Personality tests and data analysis have become the new methods of finding employees for companies that wish to cut costs and boost productivity. Interviews and the process of picking workers off of hunches has fallen by the wayside for such large and small companies alike as statistics become the guiding compass for hiring. The implications of using algorithms to choose who gets the job can lead to sticky legal situations as data can unintentionally filter out older or minority applicants. What remains the question in business owners’ minds is whether or not software can truly replace a human being in choosing the best man or woman for a certain job.
First and foremost database-hiring is a means by which most companies can save money. Every company wants to bring in as much profit as possible. Sending this profit out the window by hiring and training an employee who sticks around for a month is an unnecessary drain on companies’ monies. The algorithms of companies like Kenexa Corporation are backed by billions of pieces of employee data, and are drawn upon when a potential employee takes a pre-employment test. This data has no personal opinions or biases that would lead the test to a skewed conclusion. When a human interviews a potential employee, they are relying solely on their knowledge past experience to pick the right employee. The better of the two choices is obvious; I’d rather have billions of pieces of fact influencing the decision of who to hire as opposed to a person with exponentially more bias and far less information.
That being said, no employee or employer wants a person with a dreadful personality working with or for them, regardless of how good they are at their job. This is why the personality test aspect of database-hiring is so important. Personality plays a big role in who gets what sort of job; it is not discounted because a human isn’t present to pass judgment. Also, businesses don’t want to invest money in tests based on big data that potential employees can easily manipulate to get the answers they think the employer wants to hear. Test designer Robert Hogan, Ph.D. (and president of Hogan Assessment Systems) hears those people loud and clear who ask “What’s the point? Anybody can fake them!” and answers that cheaters “may be able to fake a whole scale (a single aspect of the measurement), but they won't fake a whole profile.” The idea that this method of using massive amounts of data to find the right employee for a job is all-encompassing and multi-faceted disallows fakers to weasel their way into a job where the data says they don’t belong.
The relationship between businesses using their own big data to turn a profit or do some other good and that of using others’ big data to hire the correct employees makes opening the door to one or the other easily possible. Once companies become aware of big data and what it can do for them, they won’t want to stop there...
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Sources: The Wall Street Journal (Thursday, Sept. 20th 2012 pg. B1)