Many major companies routinely make important decisions based on remarkably inaccurate data, says Gartner.
The research firm estimates that more than 25% of critical data within Fortune 1 000 businesses will continue to be inaccurate or incomplete through 2007.
"Most enterprises don`t fathom the magnitude of the impact that data quality problems can have," says Ted Friedman, Gartner principal analyst. "These problems cause wasted labour and lost productivity that directly affect profitability."
Moreover, the majority of large enterprises continue to reach for ineffective technology solutions even after they identify data quality problems, he says. These ineffective solutions often include priority spending programmes for advanced business intelligence and customer relationship management (CRM) capabilities. These programmes fail, in large part, because the poor quality of underlying data is not recognised or addressed.
According to Gartner, many enterprises simply look to technology they can buy to resolve data quality problems without first focusing on people and business processes.
"Throwing technology at data quality issues usually doesn`t solve the problem and won`t yield positive long-term results," Friedman says.
He adds that enterprises should also examine organisational approaches and methodologies to improve data quality. They must engage the active participation of people who use the technology to achieve business objectives, not only technology staff.
"If the IT group is the only organisation that actively works and focuses on the issue, the business`s ability to achieve data quality goals will be severely limited. The greatest success in managing data quality comes from engaging both business users and the IT organisation," he says.
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