Why do we recommend these three different measures (constructs)?
In short, we use these constructs in our assessment because they’re
Proven, valid, and reliable
predictors of job performance
Relatively stable throughout
an individual’s adult life
And there are decades of supporting research to evidence both points.
We measure different attributes of job seekers to paint a fuller picture of who they are. Intuitively, you know that a really motivated individual isn’t necessarily a good problem solver, or someone who's really outgoing isn’t necessarily going to be a quick learner. So yeah, intuitively it makes sense.
But warm-fuzzy feelings aren’t enough for stakes this high. We rely on meta-analyses, like the study from Schmidt, Oh, & Shaffer, that highlight the validity of the measures used within WonScore.
As a whole, WonScore is a powerful predictor.
But even taken individually, each component of WonScore has undergone rigorous industry validation.
Kind of the top dog here.
Cognitive ability is widely considered the best general predictor of on-the-job success.
This measure is valid for all jobs, but it’s particularly important for those very complex, technical, and/or creative roles. In other words, cognitive ability becomes more critical as the role requires increased problem solving, rapid learning, and agile adaptation.
Cognitive ability was made popular in the second half of the 19th century, when (surprise) researchers noticed there’s a correlation between intelligence and performance related to mental tasks. Since then, it has become a permanent fixture of psychological research.
Since the popularization of cognitive ability, many competing theories have emerged to define the construct. However, the Cattell-Horn-Carroll (CHC) theory has become the dominant model among leading researchers. CHC identifies three layers of cognitive ability – starting at the general level (which is what Wonderlic measures) and getting successively more and more narrow in terms of ability. The general cognitive ability measured by Wonderlic is what has been most commonly studied in relation to predicting job performance across all jobs. In fact, as the CHC theory took hold among most cognitive ability experts, researchers shifted their efforts away from understanding intelligence itself and toward showing that cognitive ability can predict meaningful outcomes, like job performance.
And their research continues to reinforce what Wonderlic has demonstrated since its foundation- that cognitive ability is, bar none, the most effective way to predict job performance. This has been widely supported by numerous studies throughout several decades. It’s predictive of success on the job, and in life.
That hasn’t stopped psychologists, social scientists, legal experts, and governmental agencies from debating the accuracy of cognitive ability. So why the debate? It stems from imperfect assessments used throughout history. Differences in cognitive ability across groups have been noted in traditional cognitive ability assessments. These scoring differences are commonly linked to differences in socio-economic status and as a result of structural inequality. We’re breaking away from that by pairing our Motivation and Personality assessments with Cognitive Ability. We don’t like structural inequality. It isn’t fair and it can prevent an organization from identifying the most qualified applicant.
We’ve had 80 years to tinker with our process- the result?
We’ve got the sharpest, fastest toolset on the market.
RIASEC (and sometimes Y)
How great is that acronym? Maybe we like it cuz it comes from Holland. No, not the Dutch- we’re talking about John Holland and his research. He’s kind of a rockstar around here.
Since the early 1900s, researchers have attempted to understand how an individual’s motivation can impact their performance in the workplace. Rather than try to handle everything that makes up a person’s motivation, researchers studied elements of motivation – such as vocational interests – in order to break up the complex topic. Broadly speaking, vocational interests represent an individual’s preferences for certain work activities and situations that they find motivating. The RIASEC typology of vocational choice proposed by John Holland in 1959 has become one of the most enduring and widely-accepted theories in the field.
His research proved that interest alignment has a strong relationship with employee motivation. Translation- if you’re doing something you like, then you’ll be more motivated to keep doing it. Who knew. (Holland. John Holland knew.) The model suggests that people will demonstrate effort and stability in careers that align with their interests.
On the other hand, if there’s a disconnect between a person’s interests and the environment they’re working in, it’ll lead to dissatisfaction, unstable career paths, and lowered performance. To measure this alignment, the RIASEC model is made up of six types, each reflecting a different domain of vocational interests (i.e., Realistic, Investigative, Artistic, Social, Enterprising, and Conventional interests). Since its inception, the RIASEC model has exerted a significant impact on the fields of industrial and organizational psychology, along with vocational counseling.
Using Holland’s model, WonScore’s motivation component
determines how well each candidate’s interests align with
the work they’ll be doing.
When it comes to personality, the Five Factor Model (FFM) is the go-to for I/O’s looking for the best of the best in hiring measures. We’re talking about the Five Factor Model of Personality, which focuses on an individual’s stable traits and behavioral tendencies.
Personality has been conceptualized in a number of different ways, but no studies have reached the same level of agreement and popularity as the FFM. Early research by Allport and Odbert laid the foundation for what would become the Five Factor Model by identifying consistent categories of personality traits in the spoken and written language of a population. Using this early work as a starting point, researchers began to propose generalized models of personality.
As a follow-up to this research, Tupes and Cristal conducted a landmark study that identified five relatively strong and recurrent factors (i.e., extraversion, agreeableness, conscientiousness, emotional stability, and openness) across several samples. The factors Tupes and Cristal proposed would eventually become the FFM as it is known today following replication by numerous other studies. These factors represent traits at the broadest level of abstraction, and are meant to summarize more distinct and specific dimensions. As the model has become accepted by researchers, the focus has shifted to the utility of it. Modern meta-analyses on the FFM have found consistent links to outcomes of interest such as job performance.
To ensure that the results are objective, remove unintended bias,
and reduce subconscious impressions, a self-reported approach is utilized
in the WonScore platform.
When more is more
*jargony term alert*
In our offices, we talk a lot about “incremental predictive validity” - you know, pretty standard water cooler stuff. Anyway, we’re talking about improving the accuracy of our predictive data by adding new assessments. Translation: We would never think about adding anything to a hiring process that doesn’t provide value. Incremental predictive validity is a critical component when determining which constructs to use.
The benefits are clear: more predictive validity = improved ability to select applicants who meet all the various requirements for high job performance. Large-scale studies have indicated that - when used together - cognitive, personality, and motivation demonstrate incremental predictive validity. This combination provides a holistic, accurate view of candidates.