The future of Part Numbers and Unique Identification?

Identification. When it comes to data management it is a very important thing. In product data management and PLM it usually comes to the Part Numbers. Companies can spend days and months debating what to include in Part Numbers and how to do that. Smart Part Numbers vs. Dumb Part Numbers. OEM Part numbers, Manufacturing Part Numbers, Suppliers Part Numbers – this is only one slice of identification aspects in manufacturing and engineering. I want to reference few of my previous posts PDM, Part Numbers and the Future of Identification and Part numbers and External Classification Schemas – to give you some background of what potential problems or dilemmas you may have towards decision about numbering schemas and identifications.

These days product information is going beyond borders of your company and even beyond your stable supply chain. The diversity of manufacturers, suppliers, individual makers combined with increased amount of e-commerce is creating the need to use product identification more broadly and maybe in more synchronized and standard way.

My attention was caught by SearchEngineLand article – How Online Retailers Can Leverage Unique Identifiers & Structured Data. Read and draw your conclusion. Article speaks about usage of product unique identification in e-commerce – GTIN.

In e-commerce, there is a unique global identifier that is leveraged across all major comparison shopping engines and search engines: namely, a GTIN or Global Trade Item Number (better known in the U.S. as a UPC). These global unique product identifiers take the guessing game out of comparing two products to determine if they are the same item, eliminating the problems typically associated with entity resolution and big data — all you have to do is compare the GTINs.

The most interesting fact is the variety of GTINs are now part of schema.org product definition. Schema.org is the initiative supported by Google, Yahoo, Bing and Yandex about representation of structured information on web pages. Google can aggregate product based on the comparison of identical GTINs. You can see an interesting patent filled by Google – Aggregating product review information for electronic product catalogs. Here is an interesting description:

An analysis module collects product reviews and determines whether each product review includes a product identifier, such as a Global Trade Item Number (“GTIN”). For product reviews having a product identifier, the module adds the product review to the product catalog and associates the product review with the product identifier. For product reviews lacking a product identifier, the module initiates an Internet search using information from the product review and analyzes search results to identify a product identifier for the product review.

You can ask how it applies to PLM and Part Numbers. In my view the initiative to have a standard of structured data representation presents the technique that can be used by manufacturing companies and software vendors. Web shows how to do it in an open way and increase the value of data access and analyzes. Finding similar parts inside your company product catalogs and across supply chain with future optimization can be an interesting solutions. Manufacturing companies are trying to solve this problem many years. It can also lead to significant cost benefits.

What is my conclusion? Adoption of web technologies and practice becomes an interesting trend these days. In my view, enterprise software (and PLM is part of it) is struggling from protectiveness in everything that related to data. Keep data close, hold format and data management practice – this is a very short list of examples you can see in real life. It was well-known business practice for many years. However, the opportunity from openness can be bigger. Schema.org is a perfect examples of how an agreement between competing web giants can solve many problems in user experience and benefit e-commerce. Just my thoughts…

Best, Oleg