How to evaluate the quality of supply chain master data and related processes
Master Data, its quality and completeness, and the processes that create, update, and synchronize across different systems have an outsized impact on sales, commerce, supply chain readiness, and operational excellence. At the same time, many organizations struggle to achieve Master Data Management Excellence.
Before you embark on a Master Data Management Excellence initiative, it is a good idea to understand where your organization stands in terms of Master Data Management.
To evaluate Master Data Excellence, it is essential to consider:
- The quality of the Master Data itself
- The processes involved in creating and updating Master Data
Building the business case for master data process improvement
The business case for making Master Data Management efficient and effective primarily rests on the following
- The Savings an organization can realize by making Master Data Management efficient and effective
- The Investment it takes to make Master Data Management efficient and effective
Both of the above can make or break the business case for Master Data Management. Ideally, savings should be higher by a factor than the investment.
Pursuit of perfect master data
The ideal number for Master Data errors is Zero.
There are two ways to achieve zero master data errors. Error-proofing and error correction. Error-proofing is infinitely better than error correction.
End-to-end process for master data management
In most cases and for many master data domains (materials for example), master data management is more than just core master data. Learn more about end-to-end business processes for master data management and why traditional approaches (ERP-centric and Data-centric MDM) fail to support the end-to-end business processes for master data management.