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Study: UK companies crippled by poor data quality

As a result of poor data quality, companies in the U.K. are wasting their budgets and investing in unnecessary areas of the business. According to a study by Experian QAS, roughly 90 percent of organizations admitted their budgets are being thrown away due to inaccurate information, with departments exhausting 15 percent of their investments on average.

"There is a growing body of evidence showing that accurate data is the key to competitive advantage,” Experian QAS managing director Joel Curry said. “Companies that are able to rely on their data can use it to better understand their customers and target campaigns."

The study also revealed that 92 percent of companies dependent on databases said the data in their possession is flawed, with the majority believing that up to one-quarter of all records are inaccurate, the study noted. This suggests that organizations need to implement data quality tools that assure the accuracy of information acquired through consumers and mission-critical analytics.

According to the study, businesses are beginning to take a stance against poor data quality and investing in solutions that guarantee accurate records. Large corporations are spending the most on these services, sinking nearly $800,000 into data quality tools during the past two years. Small and medium-sized businesses are not far behind, however, as decision-makers authorized more than $200,000 and $390,000, respectively, to be spent on data quality assurance tools.

Experian QAS also found that human error is the No. 1 cause behind poor data quality, which then leads to bigger mistakes down the line. According to the study, 57 percent of all inaccurate information is derived from mistakes by employees. However, decision-makers are taking the wrong approach to fix these blunders, as the majority of companies use the same individuals who made the mistake to counteract the problem.

A report by the Data Warehousing Institute for Business stated that organizations need to take a modern approach to correcting data quality programs. The first step to improve information accuracy is understanding the subject that the records are about.

For example, if a database is implemented in the human resources department, information will include employee status, hours, earnings and other facts. The subject in this case is the employee. Once this is understood, individuals can categorize and analyze details based on each subject, allowing the process to be slowed down and contain fewer inaccuracies, TDWI noted.

Accurate data is the key to attaining success. By utilizing quality measuring tools and understanding the content more thoroughly, organizations can acquire true information and gain a competitive advantage.

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