Assessment grounded in evidence, not assumptions
The best predictor of job performance is how someone actually thinks, decides, and acts in realistic situations. Every Neuroworx assessment is built on that principle.
Most hiring methods measure the wrong things
Traditional hiring relies on proxies. CVs reward tenure, not ability. Interviews reward confidence, not competence. Personality tests capture preferences, not behaviour.
These methods feel familiar, but decades of research show they are weak predictors of how someone will actually perform in a role. The result is inconsistent hiring decisions, costly mis-hires, and teams built on gut feel rather than evidence.
Three methods, one complete picture
Single-method tests only capture part of the picture. Neuroworx combines three complementary assessment types, each measuring a different dimension of performance.
Cognitive and Technical Reasoning
Logical reasoning, numerical analysis, pattern recognition, and domain knowledge. Consistently one of the strongest predictors of job performance across industries.
Behavioural Judgement
Decision-making, prioritisation, judgement under pressure, and interpersonal awareness. Based on Situational Judgement Test methodology with strong validity for predicting real-world performance.
Practical Execution
Applied thinking, communication clarity, strategic reasoning, and task execution. Work performance is ultimately about what someone produces, not what they recognise.
*Published meta-analytic validity for the method class: cognitive ability tests 0.51 and work sample tests 0.54 (Schmidt & Hunter, 1998); situational judgement tests 0.34 (McDaniel et al., 2001). These describe the methods in the research literature, not measurements of Neuroworx assessments. Our own measured evidence is set out below.
We measure behaviour, not self-description
Traditional personality tests rely on self-reporting and abstract questions. Candidates describe how they think they behave, not how they actually respond under pressure. Social desirability bias makes these results unreliable.
Neuroworx replaces this with dynamic scenario-based assessment. Instead of asking "Are you a good communicator?", we present a realistic workplace situation with multiple plausible responses and genuine trade-offs between priorities.
This approach is grounded in behavioural consistency theory and contextual judgement research. It reduces faking, forces real trade-off decisions like actual jobs do, and measures applied judgement rather than stated preference.
"On a scale of 1 to 5, how well do you handle conflict?"
"A key stakeholder disagrees with your project timeline and is escalating to your manager. What do you do next?"
Four plausible options. Real trade-offs. No obvious answer.
Every score maps to what the role actually needs
Most assessments give a single score or vague category. Neuroworx breaks every role down into 6 to 10 core skills, each clearly defined, independently measured, and weighted by importance to the role.
Weightings are based on job analysis and the performance drivers of the role. A Growth Marketing role weights analytical thinking higher than stakeholder management. A Customer Service Manager weights the reverse.
The result is a composite NX Score that reflects genuine fit for role, not generic ability. Hiring managers see exactly where a candidate is strong, where they are weak, and how that maps to what the job demands.
Built on proven assessment science
Not all assessment methods are equal. Meta-analytic research spanning decades shows that some methods are far stronger predictors of job performance than others.
Neuroworx uses cognitive ability tests, situational judgement tests, and work sample tasks. These are among the highest-validity methods available. Research consistently shows that combining multiple assessment methods significantly increases predictive accuracy.
Neuroworx uses these methods. We have not yet run a predictive validity study of our own assessments against job performance, so the figures alongside describe the methods, not our product. That study is planned, with independent review.
Schmidt & Hunter (1998) meta-analysis; situational judgement from McDaniel et al. (2001). Higher = stronger published predictor of job performance. Method-class estimates, not Neuroworx product measurements.
What we have measured, and what we have not yet
Published research describes the methods. This is what we have measured on Neuroworx assessments themselves.
Test reliability
In July 2026 we ran an internal-consistency analysis (KR-20) across live candidate data. 23 assessments met the threshold of at least 100 completed attempts and produced an estimate, with values from 0.34 to 0.97. Each estimate carries a 95% confidence interval, and the analysis re-runs against new attempts.
Scoring provenance
Every score is recorded with the version of the scoring code that produced it, so a result can be traced and re-examined later rather than silently overwritten. Recording model, prompt and rubric versions alongside it is in progress.
Predictive validity
We have not yet run a study relating Neuroworx scores to later job performance. It is planned with independent psychometric review, and we will publish sample sizes and limitations alongside any result.
Adverse impact analysis
Our fairness approach is recorded in our DPIA. Routine analysis of outcomes across protected groups is planned and is not yet an automated control.
Reducing bias at every stage
Poorly designed assessments can amplify bias. Neuroworx is built to reduce it.
Standardised evaluation
Every candidate faces the same scenarios, with structured scoring and consistent weighting. No interviewer variation, no inconsistent benchmarks.
Removing traditional signals
No CV screening bias, no pedigree bias, no "confidence in interview" bias. Candidates are evaluated on what they can do, not where they come from.
Adverse impact analysis
Our fairness approach, including reasonable adjustments and the rule that an assessment is never the sole basis for a decision, is recorded in our DPIA. Routine adverse impact analysis across protected groups is planned; it is not yet an automated control.
Face validity
Candidates understand why they are being assessed. Scenarios are transparent and directly relevant to the role, building trust in the process.
Accessibility
Reasonable adjustments are available for candidates with disabilities. Accessibility barriers never confound assessment scores.
GDPR compliance
Assessment data is processed lawfully with clear consent. Candidates can access or delete their data at any time.
Want to dig deeper?
Talk to our assessment science team
We are happy to walk you through our validation methodology and discuss how we would approach your specific roles.
