When we are looking for what is really important and absolutely necessary to get data quality right some sayings could be:
- “Change management is a critical factor in ensuring long-term data quality success”.
- “Focussing only on technology is doomed to fail”.
- “You have to get buy-in from executive sponsors”.
These statements are in my eyes very true and I guess anyone else will agree.
But I also notice that they are true for many other disciplines like MDM, BI, CRM, ERP, SOA, ITIL… you name it.
Also take the new SOA manifesto. I have tried to swap SOA (and the full words) with XYZ, and this is the result:
XYZ Manifesto
XY is a paradigm that frames what you do. XYZ is a type of Z that results from applying XY. We have been applying XY to help organizations consistently deliver sustainable business value, with increased agility and cost effectiveness, in line with changing business needs. Through our work we have come to prioritize:
Business value over technical strategy
Strategic goals over project-specific benefits
Intrinsic interoperability over custom integration
Shared services over specific-purpose implementations
Flexibility over optimization
Evolutionary refinement over pursuit of initial perfection
That is, while we value the items on the right, we value the items on the left more.
I think a Data Quality and several other manifestos could be very close.
But what I am looking for in Data Quality is the specific pearls of wisdom related to Data and Information Quality – while I of course value to be reminded about the universal ones.
Liliendahl on Data Quality 
Off topic, but this reminds me of a comic strip about Buzzword Bingo.
I’ve never been a fan of the buzz, but sometimes you have to use the same language to have a competitive message, & the same old patter gets trotted out by every one with a barrow to push until it becomes meaningless pap. These are truisms for all new technologies, too.
It’s often harder to formulate a data quality pitch based on what the customer actually wants – that would mean finding that out first. That’s hard work, & most sales people think they already know.
Data quality is a business problem, not a technology sell. It requires an application of expert knowledge & experience to achieve realistic results for the client.
If you can convince them that you really understand their problem (not problems like theirs), & have the nous & tools to solve them, then you don’t have to fall back on generalisations of the benefits.
Jax, an extremely belated thanks for your wise comment.