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Reverse logistics: how to cure the E-commerce pain

SHD Logistics - Reverse Logistics - June 21.jpg
Emile Naus, partner at management and technology consulting firm, BearingPoint, discusses the challenge of returns.

Most pictures of supply chain flows show a nice, straight line of products going from suppliers to customers, and cash going from customers to suppliers. However, this disguises the fact that sometimes products and cash will go the other way. Returns have always been a feature in supply chains, but E-commerce has put returns much more in the spotlight.

Everyone who is involved in E-commerce will be familiar with the challenge of returns. It is typically a very expensive flow to manage, with small quantities being returned by customers, requiring inspection, before putting the product back into the pick face. In reality, the returns management cost per item is typically a factor larger than the original picking costs. And to make it worse, the best case scenario is that the business isn’t getting paid for this activity since it is an unwanted product; the worst case is that the company also picks up the transport costs.

Whilst there are some interesting options to improve the costs of reverse logistics, it is even better to reduce the level of returns in the first place. In most cases, the root cause is in the design of the product, the description and pictures on the website, and the selling process.

Clothing is notorious for high returns levels. The complexity of colours and sizes makes it harder for the customer to pick the right product, and we regularly see examples where customers buy the same product in two sizes and multiple colours, just in case. There have been some experiments with body scanners, linked to the actual product dimensions, but the fact is that clothing sizes are inconsistent between retailers (and in many cases within the same retailer!). Colours are difficult to represent on-line and whilst some businesses experiment with virtual reality, the success rate is still pretty limited.

There is a second element to root cause, which is the customer behaviour. We have seen consistently that a small number of customers are responsible for a disproportionate level of returns. Whilst there are multiple reasons, there is often a small core of customers who buy products, use them (typically once) and then return. Data analytics can be used to identify this behaviour.

Once a return is issued, time is hugely important, and often ignored. Products have a lifecycle, and time spent when the item is not available for (re-) sale is increasing the probability that the item will have to be discounted or even destroyed. The faster the item can be restored to the point where it is available for sale, the better it is. Inspection is equally important to ensure that items that are faulty or damaged are either fixed or filtered out. Packaging plays an important role, as damage can be superficial, but the subsequent customer might reject a ‘second hand’ item purely based on cosmetic damage to packaging.

Recovery of value can be substantial through a thorough inspection process. Typically, items can be split into pristine, functionally good, repairable and beyond economic repair. In the last case, there may still be an option to recover value through recycling of components. This not only has a positive effect on the financial performance, but equally should be promoted as a way to reduce the environmental impact.

In terms of returning the item to stock, the end-to-end process becomes important. Typically, returns will be received in small quantities, making the physical handling difficult and expensive. There are some interesting options where returns are kept in multi-SKU locations, with the aim of picking these first before existing stock is used. The logic in this system is that returned items are typically relatively fast-moving stock and therefore will be picked.

There are some good options with automated solutions that facilitate this process, and in some cases seamlessly integrate this into the wider storage and picking process. But even in a manual operation, this can be applied successfully as long as the Warehouse Management System supports a level of flexibility around picking logic.

Further analytics often can support this. Based on forecast data, stock can be positioned in the right pick locations to speed up the process, and orders can be fulfilled in the most effective way.

In conclusion, reverse logistics is not going away, and is likely to become more important. Prevention is less painful than the cure, meaning that the core focus should be on understanding the root causes of returns. The second level is to really understand the business impact in terms of cash flow and potential waste; a good inspection and recovery process will drive substantial value, and time is critical.  Finally, there are some good opportunities to handle returned products to minimise the additional costs and maximise the re-sale opportunities.

As usual, taking an end-to-end view of the operation, combined with the application of data and analytics, can support the business and improve operations.

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