#6: Maybe, you can stop giving a sh** about prior work experience.

Professional experience. Even better, relevant professional experience. Why has this never been nominated as the 'Non-Word of the Year'?

Its absence spells a heap of rejections for many job applicants. The logic seems straightforward at first. Work long in an area, and you've seen and done more. Thus, you've got more relevant knowledge and suitable skills. Therefore, you'll perform better on the job.

Yes, our brains adore simple, intuitively logical connections. The power of this logic is so strong that many people I know don't even apply for jobs where they feel they lack sufficient relevant experience.

Self-rejection. The nasty little cousin of imposter syndrome.

My sarcastic view?

A potentially high number of applicants don't even apply because they think that a potentially high number of recruiters may find their experience insufficient.

Okay, this view is also partly supported by research. A recent study by Wechtler et al. (2022) shows that hiring managers are less likely to invite candidates with atypical resumes (i.e., too little or too much relevant experience) for interviews. If this behavior becomes widely known over time, it's no wonder that atypical applicants apply less frequently.

I find this absurd. Why? Simply put, experience is implicitly used as a "proxy variable" for suitable skills. And I'm not sure that's a sensible simplification. So, I looked up studies analyzing the relevance of prior professional experience for performance in the current job.

How important is professional experience for performance in the new job?

The research isn't exactly abundant. Back in 1995, Quinones et al. found that the correlation between prior professional experience and later work performance was 0.27. I'd consider a relevant connection to start at around 0.40 or 0.50. If it were a bivariate correlation, 0.27 would mean that professional experience explains roughly 7% of the variance in work performance...out of a possible 100%. In other words: 7 percent of differences in work performance can be attributed to differences in professional experience.

Yes, I hear you typing: "But, DataDan, that study is from 1995."

Hold my Jever Fun.

A more recent meta-analysis by Iddekinge et al. (2019) revisited the question. The result? The correlation between prior professional experience and current work performance is 0.06. This means 0.4 percent of the differences in work performance are explained by differences in prior professional experience.

Let's agree that 0.4% is basically zero.

Now I hear you thinking: "This can't be true. How many potentially suitable people have we rejected last year because we focused on past professional experience?"

The answer is: Probably too many.

But I haven't given up yet. After all, there's a lot of good literature on the validity of selection processes in recruiting. They essentially analyze the average correlation coefficients between various selection criteria and later work performance.

In a very nice overview of the results of various meta-analyses in this area, Prof. Dr. Benedikt Hell has clearly presented these correlations. The decisive result for me is that the correlation between professional experience and performance in Schmidt and Hunter's (1998) meta-analysis is 0.18. In a brand-new meta-analysis by Sackett et al. (2023) , this correlation even drops to 0.07.

My dear data friends. This is enough for a conclusion. These results are based on over 150 individual studies spanning over 50 years of research (based on the publication date of the primary studies in the meta-analyses).

We must all admit that we probably have overestimated the relevance of professional experience for performance potential in a new job. And the reason will be that we mistakenly equate time (professional experience in years) with ability (output of the experience).

My clear recommendation: Look at people's skills. Test these skills with structured employment interviews or a solid test of relevant work knowledge, supplemented by an integrity test. If applicants (of any background) ace these selection procedures, hire them. Regardless of what their experience says.

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This article reflects my personal views only and is not necessarily the view of the companies I am associated with.

Technical note: There have been methodological discussions as to how valid an extensive use of an average correlation and the resulting R-square for impact of a variable actually is. My current take on this: While it may be correct that even lower correlations already stand for a more impactful relationship than previously thought, the relative size of different correlation coefficients in a meta-analysis should still matter for a relative interpretation.