Master Data Management and the Mid-Market Process

In addition to speaking with Bob Bloom about the Mid-Market need as stated in the last post, I also spoke with Bob about the process to implement a Master Data Management Solution.  Basically, the MDM Summit in New York confirmed that the process to implement a Master Data Management initiative is generally the same regardless of whether the organization is a Mid-Market company or a larger enterprise.

The steps for implementing a Mid-Market Master Data Management solution are:

1. Discovery – Understand the project objectives, data, systems, timeframes, personnel, and other items related to a successful Master Data Management project
2. Design – Spec out the system and process for the Master Data Management system
3. Prototype – Develop a working Master Data Management model for testing and adjustments
4. Implementation – Install the adjusted Master Data Management prototype in the live environment. 
5. Maintenance – Support the live Master Data Management system from both a technical perspective and a user perspective
6. Repeat – Expand the functionality of the original Master Data Management solution by using a phased approached to take the MDM application to the next level

The main differences in process between a Mid-Market Master Data Management system and larger enterprise solutions are scale, scope, and timeframes.

Large enterprise Master Data Management solutions may be dealing with many more data records and many more data sources than a Mid-Market MDM solution.  Consequently, the Discovery for a large enterprise MDM Project may be longer than the entire process, Discovery through Implementation, for a Mid-Market MDM system.

Further, a large enterprise may want to include many different types of data, such as customer, employee, product, facility, vendor, and other data types in their Master Data Management project.  Mid-Market firms may be more focused on a specific data type for their Master Data Management solution.  For example, a Mid-Market company may have thousands of customers, prospects, and contacts and organizations related to these customers and prospects.  Therefore, a Mid-Market firm may be focused on a Customer Data Integration application to manage their customer and prospect data.  Customer Data Integration, also known as CDI, is a sub-set of Master Data Management since it is only managing one type of data.  However, larger enterprises many have thousands of employees, products, and other data sets in addition to customers and prospects that need to be managed as part of a MDM solution while a Mid-Market firm may not have enough employees, vendors, or other types of data that need to be included in a Master Data Management system.