An increasing issue arisen in the customer self-service age – first and foremost as seen in e-commerce – is the increasing reverse supply chain. A reverse supply chain is the flow of products being returned down the supply chain because the end customer did not want or like the product.
There are several reasons for returned products. Bad product quality is an old known reason. Bad data quality is a new important reason. Bad data quality is when the end customer did not have the right data to support the purchase. The main root cause for this is incomplete data as missing specification, missing images and other digital assets as well as missing information about related products.
Some different kinds of product data was examined in the post Self-Service Ready Product Data. Data that supports customer self-service sales approaches are mainly those data that should be provided through the forward supply chain, meaning that they are originated at the manufacturer and then passed and possibly value added by distributors and retailers.
Increasing reverse supply chains is a huge problem both from a business standpoint due to increased costs and from a society standpoint due to increased environmental impact. To decrease the reverse supply chain we need better means to put comprehensive product information through the forward supply chain in a timely matter.
The Product Data Lake is a solution to do so, as the Product Data Lake ensures:
- Completeness of product information by enabling trading partners to exchange product data in a uniform way
- Timeliness of product information by connecting trading partners in a process driven way
Further more, the Product Data Lake ensures:
- Conformity of product information by encompassing various international standards for product information
- Consistency of product information by allowing upstream trading partners and downstream trading partners to interact with in-house structure of product information
- Accuracy of product information by ensuring transparency of product information across the supply chain
Please find more information about the Product Data Lake here.