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Today’s topic

Debunking common misconceptions about psychometric assessments in recruitment

Introduction 

Psychometric assessments are a powerful tool that deliver significant business value by improving the accuracy and fairness of recruitment decisions. Despite their scientific foundation and proven utility, these tools sometimes face skepticism, particularly from those unfamiliar with the research behind them. This article addresses three common misconceptions about psychometric assessments, especially personality tests, and explains why these views are misguided. By understanding the true value of these assessments and integrating them effectively into the recruitment process, organisations can make more informed, data-driven hiring decisions that benefit both the company and the candidates.

Misconception 1: Psychometric assessments lack validity

A frequent critique of psychometric assessments, particularly personality tests, is that they do not accurately predict job performance. To some extent, that is true. There are tools on the market that are not suitable to use in recruitment. However, the Five-Factor Model (FFM), a widely recognised and scientifically validated tool, offers strong predictive validity.

Predictive validity refers to how well an assessment can forecast future job performance, typically measured by a coefficient between -1 and +1. A value of 0 indicates that the results of the assessment are in no way connected to the outcome, while a value of +/- 1 indicates a perfect relationship on the other hand. To put this into context, within the larger field of psychology, values of +/- .5 are highly rare. It is generally very difficult to look at one aspect of a human being and predict how they will behave in some other way in the future. People are very complex.
The validity of recruitment methods, in particular, have been investigated empirically across a multitude of samples and contexts.

Consistently, these studies have found evidence supporting the use of FFM assessments for recruitment purposes (Sackett et al. 2021; Barrick et al. 2001, Judge et al 2013, Hunter & Schmidt, 1998). A recent meta-analysis conducted by Sackett and colleagues in 2021 concluded that personality, as measured on factor level, has a predictive validity to overall job performance up to .31. For perspective, Sackett and colleagues (2021) also looked at a number of other assessment methods. Comparing for example personality to the number of years of experience a candidate has as a predictor, they report a 1.7x to 3.5x improvement in validity, depending on the personality trait evaluated.

Similarly, Judge and colleagues (2013), when analysing data from a combined sample of 400 000 people also concluded strong support for the predictive power of personality assessments.  The authors also report that when measuring the underlying facets instead of the overall factor, the improvements significantly improved, yielding coefficients ranging from .19 to .41. 

All this evidence shows a strong link between personality and job performance on a group level. There will always be individual differences, but since most organisations hire several individuals, these tendencies are highly likely to generate improved accuracy over time. 

While personality assessments provide substantial predictive validity, their effectiveness is maximised when integrated with other recruitment methods. For instance, structured interviews and cognitive tests complement personality assessments by offering insights into a candidate’s practical skills and situational behaviour. This integrated approach ensures that hiring decisions are informed by a comprehensive understanding of each candidate, thereby reducing the risk of mismatches and enhancing overall predictive accuracy.

Misconception 2: Traditional recruitment methods are more efficient

Many believe that traditional recruitment methods, such as CV screening, are more efficient than psychometric assessments. However, this assumption is increasingly challenged by the inefficiencies and biases inherent in traditional methods. A single job posting can attract hundreds of applications, and manually sifting through CVs is not only time-consuming but also prone to unconscious bias.

Research shows that biases, such as those based on a candidate’s name or background, can significantly skew recruitment outcomes. Moreover, traditional CVs do not strongly correlate with job performance, meaning they often fail to provide an accurate picture of a candidate’s potential.

In contrast, psychometric assessments offer a more structured and less biased approach. By focusing on scientifically validated measures of personality, recruiters can make more informed decisions, saving time and reducing the influence of unconscious biases. This approach leads to more accurate hiring decisions, ensuring that candidates are evaluated on their potential rather than their resumes alone. Psychometric assessments streamline the recruitment process by giving recruiters more data points to identify candidates who align with the role’s requirements, thereby reducing the time spent on initial screenings, increasing quality of hire and removing unconscious bias.

By standardising evaluation criteria, these assessments minimise variability and subjectivity often seen in traditional methods, such as unstructured interviews or manual CV reviews. This leads to a more consistent and fair selection process, enhancing the overall efficiency and effectiveness of recruitment.

Misconception 3: Candidates dislike psychometric assessments

Another common misconception is that candidates find psychometric assessments off-putting. On the contrary, when the purpose and benefits of these tools are clearly communicated, candidates often appreciate the fairness and objectivity they bring to the recruitment process.

Psychometric assessments can level the playing field, allowing candidates to demonstrate their potential beyond traditional markers like education or experience. This ensures a more equitable evaluation process and can improve the candidate experience by fostering a sense of fairness and transparency.

Candidate-expereince-using-Alva-Labs

Candidates increasingly expect transparency in recruitment. By explaining how psychometric assessments contribute to a fairer selection process, companies can enhance their employer brand and improve candidate satisfaction. When candidates understand that these tools are based on science and are used to ensure that the best fit for the job is selected, they are more likely to engage positively with the process.

To further improve candidate experience, organisations should actively communicate the role of psychometric assessments in the recruitment process. Providing candidates with feedback based on their assessment results can help them understand their strengths and areas for development, even if they are not selected for the role. This transparency not only enhances the candidate’s perception of fairness but also reinforces the organisation’s commitment to scientific and equitable hiring practices. Alva offers built-in immediate feedback by sending candidates their test results instantly upon completion of the tests.

Balanced perspective

While psychometric assessments offer significant advantages, it is essential to recognise that they need to be based on evidence-based methods such as the Five Factor model and even then they are most effective when used as part of a broader recruitment strategy. By combining personality assessments with other tools like structured interviews, cognitive tests, and practical exercises, organisations can create a holistic recruitment process that not only predicts job performance accurately but also enhances the overall candidate experience. This balanced approach ensures that psychometric assessments are not used in isolation but as a critical component of a comprehensive hiring strategy.

Why choose Alva Labs for psychometric assessments?

At Alva, we take great pride in the scientific rigour behind our assessments. Certified by DNV, our tools are built on the latest research to meet the high expectations of our clients. We are committed to ensuring that our assessments are not only valid and reliable but also a valuable part of a fair and efficient recruitment process.

Conclusion

Psychometric assessments, when grounded in science and implemented correctly, are invaluable tools for improving recruitment processes. Misconceptions about their validity and effectiveness often stem from a lack of understanding of the extensive research supporting their use. By choosing a provider like Alva, which is committed to scientific excellence, organizations can confidently integrate psychometric assessments into their hiring strategies, ensuring they are making informed and fair decisions.

In an era where data-driven decision-making is crucial, psychometric assessments stand out as a scientifically supported method to enhance recruitment outcomes. By addressing common misconceptions and understanding the true potential of these tools, organizations can turn skeptics into advocates, ensuring that every hire is based on a comprehensive and fair evaluation of each candidate's potential.

Deep dives

Enroll in our free training at Alva Academy, where Anna Brodin, Licensed Psychologist and Senior Customer Success Manager, provides an Introduction to psychometric assessments.

Alva Labs technical manual

References

Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and performance at the beginning of the new millennium: What do we know and where do we go next? International Journal of Selection and Assessment, 9(1‐2), 9-30.

Judge, T. A., Rodell, J. B., Klinger, R. L., Simon, L. S., & Crawford, E. R. (2013). Hierarchical representations of the five-factor model of personality in predicting job performance: Integrating three organising frameworks with two theoretical perspectives. Journal of Applied Psychology, 98(6), 875–925.

Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2021). Revisiting the design of selection systems in light of new findings regarding the validity of widely used predictors. Industrial and Organisational Psychology, 16(3), 283–300.