Gartner, the analyst firm, has a hype cycle for Information Governance and Master Data Management.
Back in 2012 there was a hype cycle for just Master Data Management. It looked like this:
I have made a red circle around the two rightmost terms: “Data Quality Tools” and “Information Exchange and Global Data Synchronization”.
Now, 6 years later, the terms included in the cycle are the below:
The two terms “Data Quality Tools” and “Information Exchange and Global Data Synchronization” are not mentioned here. I do not think it is because the they ever fulfilled their purpose. I think they are being supplemented by something new. One of these terms that have emerged since 2012 is, in red circle, Multienterprise MDM.
As touched in the post Product Data Quality we have seen data quality tools in action for years when it comes to customer (or party) master data, but not that much when it comes to product master data.
Global Data Synchronization has been around the GS1 concept of GDSN (Global Data Synchronization Network) and exchange of product data between trading partners. However, after 40 years in play this concept only covers a fraction of the products traded worldwide and only for very basic product master data. Product data syndication between trading partners for a lot of product information and related digital assets must still be handled otherwise today.
In my eyes Multienterprise MDM comes to the rescue. This concept was examined in the post Ecosystem Wide MDM. You can gain business benefits from extending enterprise wide product master data management to be multienterprise wide. This includes:
- Working with the same product classifications or being able to continuously map between different classifications used by trading partners
- Utilizing the same attribute definitions (metadata around products) or being able to continuously map between different attribute taxonomies in use by trading partners
- Sharing data on product relationships (available accessories, relevant spare parts, updated succession for products, cross-sell information and up-sell opportunities)
- Having shared access to latest versions of digital assets (text, audio, video) associated with products.
This is what we work for at Product Data Lake – including Machine Learning Enabled Data Quality, Data Classification, Cloud MDM Hub Service and Multienterprise Metadata Management.