The project triangle expresses the dilemma about that you probably want your project to be good, fast and cheap, but in practice you are only able to prioritize two of these three desirable options, in short:
The pick any two among three theme can be related to a lot of other activities thus stating three terms with only two combinations possible in real life.
So what could be the pick any two among three themes for data quality?
Of course the good, fast, cheap dilemma also goes for data quality projects. But as data quality management isn’t just a project but an ongoing program, what else?
I have one suggestion:
Fit for purpose, real world alignment, fix it as we go – pick any two
The term “fit for purpose” has become more or less synonymous with “high quality data” and thus here chosen to express the good angle of data quality.
Some data, especially those we call master data, is used for multiple purposes within an organization. Therefore some kind of real world alignment is often used as a fast track to improving data quality where you don’t spend time analyzing how data may fit multiple purposes at the same time in your organization. Real world alignment also may fulfill future requirements regardless of the current purposes of use.
Managing data both being fit for multiple purpose and aligned with the real world is not something you just do in a cheap way by fixing it as we go. You may pick any two options in these combinations:
- Make some data fit for purpose by fixing it as the pains shows up.
- Align data with the real world typically by exploiting external reference data as the prices go down.
- Lay out a thorough plan for having fit for multiple-purpose data aligned with the real world.