Effectively using recruitment assessments requires a solid understanding of the scientific principles behind them. Without this foundation, organizations risk using assessments that say little about actual job performance or, worse, contribute to biased or discriminatory outcomes. Two core concepts are often misunderstood in this context: validity and reliability.
These terms are frequently used interchangeably, even though they describe fundamentally different qualities. A skill test can be technically well designed yet provide little insight into real-world performance. Conversely, a test may aim to measure relevant skills but fail to do so consistently. This article explains what validity and reliability mean, how they relate to one another, and why both are essential for high-quality selection decisions.
Validity: are you measuring what you intend to measure?
Validity refers to the extent to which an assessment actually measures what it is designed to measure. There are several forms of validity that are particularly relevant in recruitment.
Predictive validity describes how well assessment scores predict future job performance. This is the most important form of validity in a hiring context. A test with high predictive validity means that candidates who score highly tend to perform better on the job than those who score lower.
Content validity refers to how well the content of an assessment reflects the competencies required for the role. A programming test for developers, for example, should include relevant programming languages and realistic coding challenges.
Construct validity concerns whether the assessment truly measures the underlying concept it claims to measure. An emotional intelligence test, for instance, should measure EQ itself rather than primarily capturing social desirability or self-presentation.
Reliability: consistent measurement
Reliability refers to the consistency of measurement. A reliable assessment produces similar results when administered repeatedly under comparable conditions. This is essential for fair comparison between candidates.
Several factors influence reliability, including test length, clarity of instructions, and the degree to which test administration is standardized. In general, longer tests tend to be more reliable, provided they are well constructed.
What is the core difference between validity and reliability?
The difference between validity and reliability lies in what is being evaluated. Reliability asks whether a skill test measures consistently. Does the same candidate receive a similar score under similar conditions, and do different evaluators arrive at the same result? Validity asks whether the skill test measures the right thing. Does it assess skills that are actually related to success in the role?
A practical rule of thumb is:
A test can be reliable without being valid, but it cannot be valid without being reliable.
Reliability alone is not sufficient. A test can be technically robust with stable scoring and clear evaluation rules, yet still offer little value if the measured skills are barely relevant to the job. This creates an illusion of objectivity. The numbers appear convincing, but they say little about real suitability or performance.
Validity without reliability is also problematic. A test may be conceptually well aligned with the role, but its execution introduces noise. Examples include open-ended questions without clear scoring criteria, large differences between evaluators, or results that depend heavily on subjective interpretation. In such cases, relevant behavior is touched upon, but not measured in a reproducible way, making decisions harder to explain and defend.
How validity and reliability come together at Selection Lab
At Selection Lab, reliability and validity are combined within a single standardized selection flow. Skill tests are not used in isolation, but selected and combined based on clear quality criteria. The guiding principle is straightforward: tests must be both content-relevant for the role and consistently administered and scored.
Validity: measuring what predicts success in the role
Selection Lab primarily works with scientifically validated assessments from external providers that meet strict quality standards. Only instruments with proven psychometric foundations and relevant norm groups are included on the platform. Examples include Aivy, Bright, UCAT, and Logiks by Talogy.
For personality, motivation, and culture, validity is grounded in established models such as the Big Five Aspect Scales, Schwartz’s value theory, and the Groysberg culture model. For hard skills, the focus is on task-based tests with increasing levels of difficulty to ensure that relevant job competencies are measured.
In addition, Selection Lab combines multiple valid components, such as cognitive ability, personality, and hard skills, into a single match score. Weightings can be adjusted per role. Internal use cases show a clear relationship between match scores and hiring decisions, indicating predictive value.
Reliability: consistent measurement under equal conditions
In addition to content validity, reliability at Selection Lab is ensured through standardized administration and scoring. Candidates complete short, clearly structured modules with fixed instructions and practice rounds. Scoring and norming are fully automated, minimizing interpretation differences.
Results are compared against relevant norm groups and expressed in standardized scores, for example on a 0 to 100 scale. These norm groups are updated periodically to keep comparisons current and representative. For online testing, optional proctoring can be applied using screen, webcam, and audio monitoring, further increasing reliability in high-stakes or high-risk selection processes.
Operational safeguards are also in place to reduce measurement error, including one-time test links, attention checks to prevent careless responses, and direct server-to-server result transmission. Together, these measures ensure consistent and dependable outcomes.
Reliability makes scores usable, validity makes them valuable
Skill tests only deliver value when they are both reliable and valid. Reliability ensures fair and consistent measurement, while validity determines whether that measurement actually says something meaningful about success in the role. One without the other leads to false certainty.
Organizations that use skill tests strategically invest not only in tooling, but also in scientific grounding, standardization, and continuous evaluation. Only then do skill tests become what they should be: a solid foundation for better, fairer, and more explainable hiring decisions.
