In the Face of Big Data, Interviews Are Obsolete

Once upon a time hiring the right employee was relatively easy and inexpensive. A job application and quick interview was all that was needed. Life was simpler. Attitudes were relatively predictable. Replacements were a dime a dozen. A hiring mistake was easily absorbed into the cost of doing business.

But hiring today is complicated. The risks are bigger. Jobs are more complex and constantly changing. Attitudes toward work are almost unrecognizable from generation to generation. And the cost of making a hiring mistake falls right to the bottom line.

If management hopes to get back in the game, then big data offers hope to those companies who seek better hiring and retention solutions. Unfortunately most organizations are lucky if they collect even a little data. And then it typically just gets buried in a cabinet or on a manager's hard drive.

For starters, most companies are still using the interview and reference checks as the holy grail of predictive science. It's like trying to douse a burning building with a garden hose. It's filled with the best of intentions, but soon hiring and retention will become crisis management—and interviews provide little information to help HR leaders navigate the talent management chaos.

Below are three major weaknesses of interviews, and how big data can address the information gap when it comes to hiring:

At its very core interviews are loaded with bias. I love this quote in a recent Fast Company article:

"...everyone [must] get past the idea that only blatant racists, misogynists, and homophobes are biased. If you have a brain, you are biased. End of story."

Even if a manager is a skilled interviewer, he or she is susceptible to personal bias about everything from gender to skin color to age to hair style, tattoos, and just about anything you can see or hear. That's just human nature. Most of us try our best to block out bias but it's impossible. (If you would like to "test" your bias, try this.)

The criteria for the manager's hiring success is rarely tracked. That's because few people interview exactly the same. Even when the same questions are asked, our personal styles skew how we ask the questions and hear the responses. If by chance all those factors can be neutralized, one big gap still exists.

It is almost impossible to track what makes one candidate more successful than the next based on only the interview. The interview is just too subjective—most companies have no clue how or why a manager selects one candidate and rejects another when the interview is the primary selection tool.

Hiring then becomes a crapshoot: Each recruiter and hiring manager has a different baseline; each hiring event recreates the wheel. With the lack of a "magic formula," it is nearly impossible to replicate success.

On top of manager bias and personal style, we add the candidate to the interview equation. It's not out of the ordinary to assume he has practiced and polished his interview performance with a lifetime supply of career coaches, his resume is impeccably reviewed and his cover letter is ghostwritten. Oftentimes, the hour-long interview will be the best performance a manager ever sees!

The time a candidate invests in preparing for the interview is typically far more than most managers imagine. For many managers, the interview is just another meeting or disruption in his chaotic schedule. Their goal is to get through it as quickly as possible and move on to more important things—like budget or putting out the next fire—but for candidates, this is a make-or-break moment they have rehearsed in their heads countless times.

Big data offers some relief, filling in holes of information and neutralizing personal biases.

Pre-employment testing, where large databases of candidate information are analyzed, is one way big data can ease the hiring process. Patterns and trends from thousands of people are analyzed and sophisticated algorithms sift through combinations of data for predictive trends that an individual couldn't catch. Pre-employment tests add objective and predictive metrics to the sea of subjectivity upon which managers now base hiring decisions.

With access to big data available to almost anyone who wants it, the playing field for talent is almost level. Managers can figure out what makes top performers tick, why mediocre performers miss expectations, where the good talent is hiding, and how to attract the best employees.

Finding where future talent is hiding and how to attract and retain them is an endless journey. But you have to start somewhere. And you have to start right now.

Photo: Creative Commons by Luke Chesser