Bye-Bye Bias: Practice Fair Hiring

Long-term unemployment continues to vex us. And even though the numbers have thinned after peaking in 2010, it lingers on. One academic study from the National Bureau of Economic Research shows that job applicants who have been unemployed for six months get 45 percent fewer callbacks than people out of work for just one month. Diminished skill sets and lack of job training are among the reasons given for tossing their resumes into the circular file.

It’s simple. The longer people are unemployed, the less attractive they become. In fact, another study by economist, Rand Ghayad, found that companies even favored job applicants without relevant experience over those who used to work in the same industry, but have been unemployed for a long stretch.

However, Alan Krueger, former Chair for the Council of Economic Advisors, found that the long-term unemployed really are not much different than the short-term unemployed. They may be a little older, but they’re typically as educated and work in the same industries as the short-term unemployed.

So, like the old saying goes, “Don’t judge a book by its cover.” Just because someone has been out of work for an extended period of time, does not mean that their skills and abilities are any less than those people who have been out of work for shorter time periods.

No More Guessing Games  

This is where predictive hiring tools can help. If you’re concerned over whether or not a candidate has what it takes, the powers of technology can play a key role in helping you to make an accurate and educated determination. Technology helps to eliminate unintentional (or intentional) biases and opens up a whole new pipeline of talent that may have previously been passed over.

For example, let’s say you receive a resume that details a person who worked in your industry and has the necessary skills, but has been out of work for eight months. The first things that fly through your mind may be:

  1. They were laid off because they were less valuable employees.
  2. They may have trouble readjusting to the daily grind.
  3. They’ll be more difficult to manage since they’ve been out of work for an extended period.

There’s no more making assumptions or playing guessing games when you use predictive talent selection technology. You’ll get the real story and a likely a loyal employee to boot. It’s only fair.

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