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Why Being Cautionary with Big Data is a Big Deal

Posted by Dominic Barton

27-May-2015 15:14:00

“While no one wants to roll back civilization, there is a common belief that society can anticipate and prevent misapplications of technology while still enjoying its benefits. In fact, slowing the pace of technology to prevent harms almost always requires forgoing the much greater benefits it can bring. So it is with Big Data.” - Joe Kennedy (@JV_Kennedy), Attorney and Economist




Kennedy is right. The problem isn’t using technology; the problem is when organizations begin to replace functions that thrive on human interaction with technology. In recruiting it may seem more unbiased, but there are problems that arise with EEOC compliance. In a recent post, we explained that even when using big data as a means of sourcing and finding the best candidates, you’re still at risk for being found discriminatory. When developing its case in a discrimination lawsuit, the EEOC need only show through statistical analysis how your organisation’s hiring practices affect an applicant demographic negatively. However, using big data to augment your hiring practices rather than drive them can mean the difference between adherence and noncompliance with EEOC regulations.

Be Watchful


It’s faulty to assume big data analysis can save an organization from hiring risks. The truth is, as with any piece of technology, big data has its own set of benefits and risks. For example, the Federal Trade Commission noted legal concerns even categorizing consumers with big data asking if it’s an inclusionary or exclusionary tool. The same could be said for your candidates. You have to understand how the use of big data categorizes your talent pool and the implications for your hiring process - both positive and negative. There were over 88,000 discrimination cases filed with the EEOC last year alone. Although that number decreased from over 93,000 in 2013, that doesn’t mean big data saves companies from EEOC non-compliance.


broadbeantwitter-01There were over 88,000 discrimination cases filed with the EEOC last year alone. 



How to Use Big Data


The potential insecurities surrounding the use of big data in recruiting, are predominantly a result of an over-reliance on the technology. Using big data analysis as a way to augment your hiring process, making it more efficient. With tools like our Big Data Analytics Suite, users are able to determine not only source quality and effectiveness, but also recruiter efficiency and candidate demographics so they’re aware of any potential discriminatory issues before they arise. However, even though 78% of companies with 10,000 employees or more said investing in talent analytics is urgent, nearly half (45%) said they are not yet prepared.


45% of companies say they're not prepared for investing in talent analytics.


Finding the Balance


By 2018, 6,400 organizations with 100 or more employees will have integrated big data analytics. Despite the developments in recruitment technology, it will always be recruiters finding the best candidates for the job. Recruiting will never truly lose the human element and perhaps that’s why there’s a bit of apprehension around the idea of talent analytics. Big data in recruiting can improve the quality of the talent pool and, subsequently, the quality of the hire. As the tools for recruitment have developed, it’s now almost a necessity for organizations to use talent analytics to make more educated hiring decisions and better business moves.

Big data in recruiting isn’t just a numbers game. Yes, more and more recruiters need to have data experience and training, but data science isn’t the foundation for the integration. Big data recruiting is the analytics of people. Using data analytics to hire candidates simply based on those with the highest scores is a quick way to lose the essence of HR and recruiting in the power of big data. However, by paying careful attention to the requirements of the EEOC and the tools that help you to understand your recruitment habits better, you can avoid the misappropriation of big data.


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Topics: Big Data , Business Intelligence