How often do you really think about the reverse supply chain? It’s easy to assume the reverse supply is solely based on returns. While this is partially true, all reverse logistics involve a backward flow of products that return to their origin, it’s not that simple. Returns may derive from buyer’s remorse, damage to items, defects, end-of-life disposal, and even recycling. Unfortunately, most supply chain leaders continue to incorrectly assume reverse logistics is an archaic process that’s best ignored and left to individual brick-and-mortar facilities for management. Instead of being regaled to this desolate outlook, executives need to rethink their strategy and consider how a data-driven reverse supply chain could add more value and improve profit margins.
There is a major misconception about how much data can be successfully collected within the reverse supply chain. The surprising truth is that the moment a return is initiated, the reverse supply chain should also consider the full scope of data regarding that item or its specific SKU designation that may have contributed to the need to return, repair, replace, or otherwise recycle an item. This is where the value of data-driven reverse supply chain analytics and management comes into play.
Data-driven reverse logistics allow for informed decision making to consider the unique issues affecting each return. Since this may include recalled and defective products, it is imperative for supply chain leaders to thoroughly review each return to determine if the return was justified and what the best resolution is going to be. This is a sentiment that even the biggest names in the industry have discussed at length. According to Deloitte:
“Returns are becoming one of the greatest supply chain challenges companies face today. A reverse logistics supply chain management strategy is critical to maintaining healthy inventory turn and operating expenses. Understanding the dynamics behind how, when, and why customers return items is critical to understanding purchasing behavior and improving overall experience. Every product return is a chance to learn more about the customer, drive the next sale, and make it stick. Online returns are often the result of digital challenges, such as poorly displayed images and incorrect fit. Variances in manufacturer sizing contribute to over 50% of customers returning items due to product size or fit.”
As a result, utilizing data to better understand reverse logistics and applying advanced analytics allows supply chain leaders to realize these key benefits:
Of course, that’s only half the battle in reaping the rewards of data-driven reverse supply chain processes.
To reap the rewards of analytics- and data-driven reverse supply chain, logistics leaders should follow these steps:
Keeping those steps in mind, supply chain leaders could reallocate network resources to leverage empty miles to move returned items without incurring an added cost for drivers and additional runtime for the truck. As a result, the company can better stay within applicable HOS regulations and mitigate rising reverse logistics costs at the same time. The same steps taken earlier on, such as sharing information and data, can be further used to inform manufacturers of potential defects, allowing for intervention, and effectively mitigating the risk of future returns for similar issues.
There will always be a reason for returns, and implementing a no-returns, no-repairs, no-replacements policy will inevitably backfire. Therefore, companies need to start thinking about how a data-driven reverse supply chain strategy can isolate the issues, mitigate future returns, and promote better customer experiences.
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