“Congratulations, you are the grand prize winner of $15 million!”
“Congratulations, you are the grand prize winner of $15 million!”You receive a letter proclaiming the above via certified mail. It is perfectly legitimate; this is no Publishers Clearing House ploy. You quit your job, do some celebratory big item shopping and tell everyone you know the good news.
“Congratulations, you are the grand prize winner of $15 million!”
You receive a letter proclaiming the above via certified mail. It is perfectly legitimate; this is no Publishers Clearing House ploy. You quit your job, do some celebratory big item shopping and tell everyone you know the good news.
The next day, you receive a retraction stating that the letter was mistakenly sent to you. You have won nothing.
Around 800 Carnegie Mellon University applicants were recently taken on a similarly devastating roller coaster ride, NPR shared. Jubilation at achieving a dream was followed by a crushing blow. The culprit? Lack of data controls.
The school mistakenly sent acceptance emails to hundreds of hopefuls who applied to Carnegie Mellon’s prestigious Master of Science in Computer Science program. A few hours later, an email with a much different tone arrived in their inboxes.
A school statement read: “This error was the result of serious mistakes in our process for generating acceptance letters.”
The admissions department had failed to confirm that it had selected the correct recipients for the acceptance emails, an oversight that is all too easy to make. The academic world alone has seen its fair share, with Johns Hopkins University and UCLA facing similar fiascos in the past few years.
Moments like this can be incredibly damaging for companies and institutions. Mistakes in data can lead to widespread errors, from communication blunders such as this one, to inaccurate financial reportings. Reducing reputational risk is an important discipline for companies now more than ever, when credibility is at stake. The right data controls provide the mechanism to ensure data quality is implemented whenever data is processed or exchanged. Additionally, checks and balances through data quality provide comfort in knowing compromised data won’t make it into your analysis reports which may be used for internal or external communication.
Data integrity controls monitor and mitigate risk by continually reconciling and validating information to ensure that it is accurate and reliable. This may sound time consuming, but it does not have to be, thanks to automation. The right controls will automate the process, performing the tedious work of keeping your data clean in real time.
No organization wants to be the harbinger of doom. Rigorous data controls will help minimize the chance that you will ever find your organization in this position.
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This was a guest blog post by Infogix Product Manager Jay Shah.