Unlocking the Digital Potential of Reverse Logistics

Organizations are increasingly taking the digital route to cope with evolving customer expectations, the pace of innovation, and fierce competition. And one industry – Reverse Logistics – which has been slow to hop on to the digital transformation bandwagon – is now looking to make the most of various cutting-edge digital technologies available in the market.

Digital technologies hold immense potential to transform reverse logistics. But what explains the slow adoption of digital technologies by the reverse logistics industry? Well, reverse logistics is generally an offline process – it is all about receiving returned goods, assessing, and processing them, subsequently either dispose or prepare them for resale.

Organizations are on the lookout for leveraging different software, platforms, and tools to transform their reverse logistics process. The larger objective of transforming reverse logistics is to ensure the entire reverse logistics process is a cost-effective one without having to compromise on customer experience. Organizations can do a world of good to themselves by getting into the reverse logistics life cycle and effectively address the 4 Cs - Cost Avoidance, Cost Reduction, and Cost Elimination, and Improved Customer Experience.

Different stakeholders are focused on their own set of objectives across the Reverse Logistics process. For example, from the customer’s perspective, predictability and visibility of the Reverse Logistics process are essential. Again for a field technician, coordination of product tracking and customer experience is vital, while service-level agreement (SLA) adherence holds the key for an operation manager. But there’s no denying the fact that the common objective across all various departments and touch points isto transform reverse logistics by delivering a superior customer experience as well as life cycle visibility and predictability.

Various new-age technologies such as Data Engineering, Advanced Analytics & Artificial Intelligence as well as IoT & RFID promise to transform the reverse logistics industry.

Data Engineering can drive efficiency gains in reverse logistics by unifying fragmented data sets from different stakeholders into a common data store that can be used for analysis. Similarly, Advanced Analytics and Artificial Intelligence have huge potential to transform reverse logistics by discovering insights and patterns to improve predictability. IoT and RFID can also help transform reverse logistics by enabling track & trace for better visibility and faster responsiveness.

To sum it up, globally there is a great deal of focus among organizations to drive efficiencies in their reverse logistics processes and this is where Data Engineering, Advanced Analytics, and Artificial Intelligence and IoT and RFID can aid in transforming reverse logistics.