In a bid to position themselves as leaders in the Master Data Management space, several vendors position their MDM platform as a complete solution.
The truth is that these claims are somewhat misleading. Some claim that Data Governance (a critical component of an MDM program) is built-in functionality. However, they don’t provide a Data Quality capability in their product. Today, I want you to think about the fact that Data Quality is an integral part of Data Governance and a successful MDM program.
Here’s the methodology we recommend:
1. Analyze the business problems that MDM will address
2. Define critical metrics for data and other business issues
3. Link the metrics to business problems
4. Measure results and quantify improvements
5. Communicate results and improvements across the enterprise
6. Secure budget for next year
In order to execute this methodology, it’s imperative that Data Quality measures and related workflows be part of the MDM platform your vendor provides. If not, consider a third party DQ tool to integrate with your MDM platform.
If you’d like to ask about some of the typical Data Quality metrics we’ve used in previous implementations, please contact us.