Why use psychometrics?
Psychometrics are often used in selection processes to reduce human bias and provide an objective, standardised prediction of a candidate’s performance in role. They assess a wide range of abilities, personality traits, attitudes, values and behaviour.
Practitioners use Psychometrics to quantify traits and competencies that are relevant for a job, supplementing existing knowledge about educational attainment and work experience.
There is no shortage of test providers all claiming their strengths. Some personality tests measure ‘traits’ on different continuums (e.g. extroversion – introversion). Others measure ‘types’ in different categories (e.g. thinking vs feeling). Ability tests measure what someone is currently capable of doing, while aptitude tests measure what someone will be capable of doing in the future, in other words, their potential.
Business leaders and HR / Talent Acquisition should work with a qualified, accredited Organisational or Business Psychologist who will choose, administer, and analyse the right test. They will consider:
Reliable tests produce dependable, repeatable, and consistent information about people. Will I get the same result if I take the test under different conditions or on different occasions?
A valid test actually measures what it says it measures. It should reflect the actual tasks of the job and be obvious to test-takers what it is trying to measure. It also needs to accurately measure underlying traits associated with the job and correlate with measures of actual job performance. For example, a test used to predict technical proficiency is not valid for predicting leadership or communication skills. You will disqualify good candidates if you are evaluating them on criteria that are not relevant for the role. Crucially, a test cannot be valid if it is also unreliable.
Tests are developed and validated using larger samples called ‘norm groups’. The demographic characteristics of norm groups will dictate how appropriate a given test is for your candidate, as their score will be compared to the norm group. It would be less appropriate to compare the capabilities of a Digital Analytics Director with a norm group of 100 UK residents than a group of 100 UK business leaders. This carries implications for diversity, for example, if a certain gender or ethnicity is not sufficiently represented in the norm group.
Adverse impact can occur when using psychometrics because different racial and demographic groups may score differently on tests. If testing is the sole means of selection, then this risks a selection bias, as the test may positively discriminate for certain groups.
Sabotage / Distortion
All tests can be subject to sabotage or distortion due to assessor unreliability, social desirability effects, superficial or dishonest responses as well as assessor prejudices. We may like to think psychometrics are the objective option, but their administration and completion are also subject to human biases and error.
Can psychometrics support diversity in selection?
Due to adverse impact, we must accept there is risk associated with psychometrics when it comes to promoting diversity and equality in selection processes. But if we are aware of the potential to introduce bias, we can ask good questions about protected characteristics that support diversity. E.g. What are the demographics of the norm group? How valid is the test across different demographics and protected characteristics?
By testing for aptitudes and abilities rather than current experience or attainment, we create objective selection data that helps us re-examine our assumptions. Stereotypes to watch out for include, female candidates not being as analytical, or younger candidates not making strong leaders. In this way, we avoid rejecting high potential talent in our selection, and unnecessarily reducing our talent pools. For a specific technical skill, we may not always need to hire from a particular competitor company, if they themselves are struggling with their diversity.
If psychometrics are used in the right way, we can cast a broader net, gain a representative selection early in our pipeline, and create diverse pools of talent.