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There has to be accountability for good-quality data at all levels in the organization--from the data-entry clerks all the way to the CEO.
The sports news has been filled with stories about the errors in gymnastics scoring, another company had to restate its earnings because of an accounting error, a catalog company sent me the wrong order, and I got another piece of mail from my bank offering me one of its credit cards (I already have one, thank you). These are just a few of the data-quality problems I've come across over the past couple of weeks. Larry English, president of Information Impact International, could tell you about thousands of examples--some minor (name misspellings) and some tragic (medical data errors)--that he's found while studying and consulting on the topic. I had a chance to chat with Larry and other data-quality experts at an event last week.
It's a problem that can cost companies 10% to 20% of operating revenue to do what Larry calls "information scrap and rework." Yet so many companies continue to operate with and share bad data. It's the cause of project failure for CRM, business-intelligence, and decision-support systems. Granted, new regulatory demands have brought the issue into the spotlight, but it still needs to rank high on the priority list for many companies. Not only are hard dollars at stake, but also customer loyalty, reputation, or, in the case of health-care providers, people's lives. It threatens collaboration, knowledge sharing, productivity, and real-time decision making.
Some advice from the experts: There has to be accountability for good-quality data at all levels in the organization--from the data-entry clerks all the way to the CEO. Fixing (and eliminating) the problem has to involve a strong methodology and new business processes, not just technology. Line-of-business managers must assume responsibility, not just dump it in the IT department's lap.