“The average financial impact of poor data quality on organizations is $9.7 million per year.” This is a quote from Gartner, the analyst firm, used by them to promote their services in building a business case for data quality.
While this quote rightfully emphasizes on that a lot of money is at stake, the quote itself holds a full load of data and information quality issues.
On the pedantic side, the use of the $ sign in international communication is problematic. The $ sign represents a lot of different currencies as CAD, AUD, HKD and of course also USD.
Then it is unclear on what basis this average is measured. Is it among the +200 million organizations in the Dun & Bradstreet Worldbase? Is it among organizations on a certain fortune list? In what year?
Even if you knew that this is an average in a given year for the likes of your organization, such an average would not help you justify allocation of resources for a data quality improvement quest in your organization.
I know the methodology provided by Gartner actually is designed to help you with specific return on investment for your organization. I also know from being involved in several business cases for data quality (as well as Master Data Management and data governance) that accurately stating how any one element of your data may affect your business is fiendishly difficult.
I am afraid that there is no magic around as told in the post Miracle Food for Thought.
Liliendahl on Data Quality 