For most retailers, returns optimization begins in the warehouse or distribution center

At this point in time — only once the returned item has traveled its reverse logistics journey —does the sorting, grading and disposition begin. The next life decision only takes place after considerable time, expenses and multiple resources have come into play. By this point, the return item faces real depreciation in value and frankly is at risk of irrelevance.

What does this mean?

Most returns management solutions have some sort of stake in the optimal and efficient routing at this point in the warehouse. Essentially this means that once the returns are sorted, the software can now decide whether these items should be refurbished, recycled, resold or trashed. Resales scenarios may take several forms: recommerce, liquidation, back to the retailer’s shelf, etc. But invariably alternative flows such as recycling or trashing the returns trash involves more transportation and an often-unhappy ending of dumping or burying of all or parts of the item.

Returns optimisation in the warehouse is likely to be too late

Notwithstanding whatever optimization takes place, the truth is that by the time the returns hit the warehouse, there is very little chance of significant optimization. The commercial damage is already done. The carbon emissions from transportation cannot be un-emitted. The chances of losses are overwhelmingly higher than break even. As for the probability of resale, it drops with every day that the items remain out of circulation.

To be effective returns optimisation must start sooner

So, what is the solution to this situation? The decision making around returns routing needs to take place much earlier in the process. Your returns management software should kick in as early as the moment that the customer decides to make a return.

Why now?

At this point, you can ascertain and aggregate knowledge about the return, the returner, the potential partners authorized to handle, inspect, process, and resell the returns. The decision-making mechanism can determine where they are located, what the probability of resale is, etc. Returns management that uses AI and data in real-time — from the moment that that a consumer triggers the return process — should be the de facto standard for returns calculation and dynamic routing. This early bird decision making of the next best shelf could mitigate the reverse logistics back to the warehouse and accelerate the resale of the item. Better for the bottom line and the planet!

Why not even sooner!

How could it get even better? While real-time decision making from the time that the return is triggered is a tremendous optimization on the industry standard today, believe it or not an even more efficient scenario exists. Just imagine the possibility if *at the time of purchase* your software could already predict — not only the probability of return —, but also the probability of resale, amongst other things. This kind of information would go the distance to not only reduce returns, but also to prepare the retailer to line up necessary and optimal workflows and authorized partners, just in case the next best shelf is required, when the probability of return is high.Retur

Aiming for decentralization and multi-directional optimisation

At the end of the day, returns management needs to pivot from returns being orchestrated centrally in the warehouse, to an omnichannel, decentralized model. Using AI and data, every step of the returns journey is hyper-accelerated, calculated and optimized. Software, like OtailO, that already prepares your back-end systems for the returns at the time of purchase, as well as when the consumer triggers the process, are rewriting the returns paradigm.  Your warehouse should always remain a central and pivotal hub, but your returns optimization should not be deferred until it is too late.


Photo credit Sonja Langford on Unsplash