The labor market remains tight, so you want speed and quality without putting extra pressure on your selection process. With a short self-assessment (10-15 minutes), you transfer control to the candidate: based on psychological data, he/she assesses his/her fit with the function and organization.
You don’t have to give an early go/no-go; candidates make their own conscious decision to continue or drop out, so your recruitment funnel clears itself, and the quality of inflows increases.
Here’s how it works in practice: you clearly communicate which behavioral, drive, or cognitive skills the position requires. Candidates complete a compact, work-relevant measurement (e.g., a short personality or motivational questionnaire or cognitive test).
Immediately afterwards, they receive clear feedback, including a person-function match estimate and advice on what this means for the job. Based on this, they decide for themselves: to continue applying or not.
A self-assessment allows a candidate to judge for themselves whether the job and organization offered suit them. You describe in a realistic way what you, as an organization, expect from a future employee. This can be done with text, but video, a self-test, or a game can also be used.
Then, a candidate can assess whether the position and organization suit them. This is a strong self-selection mechanism and significantly improves the quality of your recruitment funnel. The self-assessment is a powerful and often underestimated tool.
Interview top employees and describe 2-3 critical incidents
Map desired and undesired response patterns
(Optional)
Develop or enrich personas
Translate content into form, e.g. a game or a test (SJT)
Launch self-assessment and measure conversion
This results in self-selection: fewer mismatches, more convinced matches. Sometimes the volume actually increases because candidates discover that they are a good fit. Realistic information and perceived fit through self-selection increase candidates’ appeal of your proposition, acceptance of the subsequent selection process, and reduce early dropout.
Also essential is the fairness that candidates experience. They stay in control and understand what is being measured and why. That increases acceptance and makes the process transparent.
Privacy-wise, it’s simple: results belong to the candidate; sharing with the organization only happens intentionally and only when someone chooses to proceed.
The effect is: higher match quality, shorter turnaround time, and less interview waste, while your employer brand gains in professionalism and clarity. The candidate decides, and your organization benefits from a self-selecting and fairer funnel.
Once you have identified these situations and the desired and undesired reaction patterns using the Critical Incident Method, you can use them to clearly communicate your proposition to the job market. You can also use the desired and undesired reaction patterns to develop a persona. Finally, you can use critical incidents to create a Situational Judgement Test (SJT).
In a Situational Judgement Test (SJT), you describe the situation and ask what kind of behavior a candidate would like to demonstrate. This allows the candidate to discover for himself whether his reaction pattern fits the job and the organization. In this way, candidates themselves can make a clear assessment of their chances of a successful performance and fit with the organization.
If your organization wants to deploy a self-assessment, we will help walk you through all the steps. From identifying critical incidents, naming response patterns, to developing personas, and the self-assessment itself.
We write content for your career website or provide self-assessments to gamify them.
Discuss your case with an experienced psychologist NIP, and discover how a self-assessment will improve your TA activities.
This fact sheet provides an overview of the most commonly used (psychological) selection methods, both classical and modern. The figures are based on meta-analyses and dominant scientific literature.
| Method | Predictive validity (r) | Typical reliability |
|---|---|---|
| Cognitive ability (GMA test) | .51 | High (.85-.95) |
| Work test | .54 | High (inter-rater ≥.70) |
| Structured interview | .51 | Medium-high (.60-.75) |
| Unstructured interview | .18-.38 | Low-medium (.40-.55) |
| Integrity test | .41 | High (α ≥.80) |
| Conscientiousness (Big Five) | .31 | Medium-high (α ~.75-.85) |
| Job knowledge test | .48 | High (≥.80) |
| Years of service | .18 | Not applicable |
| Video/asynchronous interview (incl. AI) | .30-.40 | Good at structuring; algorithmically variable |
| Machine learning / algorithmic models | .20-.50 | Depends on dataset; generalizability limited |
| Serious games / game-based work samples | .35-.50 | High on objective metrics |
| Social media screening | .00-.20 | Low and variable |
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