Beware the Cost of 'Dirty Data'

With technology making data readily available anytime, anywhere, from any device, many of us have come to rely upon the Internet for numerous aspects of our professional lives. Before heading into important meetings with a new sales prospect or a potential hire, we want to know relevant information about the person we're meeting, the company they work for, and the industry they work in. To assemble an accurate "profile" of sorts, we spend time scanning internal corporate databases for a basic overview, more time searching the Web for supplemental data, and even more time on social networks such as LinkedIn or Twitter gathering additional context on their professional history and interests. Sound familiar?

This common scenario has all but eliminated the dependence on those massive and pricey reference books sales professionals once used to gather information about executives and their respective companies and industries—akin to how online reference sites such as Wikipedia have nearly eliminated the need for printed versions of encyclopedias. But the devil is in the details with data. While it is certainly fantastic to have so much free information readily available today via the Internet, it is often labor-intensive to find and extremely inaccurate.

For example, one major analyst firm last year found that poor-quality data is costing organizations surveyed an average of $14.2 million annually. I saw a similar and widely publicized study a few years ago estimating that dirty data (aka incorrect, fraudulent, or obsolete information) costs the U.S. economy more than $3.1 trillion annually. On average, every 30 minutes, 120 business addresses and 75 phone numbers change, 20 CEOs leave their jobs, and 30 new businesses are formed, according to Sales & Marketing Institute and Dun & Bradstreet data. Using dirty or incomplete data can hinder a developing customer relationship and derail a crucial sales initiative, and, as a result, wreak havoc on your bottom line.

As business professionals, we require the best data possible to do our jobs more efficiently and effectively—and the best data is always clean data. Such data not only enables your organization to connect and drive meaningful relationships with customers, but it can also arm your sales force with select, insightful, and customer-centric information that can mean the difference between a closed deal and a lost account.

Great data is king, ideally derived from both internal and cloud-based sources because (let's face it) some of the best information resides outside of your company's four walls. However, since we all know the accuracy and timeliness of cloud-based information can vary, and it's 

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