuable for forward logistics, they are critical for better understanding returns, everything from the time it takes a consumer to return a product to when in a buying season or a product cycle there’s a greater chance for returns. Big data can be applied, not just to assess returns, but to better understand consumer buying patterns. This can help determine future demand, knowledge that can be applied to everything from marketing and pricing to order patterns from suppliers. The more data on returns that can be analyzed, the more likely returns can be trimmed in the future.
“It’s incredible how much data we’re collecting on consumers now,” said Manzione. “We’re creating profiles that are unique to not only the individual but we can cross-reference across multiple consumers, across all consumers, to really understand patterns that will reduce returns.”
Returns technology providers “are trying to help customers get their arms around all the different types of analytics surrounding returns and how to make better decisions about how to avoid returns, how do you make better decisions on your purchasing and your forward logistics forecasting and how do you get better prepared for returns that are coming back,” added Waldrop.
Those in the industry see a point where data analytics will predict the odds that a good is going to be returned, and when, which will allow retailers to build that probability in their costing model, both for the product and for the individual buying it.
Manzione, for one, pinpointed retailers who provide goods on a monthly subscription model as being in the forefront of this trend, citing cosmetics and baby products as two successful categories. They are using data to make better decisions on what goods to offer. “The returns to those companies are going dramatically lower month to month because [these companies] have a better understanding based on the data they’re getting on what the consumer wants,” he said.
When the Last Mile is the First
The warehouse, itself, easily suffers greatly from a lack of returns-related technology, whether that warehouse is completely or just partially dedicated to returns. To begin with, it’s hard to plan space allocation in the best of times. “Returns are not pretty,” said Waldrop. “It’s going to be the biggest mess you’ve ever seen on a pallet. It’s going to be misshapen boxes stacked every which way and they’re all broken and things are falling out.”
But that’s exacerbated by a lack of advanced warning, which technology-driven systems can help overcome. “There are some more specific challenges around a lack of visibility, and obviously, it is even more difficult to predict the demand of what returns will be coming through that door. And if you don’t necessarily know what is coming back, that is where technology and AI have a role to play in terms of helping that process,” said Hawkins.
On the transport side, the objectives are the same, but the challenges are different. “The main goal right now is to reduce the cost of returns while maximizing customer satisfaction,” said Thompson. This translates into customer convenience and ease, coupled with better and more predictable shipping. He pointed out that so much effort has been put into last-mile delivery. But with returns, last-mile becomes first-mile, with different challenges, including consolidation and repackaging.
Again, data analytics will help. “Data aggregation and analysis can lead to removing operational bottlenecks, making sure you’ve got capacity in the areas where you need it,” Thompson said.
While software systems are increasingly available and being applied to returns, dedicated hardware is further down the road. So far, at least, robotics hasn’t come up with a solution for completely automated sorting of returns, the same way robots can now pick goods. It will take computer vision that can determine a lawnmower, a screw, a couch, a dress and a lightbulb in one bin, a tough task for even the most advanced robots.
And the criteria for determining resale condition for, say, an iPhone is far different from a toy phone.
