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Building a business case for Data Quality is a challenge and so it leads to
passive response from the audience. The smart way is to start your data quality
program with the areas, which have direct business significance. It's not a
question of being manipulative as these areas will be most valid candidates.
Articulation in business language is another important factor. Anything which
you do will have direct or indirect impact on business. The trick is how you
find it, quantify it (as much as you can) and articulate in business language.
For example "Expected to increase your data reliability on customers, and
provide you 5% higher strike rate in your mailing campaigns and also save
10% time of your reporting staff" is better than saying "It will achieve 15%
higher quality in the customer leads table in leads management system". Please
also note that if your data quality initiative will support regulatory compliance,
that will be one of the best arguments. Don't overstate the benefits, and
if you are not sure make them tentative and not committed goals.
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