Big data takes on the role of human resources

Since the recent recession hobbled the economy, Americans have struggled with unemployment. Bob Eisenbreis, a chief monetary economist with New York's Cumberland Advisers, said that although the unemployment rate is currently recognized as 7.7 percent, the true level is 14.3 percent when factoring in the underemployed, reported Forbes. 

One of the hardest hit demographics in the recession has been young adults between 16 and 24. According to the Center for American Progress, the unemployment rate for that demographic stands at 16.2 percent. Furthermore, the organization found that experiencing an extended period of unemployment early in a career could have an adverse effect on an individual's earning power later in life. A prospective worker who has been unemployed for at least a period of six months stands to lose $22,000 over the course of the ensuing decade. The organization's analysis concluded that young Americans will lose approximately $20 billion in potential earnings in the next 10 years.

Using big data to remove extraneous information
Many capable applicants have found themselves passed over for many jobs as traditional hiring methods overlook their potential in favor of flashy credentials that do not necessarily predict future success. However, big data has emerged as a possible solution to this issue. The New York Times reported that Luca Bonmassar and his analytics firm Gild have devised a program that attempts to quantify more abstract qualities in an applicant. The basic goal is to ignore criteria such as an applicant's alma mater and simply identify whether he or she can effectively take on the duties of the vacant position. 

Bonmassar's software specifically focuses on the adeptness of computer programmers. With the internet as a data pool, the program searches for data that would suggest whether an applicant's code is respected among other programmers and how often it gets reused. The tool also combs social media sites in an attempt to ascertain how well a potential employee will interact with current staff members.

Addressing hiring bias concerns
Gild's chief scientist, Vivienne Ming, believes that data analytics software can be used to successfully eliminate human bias from the application process.  The existence of bias across many industries has been well documented. For instance, a study conducted at Princeton University found that female applicants for a managerial position were less likely to be hired because they were viewed as less competent than identically qualified male applicants.

Developing Hadoop big data tools for the application process is a win-win scenario. For qualified applicants who have languished in unemployment or have been passed over for promotions, data analytics tools can finally showcase their potential. Businesses, on the other hand, can benefit by hiring more capable and fitting employees without the blight of bias.

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