Returns Management Software

Reverse Logistics

Reverse logistics is the intricate process involved in returning consumer goods to their original point of origin. In this complex supply chain maneuver, unwanted items are first returned by consumers before being sent to a collection center.

From there, products undergo preparation for redistribution to secondary outlets, where they are either recycled or resold. This demanding process requires meticulous coordination among all segments of the supply chain. While forward logistics focuses on product specifications and packaging, reverse logistics introduces various challenges.

Distributors, acting as intermediaries between retailers and manufacturers, must efficiently manage the flow of returns to maintain competitiveness. Failure to handle returns effectively can lead to significant profit losses, as exemplified by increased warehouse costs, missing items, incorrect shipments, and unreconciled returns variances.

 

Return Variance Analysis:

Return Variance Analysis is a critical process that involves reconciling differences between Return to Vendor (RTV) and Return to Manufacturer (RMA) documentation. This meticulous procedure requires reviewing RTV details, including quantity and pricing, and comparing them against supporting RMA information.

Due to the time-intensive nature of this task and the need to navigate multiple systems concurrently, errors can arise, leading to potential financial losses. Manufacturers and distributors often struggle with inefficient returns management, especially during peak periods like the holiday season.

Variances may occur due to discrepancies in tracking numbers, pricing data, or the categorization of returned items, causing additional complications. Efficiently addressing these variations is crucial to maintaining financial accuracy and preventing unnecessary challenges in the supply chain.

 

Types of Returns Variance

Different retailers employ specific return processes.The most common types of return processes used include:

• Single RMA (Amazon uses these types of return variances)
• Returns Variance Analysis for a set of RMAs (typically performed quarterly)
• Returns Variance Analysis over a predefined amount of time

Managing datasets of such magnitude poses challenges, leaving many companies unable to fully recover losses incurred through return variance mishaps.

Manufacturers and distributors may find themselves leaving money on the table, with inefficient returns processes resulting in substantial yearly profit losses. As distributors operate on thin profit margins, handling returns of this magnitude becomes even more challenging, particularly during busy seasons when returns processing complexities are exacerbated.