Automation experts explain how robotics can speed up reverse logistics

With the peak holiday season in the rearview mirror, warehouse managers are now dealing with another influx of movement: returns and reverse logistics.

Retailers expected consumers to return an estimated 19.3% of online sales in 2025, according to the National Retail Federation (NRF).

As retailers and logistics providers tackle this wave of returns, Automated Warehouse spoke with Kait Peterson, vice president of marketing at Locus Robotics, and Lior Elazary, founder and CEO of inVia Robotics, about how automation can help smooth the process.

What are some of the reverse logistics challenges for retailers, e-commerce companies, and brands?

Peterson: A lot of people think returns are just picking in reverse, but there’s a lot more that goes into it. It’s a lot more unpredictable. You don’t know what’s coming from where and when until the consumer initiates a return online.

For example, the item condition varies quite widely, and depending on what type of return you’re doing, whether it’s electronics or apparel, you have to disposition that right. You have to go through a process to understand whether it can be resold, whether it needs to be refurbished, whether it needs to be sent to a liquidator, or whether it needs to be completely trashed.

There’s a big change in how reverse logistics is being handled within the supply chain. More companies have announced charging for returns, because there’s so much labor and work that goes into the intake, the dispositioning, and then the restocking.

So, [returns] are a lot harder to plan for, a lot harder to standardize. There is a big peak after the holiday season, but it has become continuous. Consumer buying behaviors changed during COVID, when people started to buy two sizes of things, not just one size, and then return the one that doesn’t fit.

Elazary: I think a lot of businesses don’t have as much pain from reverse logistics as we always thought. It’s mostly because a lot of times, they end up just throwing this stuff away. If you think about it, the logistical issue is so expensive that a lot of times, it’s worth it for them to just throw [the items] away. The reason they tell the customer to return them is just so you don’t abuse it.

However, I think when they start using inVia’s system, we make certain things more efficient. As a result, they start taking on more and more, because they don’t want to lose that money.

But if you imagine trying to pay somebody the money to inspect [a returned item], to then file it away, and then to pick it again and do an inventory adjustment, all that stuff ends up costing a lot more than the items.

Now, obviously, if you’re buying iPhones, things that are in thousands of dollars, then they’ll bring it back, and they’ll charge it. A lot of the stuff that people come in with is not that expensive.

With our system, we get a manifest at the beginning of all the stuff that’s in a box. We’re able to parse these things out, not only to make a decision on what to do with the flow, but also to decide which things are not worth the logistics cost of doing the return.

Which pain points can automation help address?

Peterson: Locus is really effective, in particular, about addressing the variability and the labor dependency. When you have a fleet of robots, instead of having 10 more temp workers to handle it, you can have the same amount of staff but allocate more robots to reverse logistics.

For example, in a fleet of 100 robots at a customer facility, maybe during the peak Christmas period, 90% of those robots are allocated toward fulfillment, and 10% are allocated to replenishment and making sure the shelves are full and handling any off-item returns.

You can just flip that, if you need to. In January, you can have 50% of your robots on work directed by LocusONE that handle returns and replenishment. You integrate that with a returns management platform to walk through the workflows. That really helps with scaling capacity without having to add actual headcount.

Now, the physical automation handles things like bringing the items back to the stocking locations and being able to move everything through the warehouse. Because if you load up a robot with 25 different returns, those returns are going to be all over the warehouse, right?

So our platform can optimize, just like it does for orders. That walking time, that physical strain, all of that is on the robot. It really allows operations to maintain that performance and remain dynamic and flexible.

From a people perspective as well, our returns and replenishment are visually different on the iPad, with fulfillment on a white screen, and returns in night mode. So at first glance, associates know exactly what they need to be doing.

What types of robots are involved in returns, and how are processes different from outbound logistics or peak season?

Peterson: The key is really understanding what the workflows are and where the best solution is. So obviously, our focus is on AMRs.

They are traditionally used for transport. We use them for sortation. We use them for put-away and replenishment. Through all of that, we navigate dynamically between the picking, sorting, and restocking.

So, for example, if you have inbound items that have been dispositioned and they need to be put back into an ASRS, Locus can handle the transport from the disposition area to the ASRS area, where it can drop off the tote or whatever items need to go into it.

If there’s a sortation process, Locus Origin or Vector can pick up and drop off [the item] wherever it needs to go.

It really comes down to flexibility. Where are those areas in your workflows that need flexibility?

Elazary: There are a couple of workflows that we will be able to do. One of them is when you basically have a whole return zone.

So think of it as a big location where things get returned to, and then they take the outbound logistics from there. There are various rules around when you take things out from there, versus a new item, and there are some checks and balances.

In this reverse logistics zone, you have a bunch of mixed SKUs within one container. So with the picking format, the system has to be a lot more intelligent and be able to track things in a lot more detail in order to pick from, because every container is just a big mess in there.

We’re able to guide the person you have to go pick some things from one location, then go in through reverse logistics, pick it from there, and then move it over to outbound or shipping.

The other workflow is to replenish the containers that have those items in them. There aren’t that many customers that want to do that. They don’t want to mix the two items, where one of them is a used item and one of them is a brand-new item, unless it’s something that has very thoroughly checked beforehand.

Ultimately, it is about whether this item be sold as new, or is it going to be sold as used?

How are software and AI making operations more nimble, and where are human associates still necessary?

Peterson: So the key with this is what I know is on the top of everybody’s mind: AI. The LocusONE platform is really our orchestration platform layer. It takes and optimizes all of the work that needs to get done and feeds it into the platform.

The key to that is the data. We have billions of data points to be able to smartly direct where the work needs to go in what order.

It also means that you can work in validation, particularly if you’re thinking about things like returning or putting away medical equipment, or things with serial numbers. You can require additional scans to make sure you’re putting the right item back in the right place.

You really want to have applied AI around all the different capabilities of the software platform, and that allows you to rebalance work as the volumes are shifting.

At the end of the day, automation can reduce the overall strain and the mental load that the associates actually have to do to make a decision. We’ve got a system-directed labor now, which is part of our LocusONE platform, which tells the associates specifically where and what to do next.

Elazary: One thing that’s a bigger difference right between our system and a typical WMS is that in the typical WMS, you have to create workflows and hire engineers to program them into it. With our system, you give it business rules or business constraints.

For example, every return has to go through this inspection process, and then you have to put it into a separate container. That’s your business rule. That has nothing to do with the constraint. That’s how you want to run the business. That’s what you tell your customers.

Then the AI basically solves the best way to achieve those business rules. So it’s not that the AI is necessarily making those rules. In fact, the fewer rules you give it, the more efficient it will be.

So we give you this balance where you can load up the system with a lot of business rules, but then at the end of the day, you constrain the optimization process. So it tells you, “If you remove this rule, if you remove this thing, you’ll be able to be more efficient.” So it’s all about how dynamic the workflows are.

The warehouse manager now basically can understand, “OK, these are the business rules that we want to follow. These are the business rules that we don’t need to follow, because they’re actually inhibiting our optimization process.” So they’re able to remove that, and then the system just adjusts to that.

Can you give some examples of reverse-logistics operations that have benefited from your companies’ technologies?

Peterson: One is nGroup, which is a 3PL [third-party logistics provider]. We work with it, as well as with its Optoro returns optimization platform.

It had a 229% increase in lines per hour. The company does about a million units of put-away per month because it’s a 3PL for a large retailer, and their inventory mix is insane. Think about everything from something super small to something large. nGroup has a very complex disposition process that we worked on.

The key is that it has gone over a year without any OSHA-recordable incidents. The employees are much happier because they actually don’t have to ask as many questions or make as many mistakes.

The robots help them do the work. It’s really cool to see how the reverse logistics part is being fulfilled with automation.

Elazary: CarParts.com handles any car parts under the sun, which makes it very, very challenging, because you have anything from small bolts and screws and lights to huge bumpers, big wheels, and engine parts that are heavy. Trying to manage that does become a problem.

We started dealing more and more with those kinds of customers, because they have the biggest need for those kinds of optimizations. If you’re just doing a very limited number of SKUs, then the challenges are not as much.

If you’re trying to return bumpers, it becomes logistically a lot more complex. The nice thing is, our system calculates these costs, so then it can also tell you what you do with that.

What key performance indicators (KPIs) are your customers looking for, and have they changed in recent years?

Peterson: The overall theme, I would say, is operational confidence. They want confidence that their operations can run smoothly and error-free.

So that means throughput stability, being able to handle not just the 90% outbound and 10% inbound returns, but what if that flips? How quickly can they make those changes? Can they reallocate the workflows on the fleet? Do they have to do actually have to do it, or can the system do it itself?

Obviously, customers are focusing more on scalability and integration speed. The ability to absorb that change without disruption is a core success metric that ties back to being able to handle whatever is coming.

We still don’t know what the return season is going to look like. But our customers are ready with their fleets and their processes, so they have that confidence in their operation.

Elazary: All of them are interested in the bottom line. So there is ROI [return on investement], which is, “How much is it costing me to deal with these certain things?” There’s direct cost savings, like, “How many people can now do the same job as opposed to doing it before?”

We had one customer with a million-square-foot operation, and a lot of people are involved in making the decisions. He said, “I get paid to think from the neck up. But as a result of the systems that they had previously in place, there was a lot of work that I had to do from the neck down.”

There were big consolidations that were getting stuck, and the items weren’t flowing through because the consolidation one was getting full. So there are some more customers calculating how much automation is helping solve for those high earned people who now don’t have to do it, and they can concentrate on doing better work.

We’re able to not only save money on the labor part, which is usually maybe around the 50% mark, but also the other 50% that’s actually in the reporting. And it’s not just reporting; it’s prediction simulations.

We’re able to tell them, with pretty good accuracy, what kind of resources they’re going to need. It’s not just people. They need more carts. They need another system to increase the robot system.

In addition to the post-holiday spike, are there other periods or industries where reverse logistics are important?

Peterson: Apparel is year-round. As I mentioned, our buying behaviors have changed. People buy two pairs of shoes, two pairs of pants, two pairs of shirts, and then they plan on returning half of them. So our buying behavior has changed. Apparel, footwear, and things like that are year-round, related to fit and fashion cycles.

With electronics and consumer goods, they manage the refurbishments, the recalls, or warranty returns anytime. Let’s say a new device comes out and launches, and people may not like it and return it.

If you think about 3PLs and subscription-based businesses, that’s part of daily operations as well. So, for most of our customers, it’s a part of a permanent workload, not just a temporary surge. There also some companies that do returns processing in a separate facility.

There’s a reason why companies are starting to introduce return fees for restocking, because it’s no longer just a peak season thing. It’s an always-on thing, and it’s really creating a lot of pressure for the businesses, which is why they’re starting to disincentivize people from returns.

Free returns have been an expected thing lately, and while it incentivized people to buy up front, it created a whole lot of supply chain challenges on the back end.

Elazary: We deal a lot with OEM customers. One of our customers is SICK, which makes sensors that robots use. On one hand, they manufacture some things to order. If it’s an expensive item, if you don’t want it, they will take that return.

And one of the challenges there is, how do you file that? This is a little bit more on a business rule that the comnpany has to decide, but that’s where some of the challenges happen.

[SICK’s] industry is also sort of seasonal, because it follows the seasons of other manufacturers. As they have more volume, they need more need more of the auxiliary items to support safety and their business.

What opportunities are there for robotics and data collection to further improve returns?

Peterson: I think the biggest area for improvement is continuing to focus on flexibility and optimizing the process. Returns can be more expensive. Rather than an expensive manual process, robotics can help you to think creatively and flexibly about those processes.

Elazary: So far, whenever we’ve deployed our system, we always advocate for actually deploying the software piece first before the hardware. Operations have different challenges because of the different business rules they’ve implemented.

This helps you to understand where exactly your costs are. Where are you experiencing the most drain, and where can optimization and automation help first? This is something that our software is able to identify.

We notice that, a lot of times, the process you might be automating doesn’t necessarily have the best value. We had one customer that had almost 40% inventory mistakes. Fix that first.

That’s why I really emphasize that customers make sure they really understand where their reverse logistics problems are. That’s not necessarily an easy thing to do.

As you start to clean up things inside the warehouse, you’re enhancing everything. Then you bring in automation, and the robots will just shine and work really well.