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OPTIMIZING RETURNS TO REDUCE MARGIN EROSION

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BY MICHAEL FOY

n the early days of e-commerce, returns flew under operation’s and finance’s radar, and perhaps rightly so. The volume of e-commerce purchases was low, and returns were minimal and simple. During these early days, returns meant including a preprinted returns shipping label in the original package, which put the onus of the return squarely in the consumer’s court. Quantifying the cost of returns was basically relegated to parcel transportation costs and determining the returner’s share of that cost. Amazon’s returns model and the pandemic changed the rules — and the tools — of engagement. E-commerce sales grew by 32% from the previous year, while returns grew nearly five times that amount. Consequently, returns management became a top priority for many forward-thinking trading partners. Margin erosion from excessive returns began eating up bottom-line dollars, but to what extent remained a mystery.

While margins and return costs vary greatly by industry, company, and category, trading partners are being forced to measure and address their returns practices to avoid further diluting their hard-earned profits. Therefore, product returns have secured a spot on the executive’s “short list.” Typically, companies fall into one of three classifications for returns management and processing.

in place. However, they are not proactively mining their data; therefore, insights are limited — which is a key barrier to improving the returns process. As the saying goes, “You cannot improve what you cannot measure.” Companies in this classification will soon step up their returns effort as they learn business-asusual is not a sustainable approach.

Early Adopters The early adopters, seeing the writing on the wall, understand returns-related costs and are actively engaged in implementing solutions that provide intelligence and visibility into the post-purchase activities and behaviors of their consumers. They have embraced score-carding consumers and are actively adjusting return policies accordingly. Early adopters are also incorporating rules-based engines, machine learning, or AI to identify optimal disposition methods to maximize value recovery and minimize environmental impacts.

The Laggards The final classification is the laggards. These companies view returns as a necessary evil — one that cannot be stopped without risking the loss of a shopper. To combat the escalating cost of returns, these companies often focus on top-line growth. This, of course, can exacerbate the issue until they clearly understand the hard and soft costs of returns. Once this is determined, they can begin improving returns processes and policies by comparing these costs to the lifetime value of a customer. All companies, regardless of classification, must embrace returns as a non-linear process and suppress the urge to reallocate resources from forward logistics to reverse logistics.

Taking Care of Business (TCB) Companies in the TCB category have mature returns models and processes

24 PARCELindustry.com  SEPTEMBER-OCTOBER 2021

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