Foundational Concept for Performance Management and Data Quality

I was going through my reading, and ran across this article on the B-Eye-Network that talks about the foundational concepts that need to ground a Data Quality program. Part of this article discussed the Deming Cycle (PDSA Cycle). The PDSA acronym stands for the following:

• Plan - Plan for the future desired state
• Do - Execute actions to get to future state
• Study - Check the results against desired state
• Act - Act to correct towards desired state

This is a foundational concept that we can apply to both Data Quality programs and the use of Key Performance Indicators in a performance management system. In the data quality program we would apply the PDSA model as follows:

• Plan - Define data quality issues in a given data source
• Do - Put in place monitoring tools to analyze data quality
• Study - Analyze the results to understand issues and identify root causes
• Act - Act on root causes (typically process issues) and fine tune monitoring tools

Similarily, when we define and use Key Performance Indicators we might approach it this way:

• Plan - Define a set of KPIs that are thought to be critical to business success
• Do - Collect data on actual performance against the KPIs
• Study - Analyze the results to validate KPI effectiveness and to search for other supporting factors of success
• Act - Fine tune KPIs from learnings to improve overall performance management

If we look at this type of process as a framework, we can use it to build more effective processes that are rooted in an iterative approach to improving quality and value. With this type of execution you can climb any hill by taking small, measured steps. A word of caution however, you may suddenly realize you are climbing the wrong hill...8)

Good night,

Mark