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Most credit unions are eager to put their data to work – and when done right, it certainly can work magic. But first, a credit union must work for the data.
"Working for the data" means more than pulling it into an analytics platform. In order to work its magic, action must be taken to improve data quality – and there's a very real, bottom line reason why. Research and consulting firm Gartner says that every year, poor data quality costs an average company $12.9 million. In addition to the immediate impacts on revenue, the compounding effects of poor data quality ultimately lead to poor data analytics – and then, poor decision-making based on those analytics.
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