Recruitment mistakes remain a reality and despite the proliferation of selection methods its success rate stands at only 54%. That means a recruiter makes one bad decision for every two recruitments.
According to a study by the Society for Human Resources Management (SHRM), the cost of selecting the wrong person can run up to five times of a bad hire’s annual salary. And higher the position and longer the person remains in that position, the more it will cost to replace them. It is also known that in 89% of the cases, the failures are explained by behavioral factors and not by a lack of technical know-how.1
Psychometric assessments have already proven their objectivity and reliability in various HR decision-making processes. But their current way of use proves lacking against the evolving organization HR challenges, like the emergence of new skills and occupations, perennial dearth of talent, and more than ever diverse working environments.
Better target potentials through multi-criteria assessment approach
Human behavior is incredibly complex with each person having a unique set of characteristics. So, trying to predict how a person is going to behave and perform at work is not an easy task. That is why making a good recruitment decision is not anymore based on “gut feeling” or “liking the candidate”; it is about combining multiple data for a more accurate and predictive analysis of a candidate’s potential.
Due to their construction and scientific validity, psychometric assessment matches well the "big data" approach and provide accurate and unbiased insight into people’s behavior and potential.
However, it is well known that psychometrics is not a crystal ball. Psychometric tests have surely shown to have a predictive value in relation to job competencies and overall performance, but their success rate depends significantly on the how well the assessments are used.
Recruitment decision cannot be based solely on cognitive skills evaluation or just a personality test alone. As research has shown that the predictive ability to use a single assessment tool is often moderate. However, when multiple assessments are combined, their predictive analysis enhanced significantly.
This is precisely what Harvard Business School study shows2, the combined use of personality and intelligence tests increases recruitment efficiency by 15% compared to a non-test recruitment process.
These significant findings corroborate the Schmidt & Hunter study, which highlighted the predictive values of several selection methods including intelligence tests and integrity assessment. Thus the use of intelligence tests in addition to the structured interview allows to increase the success rate by 12% compared to maintenance alone. More generally, this study shows that the combination of selection tools, when they are relevant, is always more predictive.
“In terms of recruitment algorithms do better than intuition.”
Since the results from different psychometric tests complement each other, they can ensure a more accurate assessment. For example, one can combine a personality test, a sales aptitude test with an emotional intelligence test for a more precise and comprehensive evaluation, when it comes to hiring for a sales position.
The only limitation with this approach is that the assessors need to juggle report results of different assessments to obtain one complete analysis of the candidate’s profile.
It relies on a powerful algorithm to analyze the results of multiple assessments in a single competency framework and job referential.
TALENT MAP offers decision-makers the power to match a candidate profile with 36 competencies and 138 occupations, with just one click. Fully customizable, the tool can adjust to your own criteria and you can define the competency estimated according to your expectations.
The multi-criteria approach redefines the use of psychometric assessments and will significantly increase the success of your recruitments.
In summary, psychometric tests are excellent tools for decision making in recruitment, even though there is no quick fix. This predictive accuracy could be further enhanced by an optimized use of psychometrics, notably through the promising multi-criteria approach.