In psychology few things have shown such everyday value as discovering how General Mental Ability (GMA) works. And that's because it helps to explain how the various parts of our intelligence mesh together.
It's difficult to argue that we humans don't differ in our ability to understand and solve problems, to learn, to remember, and to use specific types of thinking: some people are better at numerical stuff, others are more verbal, still others are good at visualising problems, and so on. But of course, how well we use our individual cognitive abilities varies depending on the occasion; and what we know about how successful we have been, on how they are measured.
However, before exploring what it is to use our abilities successfully, there's something else to know about GMA. Which, by the way, is sometimes just called "g." It sits at the top of a hierarchical structure with three stratum (layers). On the next stratum down are "fluid" and "crystallized" intelligence, different aspects of memory, processing speed, and other core abilities. And beneath this are a long list of specific abilities like verbal, numerical, and spatial reasoning.
Technically this structure is known as the Cattell-Horn-Carroll Model and it's based on over 70 years of research. GMA is at the top because it's the summation of all the parts. There's a bit of GMA in all the other aspects of intelligence. Basically, it's the glue.
From a career point of view all the parts may be important — depending on what someone is being asked to do. But the two that typically receive the most attention from employers in interviews are "fluid" and "crystallized" intelligence.
Fluid intelligence is the ability to deal with new situations and to quickly solve problems using logic — to be able to "think on your feet." It's closely related to the ability to learn and often draws on working memory, especially when there's a complex task to be done. People often refer to fluid intelligence as someone's potential.
In contrast, crystallized intelligence is what someone has learnt through education, training, or experience. This is about using language, skills, and existing strategies to tackle problems. When employers talk about wanting someone who can "hit the ground running" this is what they mean. Someone who already knows what to do, from day one.
While both fluid and crystallized intelligence are important, in a hiring context the former should be top dog. That's because employees with higher potential learn job requirements more quickly and in greater depth. This is something that's particularly important in a fast moving or changing workplace.
Clearly knowledge and relevant experience are also useful things to explore — and may predict short-term performance — but GMA is a much better predictor of long-term performance.
It's also the case that GMA predicts performance even when job knowledge is taken into account. With high GMA, employees are able to build on existing knowledge and make decisions even in unfamiliar situations. So maybe what employers should really be looking for are employees who can "hit the ground learning!"
What does success look like? Let's look at the numbers.
Large meta-analytic reviews consistently find that GMA predicts job performance. For instance, a review of 20,000 studies and 5 million participants found average predictive validities of 0.5. This tells us that the percentage of variance in job performance accounted for by GMA is 25% — put simply, it predicts one quarter of all job performance. In pure prediction terms this is a significant figure. If you enjoy the technical details, this means that an increase of one standard deviation (SD) in GMA is associated with a 0.5 SD increase in work performance, above the average. When applied to a hiring process this is a very big deal indeed.
Other studies have found that GMA predicts work performance and ability to learn, to different degrees depending on the complexity of work. In practice this tells us that while GMA is a good predictor for all roles — from a team member in a fast food restaurant to a manager in a large organization — it works best for jobs of medium to high complexity. For medium complexity, that's things like Administrators, Customer Service Representatives, Sales People, Technicians, and Skilled Trades; and for high complexity, Managers, STEM, IT Professionals, and Functional Specialists (Finance, Marketing, Legal, HR/Training, etc). In this case, if the numbers are split by complexity, the prediction of work performance is even more impressive, ranging from 0.53 (28%) to 0.64 (41%), respectively.
As you might expect, because GMA predicts work performance it also predicts how high someone will rise within an organization. This is a complicated topic because it's also heavily influenced by background, education, and opportunity. However historical US Employment Service data suggests there is an extremely powerful correlation (0.72) between GMA and occupational level. In a similar way, lifetime earnings also seem to be influenced by GMA. Something that's true even when controlling for socioeconomic status. The higher your level of GMA, on average, the higher your earnings.
Obviously success at work — and in life — is far more complicated than simply looking at a person's GMA. There's the influence of background, education, and opportunity, quite apart from personality, motivation, values, and interests. Also being able to demonstrate potential relies on being in the right place at the right time, and for some, just being given the chance to show what they can do.
However there's an important role for GMA, as long as employers use tests that are reliable, valid, and fair. In particular, prioritize tests of GMA that focus on fluid intelligence. Because what is remarkable is that assessing GMA is predictive of work performance across all industries and all levels of work. When used wisely it's the best "one-shot" predictor of work performance available.
Traitify is working hard to bring you a GMA assessment soon! If you'd like to learn more, connect with us.
