Using data to support reverse logistics

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Dominic Potter, General Manager, International at Logistyx Technologies explores how to use data and analytics to tackle the reverse logistics challenge.

Dominic Potter_V1.jpgThe COVID-19 pandemic has prompted more people than ever to embrace online shopping. The downside for ecommerce companies, of course, is that this has triggered an explosion of product returns. In fact, it is estimated that approximately half of UK shoppers have returned items they bought online during the pandemic period. And 12% of shoppers admit to returning products because they are choosing to use home deliveries as a ‘try on’ service. In sectors such as fashion, consumers are ordering multiple styles, sizes, and colours to try, before sending back what they don’t want. At the same time, many retailers are extending returns periods and offering free returns, where previously customers may have had to bear the cost of returning unwanted goods.

On the other hand, for some companies, the overall cost of processing, collecting, checking, and placing returned items back into stock is not economically viable, so they are avoiding having to collect the returns altogether. For inexpensive items or large ones that would incur hefty shipping fees, the likes of Amazon, Walmart and others are choosing to give their customers a refund while letting them keep the unwanted order. It works out better for these retailers to bear the additional cost and keep the customer happy while avoiding the extra administration and reverse logistics challenge of processing the return.

However, for most companies, the pressure is on to find ways to reduce and manage the cost and volume of returns and to manage reverse logistics operations more efficiently. There are two clear ways to reduce the cost to the business: cut the total volume of returns and find ways to optimise reverse logistics costs. And in each case, the first step to determine which approach to take is analysing the underlying data.

Cut avoidable returns with analytics

Some returns are avoidable, and data can be central to identifying and addressing the key causes. For example, examining the returns patterns can flag weak links and errors in fulfilment by tracing wrong product shipments to certain distribution centres or pickers or by highlighting recurrent problems that can be resolved by correcting inventory and warehouse management processes. It might be possible to identify frequently returned products and to investigate why they are so often sent back. For example, can they be packaged in a different way to avoid damage in transit?  Or is it a case of switching carriers?

When fulfilment errors cannot explain the pattern of recurring returns, analytics might point to potential merchandising problems. Do many returns originate from the same product or product category? Perhaps you should consider discontinuing those product lines altogether or only selling them in store.

Analysing routinely returned or problematic SKUs provides the opportunity to take proactive steps. It might be as simple as an incorrect size in the product listing, or something more serious, such as a product with a manufacturing defect.

Consumers often return products because product information was unclear or confusing on the website. Does the product description accurately explain the dimensions, features, and instructions for use? Are products returned because product colours online do not match the product colour in person? Or are customers ordering clothes that are too small or large because sizing information is inconsistent?

With proper visibility into returns data and a structured approach to extracting insights across departments, you can streamline operational workflows and take steps to reduce returns rather than react to them.

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Optimise reverse logistics costs by choosing the right carrier.

Some level of returns are probably unavoidable, so the emphasis here should be to try to reduce the cost of collecting and processing them. Some products, such as perishable goods, need to be collected immediately, while others can wait a little longer. And different carriers apply different rates and surcharges based on parcel size and volume and speed of turnaround as well as customer pickup location. By using a pool of different carriers, it’s possible to optimise the cost of returns by analysing and selecting the most cost-effective carrier partner for each returned product. Multicarrier transportation management technology can rate and rate shop all carrier services within a retailer’s transportation network and automatically identify the right carrier for each pickup. It will also produce the required labels and paperwork, allow users to track inbound shipments and audit the entire shipping and returns process to identify cost-saving opportunities throughout the fulfilment lifecycle.

Ensure good visibility of expected product returns

While most shippers recognise it’s essential to track parcels on the way to customers, many don’t place the same importance on having visibility of return shipments.

Leveraging sophisticated transportation management technology for parcel shipping that includes tracking tools for inbound shipments is key to efficiently managing warehouses and returns centres. For example, with an accurate picture of the expected volume of returns, retailers can schedule the appropriate number of workers to check and process returned goods so they can be swiftly put back in stores for resale. Doing this quickly and cost effectively is vital. Products in the hands of the customer, either pending return or in the process of being returned, is inventory that is unavailable to resell.

Another area that deserves attention is making the returns experience as simple and hassle free as possible for the customer. One growing trend is providing an immediate refund to the customer the instant the carrier scans the return parcel on the doorstep. While this runs the risk that the product might not be in resale condition, eliminating the wait for the refund encourages customers to shop with a retailer again and builds loyalty. Once again, it is important to keep a close eye on the data: how many returned products are not suitable to go back into stock and how much is this costing the business? 

Conclusion: Pay attention to the data

The expansion of ecommerce means creating an effective returns operation is more important than ever. By paying attention to the data and continuously running analytics, companies can proactively reduce or combat the growth of ecommerce returns. In many cases, this requires putting a team or person in charge of overseeing returns and reverse logistics and allocating the necessary resources and technologies to study the challenges. By paying attention to returns data it is possible to unlock a wealth of critical business insights.

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