Classifying products and services using a standardized coding system helps companies enhance the effectiveness and efficiency of their purchasing activities without the cost and complexity of maintaining a proprietary coding system. Many purchasing systems support this and other classification systems out of the box, making them relatively simple to start using.
However, using these standardized coding systems does have disadvantages. Standardized systems may not be optimized for specific industries or lines of business. It could be too granular in some areas, and too general in others. Items may be classified in ways that don’t match a business’s specific sourcing, procurement, or supply chain strategies. Additionally, no matter how detailed, categories seldom provide the level of detail that unique item identifiers can.
Companies using Amazon Business can take advantage of a distinctive data field—the Amazon Standard Identification Number (ASIN)—with new possibilities for spend analysis. Every product on Amazon is assigned a unique ASIN—even products that lack a Universal Product Code (UPC) or International Article Number (EAN). ASINs give companies item-level data for every product purchased through Amazon Business.
At a basic level, ASINs can be used for typical spend analysis activities, such as identifying savings and consolidation opportunities, evaluating suppliers, reducing risk, and communicating usage data and reports. An example of a more in-depth use case could be employing ASINs as a kind of “Rosetta Stone” to normalize product data across a supply chain, in much the same way that other standard codes are used except with item-level detail. Leveraging this kind of information can help reduce risk to supply chains because it increases the visibility at lower levels of the supply chain that most organizations lack.
Because ASIN identifiers are universal and unique across products offered on Amazon Business, they provide item-level detail that other categorizations lack. Additionally, ASIN reports can be extracted from Amazon Business easily using Amazon Business Analytics tools for analysis and incorporation into purchasing data normalization projects.