Some businesses are so busy imagining the potential of big data that they aren't thinking about the potential consequences that can come with it, if the information is corrupt with bad data quality.
For instance, a business that invests in a customer service optimization plan might make changes that are expected to speed up website performance to improve satisfaction and conversion, according to a post for the Sys-Con big data blog. However, if the information used in plan development was incorrect, the outcome of the efforts might actually make web experiences worse. Ultimately, client experiences may worsen and the money spent proves to be a waste.
To avoid that type of situation, companies need to make data quality a priority, according to IT Web. This often requires the support of senior of executives, who might be convinced with a six-step proposal that begins with a clearly articulated problem, a vision for the solution, an example of how it will be delivered and plans for preparation. Next, decision-makers will need to see that the outcome is being influenced and that results can be sustained.
If data users uphold these practices, they can develop a data quality advocacy team that ensures all contact information is run through an address management program and that data sets are checked for errors or inaccuracies.