No matter how much attention companies devote to issues of data quality, it will be difficult for them ever to achieve 100 percent perfection. They can put a significant amount of effort into ensuring the accuracy of their information, including the use of address management solutions to clean up customers' contact data, but mistakes will still persist.
The ideal of 100 percent perfection sounds nice in theory, but in practice, it's impossible. Given that truth, companies are faced with a difficult question - should they be honest about the small imperfections in their data clusters, or should they cover them up?
According to Information Management, it may be beneficial for IT leaders to come clean about the errors in their data. Data quality guru Jim Harris, curator of The OCDQ Blog, likens this honesty to what author Daniel Pink calls the "blemishing effect." The theory is simple - when you're honest about an imperfection, it makes you appear more genuine.
Pink covered this concept as it relates to sales in his 2012 book, "To Sell Is Human: The Surprising Truth About Moving Others," but it relates to data quality, as well. Pitches of all kinds are more believable when they include the truth about imperfections.
"The next time you're making the business case for a data quality initiative, try listing all the positives that high-quality data has brought to your organization - and then add a specific instance where poor-quality data negatively impacted the organization," Harris advised. "Perhaps being honest about the existence of a small blemish will enhance the true beauty of your data quality business case."
Companies put a lot of time and money into purifying their information. With significant effort, they can eliminate many of the mistakes in their databases. With those errors that remain, honesty may be the best policy.
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