Not recognising yourself in your scores?

It can feel strange to complete a test that puts numbers on your traits and behaviours, and to see results that don’t match how you see yourself. That’s very understandable. That's why we have written this article, to explain a bit more about why, for example, you can trust that our games measure what they measure among other important points surrounding this topic. Hopefully, this article will clear things up a bit for you.

When designing a new tool to measure a trait or ability that has no pre-existing valid means of measurement, there are some statistical methods that can be used to test the data produced by it. The goal of these tests is to detect patterns that can indicate the validity of the tool. When another valid measurement tool already exists, the validity of a new tool can be established by comparing the results of the new tool to those of the pre-existing one. If both instruments measure the same underlying trait, the response patterns of people using them both should be similar. This then supports the validity of the new tool. During development, our games are compared with established tests of the same abilities.

Our games fall into three groups: cognitive games, behavioural preferences and behavioural skills.

Our cognitive games are a combination of cognitive ability tests. Each game focuses on a specific ability, such as cognitive flexibility, and results range from lower to higher. Behavioural preferences describe which of two approaches you tend to prefer; there is no right or wrong answer. Our behavioural skills games look at skills that help people work effectively with others, such as communication, teamwork and accountability (ranging from fair to excellent).

The abilities and preferences measured by our cognitive and behavioural games develop as you grow up, shaped by your experiences and environment. Research suggests that by early adulthood they tend to settle into a relatively stable level (Hartshorne & Germine, 2015) , and that people’s standing relative to one another stays fairly consistent over many years (Deary et al., 2013). They can still develop later in life, but usually gradually rather than drastically. In practice, if you play the same game again one year later, your result will usually be broadly similar.

This doesn’t mean you haven’t developed techniques to help with things that don’t come naturally to you. Our games are designed to focus on the underlying ability or preference rather than on learned techniques, so that results depend less on prior coaching or training. That is not a judgement on the value of those techniques: in everyday work, the strategies you have developed can be a real strength.

Take prioritising as an example. The Ferry game looks at prioritising, but a well-known technique such as “eat the frog” (doing your hardest task first) doesn’t apply within the game. So you might score lower on Ferry even though you prioritise well in daily life using strategies that work for you.

For hiring managers and recruiters, this makes a useful interview topic. Asking a candidate about their results gives them the chance to explain the techniques they use, for example to handle prioritising. A result that raises questions could lead to an interesting conversation.

Our behavioural skills games work differently. The Team Tactics games are situational judgement tests that reflect skills you have developed over time and can keep developing. A “fair” result, for example on ownership, points to a possible area for development. Your own reflection on your results can be valuable in conversations with hiring managers and recruiters.

It can feel odd to see something you believe you’re good at expressed as a score. Your results are not a measure of your worth, and they shouldn’t make you feel you aren’t good enough. Everyone has relative strengths and areas that come less naturally. That's why every candidate or team member will receive a link to an article with tips and tricks around strategies that you can apply to your day-to-day as well as your professional life.

Research shows that cognitive ability tests are among the useful predictors of job performance, though no single measure predicts it perfectly (Sackett et al., 2022). The scores describe likelihoods for groups of people with similar results, not certainties about any one person. For example, a higher result on the game that measures cognitive flexibility suggests a person is more likely than average to adapt readily when rules or situations change. It doesn’t tell us how that person will behave in every situation.

Different work environments challenge you in different ways. If a result is lower than you expected, it may be that your current role doesn’t draw much on that ability or preference, so it hasn’t stood out. In a role that relies on it more, you might notice it more.

If your results don’t match how you see yourself, there are two separate questions worth keeping apart. The first is how accurately any of us can judge our own abilities. The second is how well a particular test measures them. Both matter, and neither answers the other.

On the first question, research shows that self-knowledge is imperfect, for traits as well as abilities (Karpen, 2018). One well-documented reason is the above-average effect: people often lack the information needed to compare themselves with others, and overlook information they do have (Dunning et al., 2004). As a result, many people rate themselves above their peers, and correlations between self-ratings and actual performance tend to be weak (Karpen, 2018).

Game-based assessments take a different approach. Instead of asking how you see yourself, they look at how you perform on a task. That makes them less dependent on self-perception, and harder to steer towards the answer you think an employer wants. Like any measure, they also have limits, which is why we recommend using results alongside other information, such as structured interviews, rather than on their own.

We hope this helps explain why your results might not match how you see yourself, and how to interpret them.

Interested in the science behind our games? Find out more here.

References

Deary, I. J., Pattie, A., & Starr, J. M. (2013). The stability of intelligence from age 11 to age 90 years: The Lothian Birth Cohort of 1921. Psychological Science, 24(12), 2361–2368. https://doi.org/10.1177/0956797613486487

Dunning, D., Heath, C., & Suls, J. M. (2004). Flawed self-assessment: Implications for health, education, and the workplace. Psychological Science in the Public Interest, 5(3), 69–106. https://doi.org/10.1111/j.1529-1006.2004.00018.x

Hartshorne, J. K., & Germine, L. T. (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychological Science, 26(4), 433–443. https://doi.org/10.1177/0956797614567339

Karpen, S. C. (2018). The social psychology of biased self-assessment. American Journal of Pharmaceutical Education, 82(5), 6299. https://doi.org/10.5688/ajpe6299

Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2021). Revisiting meta-analytic estimates of validity in personnel selection: Addressing systematic overcorrection for restriction of range. Journal of Applied Psychology, 107(11), 2040–2068. https://doi.org/10.1037/apl0000994