New York, NY (Jul. 5, 2013) – Inadequate data governance can cost millions. From regulatory fines for systems and control failures, to the labor expenses incurred from the extra effort required to produce accurate information for critical business decisions, to the legal fees spent cleaning up a publicity nightmare from a data-driven error. Moreover, when it comes to patient or consumer safety, poor data quality can also cost lives.
In addition, most organizations tend to handle data quality in a very tactical fashion. Either the IT organization rectifies any issues, or the individual business units must create business processes to fix it. When IT is in charge, the problem goes into the queue and, more often than not, gets relagated to a low priority. So business units, who face the problem on a day-to-day basis, must step in to deal with it.
Key findings from a Gartner study revealed:
- Poor data quality is a primary reason for 40 percent of all business initiatives failing to achieve their targeted benefits
- Data quality effects overall labor productivity by as much as a 20 percent
A survey performed by The Data Warehouse Institute demonstrates similar results, with respondents claiming that poor data quality has led to lost revenue (54 percent), extra costs (72 percent), and decreases in customer satisfaction (67 percent).
So why aren’t data quality problems being handled at an organizational level?
Typically, the numbers cannot be adequately digested when business processes and workarounds to these issues are constantly being developed. Oftentimes, changing the status quo means changing the organizational culture, and being able to treat data quality as an ongoing strategic program, not a series of one-off projects. Cultural change is difficult to foster, and if there are perceived business processes to deal with the problem anyway, it just seems easier to leave things be.
Read the full whitepaper: The Real Cost of Bad Data: Six Simple Steps To Address Data Quality Issues (PDF)
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SOURCE: Information Builders
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