In his book “Incognito: The Secret Lives of the Brain,” David Eagleman discussed aspects of a bizarre, and rare, brain disorder called Anton’s Syndrome in which a stroke renders a person blind – but the person denies their blindness.

“Those with Anton’s Syndrome truly believe they are not blind,” Eagleman explained.  “It is only after bumping into enough furniture and walls that they begin to feel that something is amiss. They are experiencing what they take to be vision, but it is all internally generated. The external data is not getting to the right places because of the stroke, and so their reality is simply that which is generated by the brain, with little attachment to the real world. In this sense, what they experience is no different from dreaming, drug trips, or hallucinations.”

Data quality practitioners often complain that business leaders are blind to the importance of data quality to business success, or that they deny data quality issues exist in their organization. As much as we wish it wasn’t so, often it isn’t until business leaders bump into enough of the negative effects of poor data quality that they begin to feel that something is amiss. However, as much as we would like to, we can’t really attribute their denial to drug-induced hallucinations.

Sometimes an illusion-of-quality effect is caused when data is excessively filtered and cleansed before it reaches business leaders, perhaps as the result of a perception filter for data quality issues created as a natural self-defense mechanism by the people responsible for the business processes and technology surrounding data, since no one wants to be blamed for causing, or failing to fix, data quality issues. Unfortunately, this might really leave the organization’s data with little attachment to the real world.

In fairness, sometimes it’s also the blind leading the blind because data quality practitioners often suffer from business blindness by presenting data quality issues without providing business context, without relating data quality metrics in a tangible manner to how the business uses data to support a business process, accomplish a business objective, or make a business decision.

A lot of the disconnect between business leaders, who believe they are not blind to data quality, and data quality practitioners, who believe they are not blind to business context, comes from a crisis of perception. Each side in this debate believes they have a complete vision, but it’s only after bumping into each other enough times that they begin to envision the organizational blindness caused when data quality is not properly measured within a business context and continually monitored.

This post originally appeared at OCDQ Blog.

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