Is the Data Quality Glass Half Empty …or Full?
Jim Harris, a well-known industry thought leader on all-things data quality, brought up a great point in his recent blog entry, “Why Isn’t Our Data Quality Worse?” His point – instead of asking ourselves, why isn’t our data quality better, we should also ponder, why isn’t our data quality worse?
It’s an interesting point and a different take on determining issues with your contact data. We like how he’s coming at it from a different direction.
Harris states that we have a tendency to focus more on problem-seeking when analyzing our data quality efforts. “Most data quality initiatives focus on creating new best practices, and not leveraging existing best practices,” Harris states.
Well put. Why not instead try a solution-oriented approach to data quality initiatives that asks the question, “what’s working and how can we do more of it?”
Here’s what Harris notes in his blog:
The common approach is to ask the following questions
(using a problem-seeking mindset):
* Why isn’t our data quality better?
* What is the root cause of the 20 percent inaccurate data?
* What process (business, technical, or both) is broken, and how do we fix it?
* What people are responsible, and how do we correct their bad behavior?
But why don’t we ask the following questions
(using a solution-seeking mindset):
* Why isn’t our data quality worse?
* What is the root cause of the 80 percent accurate data?
* What process (business or technical, or both) is working, and how do
we re-use it?
* What people are responsible, and how do we encourage their good behavior?
To read Harris’ entry, click here