Five data quality archetypes: which one are you?

Phil Simon, a frequent keynote speaker and award-winning author of several management books, has shared some interesting thoughts with us on business management issues pertaining to analytics and data quality. These include his definition of five archetypes for employees when dealing with data quality.

1. The Ignorant

The Ignorant don't know about data quality. Period. They go about their jobs without any regard to the data consequences of their actions. The Ignorant can be entry-level HR as well as high-level strategy people. They either never figured out the importance of DQ or no one ever explained it to them. Ideally, a serious conversation will convert these folks and make everyone's lives easier.

2. The Aloof

The Aloof do know about about data quality, but they just don't care. They often believe that it's the responsibility of IT to cleanse bad data. What's more, they typically become frustrated when application rules prevent them from keying in data willy-nilly. They are fond of blaming "the system" for not letting them indiscriminately enter data.

3. The Skeptical

The Skeptical do not doubt the need for high data quality in theory. But they do doubt what is being done with them in practice. Perhaps their dubious nature emanates from bad experiences in the past. They may seem to have a point but the longer you postpone the focus on data quality, the harder it gets to reach this quality when the organizations starts to focus on it eventually.

4. The Paranoid

At the other end of the spectrum are the Paranoid. These people won't do anything because of potential data quality ramifications, even if the risks far exceed their rewards.
Often these blocking manoeuvres are inspired by other motives. You can read a nice example of this in the detailed descriptions referred to below.

5. The Justly Concerned

Finally, there are those who appreciate the data quality consequences of their actions. At the same time, though, they bring a modicum of perspective to data quality-related issues. Sure, they want to preserve the integrity of enterprise data. That's a given. At the same time, though, they understand that perfect is the enemy of good. They're in touch with their inner Voltaire.

Read more about these different archetypes and the consequences of their attitude for the entire organization in the two-part blog series here and here.