When managing the success of data governance programs, which measure should NOT be used?

In the context of data governance programs, the success of various initiatives is typically evaluated using specific, measurable goals related to data management activities. The measure of data quality improvement, the number of data issues closed/open, and data standards compliance are all direct indicators of how well a data governance program is functioning.

Data quality improvement reflects how effectively the governance program enhances the accuracy, reliability, and overall quality of the data. Tracking the number of data issues closed and open provides insight into the efficiency in addressing and resolving data-related problems, which is crucial for effective governance. Compliance with data standards ensures that the organization's data management practices align with established guidelines, essential for maintaining data integrity and interoperability.

On the other hand, while the number of business processes improved can provide some context about the overall business efficiency, it is not a direct measure of the data governance program itself. Improvements in business processes might occur due to various factors unrelated to data governance, such as operational changes or shifts in strategy. Thus, this measure may not provide a clear representation of the effectiveness or success of the data governance program specifically.