Brains or Personality: Which Predicts Performance Better?

If there’s one “rule” in Industrial-Organizational Psychology, it’s that intelligence (i.e., cognitive ability) is the strongest predictor of job performance. But there’s a glaring omission in this claim: the vast majority of research has looked at task performance, that is, the behaviors related to your official job responsibilities and duties.

We know that job performance is also made up of two other types: (1) harmful counterproductive work behaviors and (2) helpful organizational citizenship behaviors.


How well does intelligence predict these other two types of job performance?

Harmful CWBs & helpful OCBs

First, some definitions.

Counterproductive work behaviors (CWBs) are ones that (1) harm the organization such as theft, sabotage, or shirking responsibility and (2) harm employees such as yelling, insults, or taking credit for someone else’s work.


Organizational citizenship behaviors (OWBs) are ones that (1) help the organization such as volunteering for overtime and proactively suggesting new ideas and (2) help employees such as offering to help others and working productively with difficult colleagues.

Why should we care about CWBs and OCBs?

Research has found that harmful behaviors such as theft, sabotage, and increased absenteeism and turnover result in billions of dollars of financial loss. Helpful behaviors, on the other hand, encourage creativity and adaptability in the workplace and improve employee morale (i.e., keep people happy).

Does intelligence or personality predict CWBs and OCBs?


The results found that intelligence accounted for 9% of the differences among employees in harmful counterproductive work behaviors while the Big Five personality traits (Openness, Conscientiousness, Agreeableness, Extraversion, Neuroticism) accounted for 91% of the differences among employees. So personality is the overwhelming winner there.

More interesting was the finding that there were no differences in self-reported counterproductive work behaviors between high- and low-intelligence employees but managers reported high-intelligence employees had lower rates of counterproductive work behaviors. Are managers falling prey to a halo effect or are these smarter employees just better at hiding their harmful work behaviors? Unknown.


For helpful organizational citizenship behaviors, the results were pretty evenly split: intelligence accounted for 53% of the differences among employees and personality accounted for 47%.

Overall job performance

The results for overall job performance (task performance + CWBs + OCBs) verified that intelligence is a stronger predictor than personality, accounting for 71% of the differences among employees vs. 29%.


The takeaways

Research suggests that compared to intelligence, personality is a better predictor of harmful work behaviors, as good as a predictor of helpful work behaviors, and not as good but still valid predictor of overall job performance.

So should you use intelligence or personality to hire? Your best bet is measuring and assessing both. But if you have to choose, I’d argue you should use personality because of the major concern with intelligence testing: the potential for adverse impact (i.e., differences in scores among minority groups).

It also makes a difference depending on the role you’re hiring for. For sales in particular, research by Vinchur and colleagues of 45,944 salespeople found that intelligence was correlated with sales but only for manager ratings of performance. For objective sales performance, the correlation with intelligence was effectively zero.

So it’s good to be smart, but it’s better to be accurate when it comes to your hiring.

How do you assess brains and personality when you hire? Let me know in the comments.

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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices in data-based recruitment. She writes about research and trends in talent acquisition, recruitment tech, and people analytics.
Ji-A Min