The impact of poor data quality on the typical enterprise

Влияние низкого качества данных на типичное предприятие
Thomas C. Redman
1998-02-01

customer dissatisfactiondata quality programsdecision-makingoperational costpoor data quality
Poor data quality has far-reaching effects and consequences. The article aims to increase the awareness by providing a summary of impacts of poor data quality on a typical enterprise. These impacts include customer dissatisfaction, increased operational cost, less effective decision-making and a reduced ability to make and execute strategy. More subtly perhaps, poor data quality hurts employee morale, breeds organizational mistrust, and makes it more difficult to align the enterprise. Creating awareness of a problem and its impact is a critical first step towards resolution of the problem. The needed awareness of the poor data quality, while growing, has not yet been achieved in many enterprises. After all, the typical executive is already besieged by too many problems, low customer satisfaction, high costs, a data warehouse project that is late, and so forth. Creating awareness of issues of the accuracy level and impacts within the enterprise is the first obstacle that practitioners must overcome when implementing data quality programs.
1
It contributes to customer dissatisfaction, higher operational costs, less effective decision-making, and reduced ability to formulate and execute strategy.
2
Many enterprises still lack sufficient awareness because executives are already overwhelmed by competing operational and strategic problems.
3
Poor data quality also undermines employee morale, fosters organizational mistrust, and makes enterprise-wide alignment more difficult.
4
Poor data quality produces far-reaching consequences across typical enterprises, extending beyond isolated data-management problems.
5
Raising awareness of data-quality accuracy levels and organizational impacts is identified as the critical first step toward resolving the problem.

poor data quality in a typical enterprise

the organizational and operational impacts of poor data quality, including customer dissatisfaction, increased costs, ineffective decision-making, reduced strategic execution, lower employee morale, organizational mistrust, and difficulty aligning the enterprise

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1998-02-01
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Thomas C. Redman
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