It is widely known that that the retail industry relies on economies of scale benefits, i.e. it is characterized with high volumes and low margins. In such an environment, any bottom line value recovery automatically contributes back to the top line or revenue of the company, giving it a natural edge over other players who do not emphasize on a similar recovery philosophy. One major value recovery opportunity in retail is with Returns/Rejects or Defective/Damaged inventory which constitutes a backflow to the forward supply chain. Owing to the unpredictable and non-linear nature of this reverse flow there isn’t a definitive and single point optimal solution for managing this reverse flow of inventory. Based on select key parameters analysed in great depth over the course of our study, we have designed a hybrid model for managing rejects aimed at maximizing value recovery.

Returns can flow into the Warehouse Management System (WMS) as Shipments, Consignments, and Identified or Unidentified inventory items. The first step in processing them is to account for them by confirming the receipt of the shipment or consignment in the WMS. For identifiable inventory items, inventory quantity needs to be created in the stock file with a tagging of the specific reason of creating the stock. Similarly for inventory which can’t be identified, based on the legal implications prevalent in the region of operation, a line item or tag can be created in the WMS, with specifications of the inventory specified by authorized personnel and approved by the appropriate approval authority within the organization. These are the primary steps in returns inventory processing and management.

The crucial parameters that should be considered while selecting a strategy for managing these returns are: type of retail – e-retail, mom and pop, superstore, brand store etc., range of categories sold and returned, point and time of return, trade terms with suppliers, type of procurement, operational capabilities, size of inventory, sales and return type and quantum of returns.

Based on these either a specific alternative or a hybrid model can be derived for optimized returns management designed around methodologies like: inventory serialization and serialized order pick, inventory bucketing and product ID level order pick, bulk/non-tagged inventory with bulk outward.

For either of these strategies the WMS needs a specialized orchestrator using a rule engine that uses multiple parameters and flag based configurations for flexibility to handle variability. The usage of multiple parameters largely depends on the fact that the existing systems are built with these parameters being captured at product on-boarding and inventory creation or these are recorded while accounting of returns which has been mentioned above as the first step of the returns process flow.

This paper aims to provide a comprehensive view of the design of the new process and an overall understanding of the orchestrator capabilities required for each of the aforementioned alternatives.