The value of using GMA tests for identifying high potential candidates in recruitment is well known. The utility and predictive validity of GMA tests has been studied since the beginning of the 20th century. Research shows conclusively that people with high GMA are more likely to be top performers than people with low GMA. In the words of Sternberg and Hedlund (2002):
The so-called general factor (g) successfully predicts performance in virtually all jobs (Schmidt & Hunter, 1998). We do not believe there are any dissenters to this view. [...] The issue is resolved, and it is not clear that further research will do anything more than to replicate what has already been replicated many times over.
It is also clear that the effect of GMA on job performance is stronger as the complexity of the job increases. For unskilled jobs, it has been estimated to r=.39 (which is still a strong relationship in the context of psychological science) and r=.74 for professional and managerial jobs (Hunter et al., 2006).
These findings are however always discussed on an aggregated level, and the effects are calculated for groups of people. Yet, as managers, recruiters, candidates and employees we are mostly concerned about single individuals. What does it mean for one individual to have a high GMA?
A common theory is that GMA is related to job performance through learning. That is, a person with high GMA is likely to accumulate relevant skills and knowledge, which in turn makes them more likely to perform well.
Looking at the schematic above, it is clear that there are more things at play than intelligence when it comes to job performance. Even the most intelligent person will not acquire any knowledge without putting in time and effort. And without relevant knowledge, no amount of GMA will make a top performer.
High intelligence can be seen as a competitive advantage, much like being tall in a team of basketball players. It certainly helps, but there’s a lot more to being a good basketball player than being tall. And there’s also a lot more to being a top performer than having a high GMA.
We believe that GMA should be evaluated in relation to the demands of the job and weighted together with other information about the individual. Personality, previous experience, existing knowledge are all relevant data that should be taken into account. What an individual lack in one area can be compensated by strengths in other areas.
Hunter, J. E., Schmidt, F. L., & Le, H. (2006). Implications of direct and indirect range restriction for meta-analysis methods and findings. Journal of Applied Psychology, 91, 594-612.
Sternberg, R. J. & Hedlund, J. (2002). Practical Intelligence, g, and Work Psychology. Human Performance, 15, 143-160.