AI and the Reverse Supply Chain

Introduction

When designing their supply chains, companies typically seek to turn their products from raw materials to finished products in their customers’ hands as efficiently and profitably as possible. Ensuring that the links between suppliers, manufacturers, and distributors maintain a steady, reliable flow is one of their top priorities. In a perfect world, with no product defects, unsatisfied customers, or mistaken orders, this one-directional supply chain would be companies’ only concern. But what happens when there is an issue, and customers return products? How do companies resolve these problems in an equally efficient manner, instead of having to fight upstream against the current they’ve created? With the rise of e-commerce, and increasing commonality of product returns, creating and maintaining a well-oiled reverse supply chain is gaining ever more importance. Fortunately, new AI technologies can help companies adapt to evolving markets and demands along each step back up the supply chain.

AI and Return Request Receival

The first step in the reverse supply chain is the customer point of contact, in which the return request is initiated by the customer. Many online retailers have already automated this process, as seen with Amazon’s form-based return request system in both their app and website. Here, instead of relying on a customer service representative to field the complaint and assess return eligibility, AI programs automatically process the request and analyze whether or not the product meets eligibility requirements. This not only saves the e-commerce giant time and money in the form of wages, but allows the customer to have a faster, almost instantaneous resolution to their problem.

This situation applies to more than just the largest online retailers such as Amazon and Walmart. In fact, research from the International Council of Shopping Centers found that, on average, over 15% of products bought online are returned, with the return rate jumping to 22% for apparel. Companies of any size, and in any industry, that sell products online must factor in the likelihood of processing returns, as inadequate preparation would make their business unsustainable. AI automation of returns management can help small business owners spend more time focusing on issues that require hands-on involvement, instead of sorting through and replying to emails or phone calls from customers expecting refunds. Human capital can be put to better use by allowing AI to take care of the relatively menial and predictable tasks of returns processing.

AI Decision-Making

The value of AI becomes even more apparent in the next step of the reverse supply chain, in which a decision must be made as to what to do with the returned product. Companies must first answer the question of value before sending the returned product on its way. How much value can be extracted from the returned product, via remanufacturing or refurbishment? Is it more or less than the cost of simply sending the product to a dump? AI analytical tools can make these assessments, and then uncover the most efficient way to act upon the decision. If there is still value to be recovered from the returned product, AI logistics systems can determine the most time and cost-effective route to ship the product to a remanufacturing facility. If the product is destined for scrap or written off as waste, AI can find the nearest and least expensive scrapyard or waste facility.

With AI taking the lead in this decision-making process, companies can once again save valuable time and money. Instead of having an individual employee or team pour over the data to determine the best course of action, AI technologies can quickly analyze the available data and reach a conclusion. The value of automation doesn’t end there, as these AI programs can automatically place the shipping order and print the shipping label, directing workers in distribution facilities to handle the product accordingly in preparation for shipping. By automating these key components of distribution logistics, products move through the reverse supply chain much more efficiently.

AI and Remanufacturing

With the goal of the reverse supply chain being to recover as much value out of a returned product as possible, remanufacturing is among the most important steps, as it provides the opportunity for substantial value extraction. Whether the raw materials of the product are being recycled for the production of new products, or the product is being refurbished to be put up for sale, remanufacturing allows companies to minimize their losses and open up new avenues of revenue. AI advancements in product design, defect detection, and additive manufacturing can expedite and enhance the remanufacturing process. AI can even help companies analyze marketplace trends to determine how to price refurbished and remanufactured items, making sure companies aren’t selling themselves short and losing out on opportunities to create and maximize value. AI’s existing role in remanufacturing and its massive growth potential has encouraged great investment in the field, and you can find out about how the European Union is investing in AI for remanufacturing in our deep dive here.

AI can improve every aspect of the reverse supply chain to help companies achieve their goals more efficiently and effectively. By making faster and more accurate decisions, AI technologies can free up time for workers to put their efforts into areas AI is not yet able to contribute to, and ensure companies aren’t wasting their resources. For ecommerce giants and small online retailers alike, and everything in between, incorporating AI throughout the reverse supply chain offers companies new ways to enhance their systems, strengthen their margins, and improve their products.

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