By Elliot King
While assessment is obviously the first step, it should be just as obvious that
it can’t be the last. Data assessment indicates that problems exist in the data.
The goal should be to consolidate the data generated through the data assessment
process into issues that can be addressed. The data assessment process may show
that 30 percent of purchase orders lack a customer ID and 15 percent have
incorrect contact information. The quality issue is that your purchase order
records are flawed.
Moving from issues to action requires a series of systematic steps and the first
one is not to fix the flawed data. Simply fixing data errors is like bailing
water on a leaky ship. No matter how fast you fix errors, more will be coming
Once data issues are identified, the first step is to determine their impact on
the bottom line. It could be that the errors do little or no harm to corporate
processes and need not be rectified. Unfortunately, that generally is not the
case, but determining the impact of data quality problems is essential for
guiding investment and priorities in fixing them.
The next step is to understand why these errors are occurring. Do front-end data
entry screens have to be altered? Does the data incorporated from third-party
databases fail to conform to your company standards? Do certain divisions of
your organization ignore specific business rules? Are certain data
transformations being executed inaccurately? Is there significant data decay?
Once the root cause of the data problems has been pinpointed, a suitable remedy
can be constructed and then implemented. The final step is to monitor the
While this process seems straightforward, each step has several different
directions from which it can be approached. The key, however, is to work
systematically. If not, you will find yourself applying a Band-Aid when you
really should be doing major surgery or vice versa.