Poor Quality Data and Equifax

Data in information systems allows for businesses to process various actions in a way that is seamless. If one imagines a business as a factory, many businesses main product is data. From hospitals to banks, data is created, stored, transferred, and viewed every single, work day. If this data is of poor quality, it may slow down a business’ processes. For example, a hospital’s medical records are still on paper and have not been transferred to a digital copy. Such an event can trigger easier data breaches and longer wait times for information to be retrieved, copied, and transferred.
What makes data quality poor? There are collectively defined standards that define data quality. They are accuracy, completeness, consistency, uniqueness, and timeliness (Kimball, Ross, Thornthwaite, Mundy, & Becker, 2011). When poor quality data is inaccurate like for example, the last name of a customer in a bank, this leads to service hang ups and mistakes. For completeness and consistency, poor quality will not be clear or in agreement with underlying atomic-level detail (Kimball, Ross, Thornthwaite, Mundy, & Becker, 2011). If such data exists in a business, it can lead to further mistakes down the line, especially regarding assessments or information retrieval. Effectiveness in information retrieval is important, that is why poor data quality means little to no uniqueness. Lastly, if data is not current, relative to a business’ needs (timeliness), the business suffers.
I can provide an example from my own personal experience when I went to the dentist. The dental office still has paper records and have yet to transfer them to a digital version. They have extensive paper files put into a cabinet that can be easily accessed by patients or anyone walking into the office. Because the data is on paper, anyone that sees where it is stored can walk in ad take it. Additionally, they do not check for duplicates and often have incorrect spellings of patient names or old addresses that have not been updated for years. This leads to chaos and missed files, longer waits for patients.
To ensure good data, organizations need to improve compliance and accuracy. Poor data quality may negatively influence the public perception of a company/organization. Going back to uniqueness and eliminating redundancies, when duplicate mailings are sent for example to customers, this leads to extra costs. These costs can be eliminated by implementing adherence policies to manage the quality of data entry (Roebuck, 2011). Policies can be written to ensure there are periodic checks for duplicate addresses, out of data contact information, and so forth.
This lends to creation of methods that improve information accuracy and uniqueness. These two things are key hallmarks of top quality data. To do that organizations may need software upgrades like CRM software (Roebuck, 2011). They may need to digitize their information and set up cloud-access applications to store and easily transfer/remove data.
If these practices cannot be done, poor data security can happen. Going back to the example of the paper records at the dental office, poor quality data left in an easy to access place leaves the personal and private information of dozens of patients in jeopardy of being taken. When there is poor data security, confidential information can be leaked easily, leading to data breaches (Lopez & Durai, 2018).
Many problems have stemmed from confidential data breaches that have led to prolonged problems for business, customers, and patients. One such major poor data security example is the Equifax security breach. The Equifax security breach led to over hundred million Americans to have their personal data stolen from them. Now millions of Americans stand to face potential identity theft because their precious and confidential information was handled poorly.
The Equifax nightmare has resulted in many people facing a host of problems that come from their personal information being exposed. From identity theft to issues with credit and loss of potential income, the Equifax data breach has led to people losing their privacy. Social security numbers, license numbers, names and addresses were exposed thanks to the malevolent actions of hackers and the poor, careless actions of Equifax employees.
After that first bombshell in early September, news trickled out in the days that followed, including the revelation that as many as 145.5 million people were exposed to identity theft in the massive breach. It was revealed that part of the trove of personal data seized by the bad guys included Social Security numbers, credit and debit card numbers and names and addresses (Johnson, 2018).
To make matters worse, Equifax attempted to force consumers affected to remove their ability to sue in court through acceptance of their credit monitoring service (Johnson, 2018). What has happened from this is mass litigation issues for Equifax. For instance, San Francisco Super Court has allowed a lawsuit for millions of affected to sue Equifax for careless data breach. “The lawsuit further accuses Equifax of violating California state law, failure to provide a timely notice of the data breach to affected Californians and failure to provide complete, plain and clear information” (Buhr, 2017).
Keeping data secure remains of utmost importance hence why data governance is so important. Data governance is processes organizations follow to safeguard high quality data as it exists throughout complete lifecycles. Data governances involves four main focus areas: usability, integrity, security and usability (Bhansali, 2014). Through these standards, data management avoids the pitfalls of poor handling, poor quality data, and so forth. Data governance acts as an outline for what must be done to secure confidential data.
References
Bhansali, N. (2014). Data governance: Creating value from information assets. Boca Raton, FL: CRC Press.
Buhr, S. (2017, September 27). San Francisco sues Equifax on behalf of 15 million Californians affected by the breach. Retrieved from https://techcrunch.com/2017/09/27/san-francisco-sues-equifax-on-behalf-of-15-million-californians-affected-by-the-breach/
Johnson, C. (2018, February 14). Turns out, the Equifax data breach was even worse than we thought. Retrieved from http://www.daytondailynews.com/business/personal-finance/turns-out-the-equifax-data-breach-was-even-worse-than-thought/rT2KfaU5SLna2c2I3xprPP/
Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., & Becker, B. (2011). The Data Warehouse Lifecycle Toolkit. Hoboken: John Wiley & Sons.
Lopez, D., & Durai, M. A. (2018). HCI challenges and privacy preservation in big data security. IGI Global.
Roebuck, K. (2011). Customer relationship management (CRM) software: High-impact strategies, what you need to know : definitions, adoptions, impact, benefits, maturity, vendors. publisher not identified.