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Increased scrutiny and many new projects have been

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Unformatted text preview: ew projects have been put on hold or cancelled. A downturn forces businesses to focus inwards to reduce costs and improve efficiencies to prop up revenues and profit margins. New IT investments are also invariably affected, and CIOs are left scratching their heads about how to fund and sustain important information management projects such as data quality improvement. Ovum would advise against cutting into these projects too deeply because having a rigorous data quality program in place that ensures the availability of accurate and up-to-date information is now a business imperative rather than a luxury. Implemented correctly, it can help organizations ride out a recession and raise competitiveness when the economy recovers. But it is not an easy task. Here we highlight some of the key issues. Bad data means bad business The requirement to improve data quality is not a new problem, but if recognized and treated properly it can be part of the solution. Organizations should realize that poor data quality is a pervasive issue that puts a drag on performance, revenues, and profits. The problem is huge. It’s estimated that up to 30% of the data held by businesses is incomplete and inaccurate. This affects bottomline corporate profitability, including customer service, management decision-making, and operational productivity, yet few corporations have mastered how to systematically manage data quality improvements. S TRAIGHTTALK I T 5 It is estimated that 40% of IT costs result from problems related to data quality, which adds up to hundreds of millions of dollars every year in wasted detect-and-correct efforts and system downtime as a result of reloading or updating fresh data. However, the consequential cost of poor data quality related to IT is just the tip of the iceberg. The quality of data reflects the overall level of professionalism of a business. Bad data is a sign of bad organizational and process discipline and management in terms of missed sales opportunities, erosion of customer confidence, missed cross-sell or up-sell opportunities, excessive and unnecessary operational overheads, and liabilities arising from incomplete records. The devil is in the detail Glo...
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