Taking Mythology Out of Resume Screening

Ah, so much for the summer blogging break.  I have so much to say about WFH and the delta variant whiplash.  But, that is for another time.  What I have been thinking about lately is how there is so much available talent (people looking for work and to change jobs) and what employers are doing about it.

Typically, this kind of environment is great news for companies that are hiring.  That is not entirely the case now because, since there is so much employee movement, job candidates seem to have the upper hand in terms of salary and WFH flexibility.  However, employers do have a lot of options as well.  The only problem is that some are over playing their hand.

Case in point is the use of resume screening software.  Don’t get me wrong—this type of tech is something that companies need to use.  It is an efficient and objective way to go through resumes.  However, as this article (thanks to Denis Adsit for sending this my way and the link requires a subscription) points out, employers are likely missing out on lots of good candidates.  It is not because the algorithms don’t work.  It’s because they filled with untested assumptions that are provided by hiring companies.

It is amazing how many myths companies have about who they hire.  For instance, each time I have done a validation study in a contact center, line managers insist that previous experience is a plus.  And each time the data does not support that assumption.1  If you attempted to validate similar assumptions, I am sure that you would find that fewer than 50% were actually good predictors of performance.

When these myths are plugged into resume screen algorithms, they help to screen out people randomly.  This means that you have fewer resumes to read, but it also means that the ones you are reading are not better or worse than the ones you don’t.

Another problem with the data companies give to the algorithms is that that the choices are draconian because they are used as a thumbs-up or thumbs-down screen.  A better approach would be one where certain elements are given points (again, based on a validation study) and a cut-score is used.  For instance, let’s say that your algorithm selects out people who have had more than 3 jobs in 5 years.  You might be missing out on people who have several other very attractive things in their resumes.  And you would potentially be interviewing people with fewer attractive things on their resume but stayed at a job for 5 years.  Is that one thing really such a deal breaker at this stage of the process?

The other hurdles that companies place in front of candidates in the algorithms are unnecessary educational requirements.  I’ve written about this before, so I won’t get into again here.  However, if you are going to validate other assumptions about what is predictive of success on resumes, you should do the same regarding educational requirements.  This will widen your pool and likely lead to an equally, if not more, qualified pool and one that is more diverse.

Resume screening software is a very useful tool in pre-screening resumes.  Like any other computer program, they are only as good as the data that goes into them.  By ensuring that what you provide the algorithms is based on fact rather than myth, you will get a lot more out of the screens.

1 If anything, my experience shows that for contact centers, the opposite is true—those who worked in them before do worse in the next job.  Why?  Well, if they were good at the job, they would not have made a job change in the first place.  Also, there is a lot of unlearning that has to go on when training veterans on the customer management software.

Blacks Welcome to Apply

The aftermath of George Floyd’s murder has many of us asking, “What can I do better?” when it comes to ending racism.  This is critical in that racial bias in hiring have changed little in 30 years.  HR and I/O psychology play a unique role in that we create the processes that allow for equal employment.

None of the suggestions below require lowering of standards.  Rather, it provides a framework for applying standards in an equitable way.  Science and good sense points us in this direction with these actions:

  1. Widen your recruitment net.  If you recruit from the same places, your workforce will always look the same.  There is talent everywhere—go find it.  Whether from a high school in a different part of town or a historically black college/university.
  2. Make Resumes Anonymous.  The science is very clear that anonymous resumes reduce racial and gender bias.  It is not an expensive process to implement and works for all kinds of business.
  3. Examine minimum qualifications carefully.  Whether based on job experience or education, these can serve as barriers to black job candidates.  The ground breaking employment discrimination lawsuit, Griggs v. Duke Power, was based on an invalid requirement that supervisors needed a high school diploma.  Don’t get me wrong—I want my surgeon to be an M.D. But, do your entry level positions really need a college degree?  Do your managers really need to be MBAs?  If you analyze the relationships between education/experience and job performance, you are likely to find that they are not as strong as you think.
  4. Use validated pre-employment and promotional tests.  As a rule, validated pre-employment tests do not adversely affect blacks and are certainly less biased than interviews (see below).  This is particularly true for work sample tests (show me what you can do) and personality tests.  However, cognitive ability tests, especially speeded ones, may lead to discrimination.  If you use them, analyze your cutting score to ensure that it is not set so high that qualified candidates are being screened out.
  5. Reduce reliance on interviews.  Interviews can be biased by race and ethnicity.  And, more often than not, they are far less valid than tests.  We need to convince hiring managers that they are not good judges of talent—very few people are.  Remember, interviewing someone to see if s/he is a “good fit” is another way of saying, “this person is like me.” 

  6. Make your interviews more structured.  This can be achieved by asking candidates the same questions and using an objective scoring methodology.   Adding structure to the interview process can reduce bias (and improve validity).

You may already be doing some of the above.  I would encourage you to do all of them.  The outcome is fairness AND better hires.  What could be better than that?

Is College Recruiting Ageist?

When we hear about age discrimination employment lawsuits, they are typically centered on older workers being let go when a company reorganizes so that less expensive (e.g., younger) employees are retained. Of course more subtle examples of ageism are present in workplaces and we need to be as aware of them as we are of bias against women, the LGBTQ+ community, and racial minorities.

Recently, the US District Court in California allowed an age discrimination case to proceed as a class action. As summarized here, the plaintiffs claim that the company used only college recruiting to bring on entry level hires, hence discriminating against potential hires who were not in college (re: people of 40). As evidence, they present that web postings of the positions only appeared through college recruiting sites and not on their regular career site and that resumes from older workers were regularly rejected. They also argue that the company has a general culture which values younger workers over older ones. The company counters these arguments by saying their process is merit-based and that given the number of candidates who apply, using the current process makes business sense.

There are several aspects of this case which are interesting and instructive:

1) There is nothing inherently wrong with college recruiting, especially for entry level jobs. However, if this is the ONLY way a person can get into the pipeline, by definition you are primarily looking at candidates in their 20s.

2) It shows a presumption that older workers will not take entry level positions. That may be true in some situations, but it is really up to the job candidate to make that determination. If an entry level job pays well relative to the experience necessary, why wouldn’t an older worker take it?

3) Like many class action suits, the statistical data will be a key point in determining if there was adverse impact against those age 40 and older. If, as the company claims, only 3% of college candidates get hired (I can see a huge legal argument about who was an applicant and how many there were), the plaintiffs will have to show that fewer than 2.4% of older candidates (again, a fight over who were actually applicants) were hired for the positions. That seems like a pretty low bar to get over.

4) The company’s second argument that college recruiting is efficient, therefore is OK even if it does discriminate (which they argue it does not), will be a tough one to make. Civil rights laws allow neutral selection techniques to have adverse impact if they are job related, but make no exclusions based on expense. I honestly do not see how this is relevant to the complaint.

This case will take years to wind its way through the courts. However, it does provide a timely reminder to review recruiting processes and valid selection tools for adverse impact based on age and not only race and gender. College recruiting is not in and of itself ageist, but you will want to be sure that it is not the only point of entry into your company.

What Do Grades Tell Us When Hiring?

Welcome to 2018! This first link actually highlights a look at valid personality testing on a largely read website. This makes me think that the year is off to a good start in the field.

Along those same lines of predicting behavior, a line of thought has always been that school grades are indicative of future success. The logic behind this makes sense. If a student applies him/herself and does well in school, then it is likely that he or she will do the same at work. Critics will say that grades measure something very specific that does not really translate to work and there are biases in how grades are given (which is why universities use standardized tests).

As always, what makes a good predictor really depends on the outcomes you are looking for. If your goal is to hire people who are good at following rules and doing lots of things pretty well, then this article suggests that school grades should be part of your evaluation process. But, if you want to hire very creative and novel thinkers, then GPA probably is not your best answer.

What also grabbed me about the article was the definition of success. The research article cited indicated that those who did very well in high school, nearly all of them were doing well in work and leading good lives. But, for the authors, this apparently is not enough. Why? Because none of them have “impressed the world,” whatever that means. And because there are lots of millionaires with relatively low GPAs (here is a suggestion: how about controlling for parents’ wealth before making that calculation?).

From an employment perspective, we need to be clear what valuable performance looks like when validating and part of the selection process. If your goal is to select people into positions that require developing unique solutions, then GPA may not be a useful predictor. However, if you expect people to follow processes and execute procedures, then GPA is likely to be a useful tool which should be used with other valid predictors.

And, if you are looking to hire people who are going to “impress the world,” good luck to you.

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