Thomas C. Redman
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Index Terms
- The impact of poor data quality on the typical enterprise
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Reviews
John R. Ray
Redman's main goal is to draw attention to poor data quality and the myriad problems it causes, including its effects on customer satisfaction (or dissatisfaction), operational costs, the effectiveness of decision making, and the ability to make and execute strategy. Equally important is that poor data quality lowers employees' job satisfaction, thus creating a full cycle of problems. Poor data quality compromises decision making, makes it more difficult to reengineer a project or activity, and increases the mistrust that internal organizations may have for one another. While less direct, the impact of poor data quality on strategy setting often leads to inaccuracies, missed deadlines, or generally poor execution of work plans. Finally, customers who do not trust an organization because of data errors will not continue to work with that organization. Redman concludes with the idea that creating awareness of these issues is the first step in solving the problem. While the tangible impacts of poor data—customer dissatisfaction, increased costs, ineffective decision making, and negative effects on strategy—are bad enough, the resulting lowered morale, organizational mistrust, and issues of ownership may be worse.
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