Psychological assessments make talent measurable. They help organizations to select more objectively and to map development potential reliably. This way, you prevent mismatches, increase sustainable employability, and make choices that contribute to growth and agility for people and organizations.
We help HR leaders gain strategic insight into culture, skills, and behavior. Using psychology and data, we bring growth opportunities, skills gaps, and development needs into sharp focus. For individuals, teams, departments, and organizations. This enables you to build on development, agility, leadership, and future-proof growth.
Want to know who has the potential to contribute to growth? Starcheck’s assessment tools give HR professionals reliable, data-driven insights into talent, team dynamics, and development potential. Substantiate selection and development decisions with psychological precision. Read more about our tools.
Working in teams is becoming increasingly important. The added value of a team is that it collectively outperforms the sum of its members. But how do you predict that? Our insights into team chemistry predict a team’s success and performance. This reduces interventions, fixes after the fact, and increases team performance.
We live in a world where work is no longer defined by job function, the workplace is no longer a specific place, and many colleagues are no longer traditional employees. With the advent of AI in the workplace, the future of work has never been more uncertain. Organizations are rethinking everything from talent strategies to the role of human resources to rethinking roles, structures, and functions in a technology-driven world. Work performance today is no guarantee for tomorrow. To take people with us into the future of work, we will need to delve more deeply into who they are.
Psychology and data help predict behavior. So you know in advance who will be successful in a role or team. This prevents disappointment, underpins selection and development decisions, and provides a grip on future performance, without assumptions.
What skills does your organization need to remain agile, innovative, and competitive? Our insights make growth paths visible at the individual, team, and organizational levels. With psychological insights and data, you can focus on acceleration.
Teams with high collective intelligence solve problems faster and perform better. We help you build and strengthen those teams. With our unique tools, you make collective intelligence concrete and measurable. So that the collective can grow and accelerate.
Does an assessment make sense? As a hiring manager, you probably ask that question not out of enthusiasm but out of doubt. And that doubt, in that, you are not alone. Finally, an assessment is a snapshot in time. Someone
Less turnover, better skill-fitt, and more effective collaboration: benefits that make the ROI of an assessment very short. Our ROI calculator is based on the Brogden-Cronbach-Gleser (BCG) model. Learn more about the ROI of an assessment.
Collective intelligence enables teams to make better decisions together than individuals alone. It promotes innovation, flexibility, and problem-solving ability. Organizations that harness it remain agile and consistently perform better in a dynamic marketplace.
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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