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SmartData Collective > Big Data > Data Quality > Data Quality – Everyone is a Stakeholder
Data QualityPolicy and Governance

Data Quality – Everyone is a Stakeholder

Raju Bodapati
Raju Bodapati
7 Min Read
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I have been wondering when we as a society realize our stake on effective implementation of data quality assurance. We “the people” systematically learn to accept the consequences and fallacies in data and information mismanagement.

We learned to live within this system of errors, without even thinking much about how we can complain (let alone demand the organizations to take responsibility) for their data errors. The following scenario (which is still unresolved) can put our helplessness and/or stigma into a proper perspective.

I have been wondering when we as a society realize our stake on effective implementation of data quality assurance. We “the people” systematically learn to accept the consequences and fallacies in data and information mismanagement.

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We learned to live within this system of errors, without even thinking much about how we can complain (let alone demand the organizations to take responsibility) for their data errors. The following scenario (which is still unresolved) can put our helplessness and/or stigma into a proper perspective.

Four years ago, someone I know got a call from a collection agency twice in a row for two days. When he answered the call, they said he missed paying a hospital bill and his credit would be affected if he did not pay immediately. He paid the amount they said he owed and was told it would not hurt his credit scores. He was given very little information at that time. After a few years, when he ran his credit report, the claim was in two of the credit agency reports as resolved and paid, but it lowered his credit report from “excellent” to simply “good.” After several calls to the hospital administration, he realized they neglected to enter his contact information into their system, thus explaining why they never sent him a bill in the first place. However, they ended up reporting the record to the collection agency. While the manager of the hospital agreed to send a corrective transaction to credit agencies to take it off his credit report, the correction has yet to show on his credit history. The implications of poor data entry and data quality between government, healthcare and financial agencies was significant for him and many others.

Specifically, he now faces:
a) Fear of applying for a loan as he will not get an interest rate he truly deserves.
b) The stress and agony of the required follow-up. This has already consumed so much of his energy and time that he could have utilized for something else.
c) Uncertainty over claim charges. While the charge that he ended up paying was covered by his former health insurance company, he is not sure if he can reclaim the out of pocket expenses.
d) The frustration that the credit agencies and the hospital do not take more responsibility; He is now focused on personally getting his credit report corrected.

A bit of research confirmed my worst fears. The extent of the kind of issues he faced is very widespread and affects many people. According to the U.S. Public Interest Research Group (PIRG), one in four credit reports contains errors serious enough to cause consumers to be denied credit, a lease or even a job (National Association of State PIRGs, June 2004: “Mistakes Do Happen: A Look at Errors in Consumer Credit Reports“). They surveyed adults in 30 states to order their credit reports and complete a survey on the reports’ accuracy.

They found,
– Twenty-five percent (25%) of credit reports surveyed contained serious errors that could result in the denial of credit, such as false delinquencies or accounts that did not belong to the consumer;
– Fifty-four percent (54%) of credit reports contained personal demographic information that was misspelled, long-outdated, belonged to a stranger, or was otherwise incorrect;
– Twenty-two percent (22%) of credit reports listed the same mortgage or loan twice;
– Almost eight percent (8%) of credit reports were missing major credit, loan, mortgage, or other consumer accounts that demonstrate the creditworthiness of the consumer;
– Thirty percent (30%) of credit reports contained credit accounts that had been closed by the consumer but remained listed as open;
– Altogether, 79% of credit reports surveyed contained either serious errors or other mistakes of some kind.

These issues are clearly the results of many systemic failures. First, the consumers should be able to easily lodge a complaint and be able to report to the government on these blunders in the system. Second, government should track these cases and impose severe penalties on all the responsible organizations by making them pay the total cost of failure. Third, there should be public policies in place to protect the consumers against the subtle effects of these errors in other related systems like how banks determine the interest rates. Fourth, the extent, speed and completeness of addressing these issues should be reported publicly by media, so the stock markets take information quality as a performance measure of the organizations. Once these are in place, the organizations would naturally be driven towards taking responsibility for their data quality fallacies.

In summary, it is each one of us and collectively the civilized society as a whole that should develop means to demand that organizations and governments take full responsibility for the impacts poor data and information quality management have on the society by making them accountable for each and every fallacy in their information management, assurance and oversight processes.

TAGGED:data managementdata quality
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