PRODICTA
The Science

Scientific Foundations of PRODICTA

From prediction to performance

Traditional hiring methods focus on measuring traits such as personality, cognitive ability, and behavioural preferences. These approaches are widely used and supported by research. But they answer a limited question: What is this person like?

PRODICTA is built to answer a more important one: How will this person actually perform in the job?

What PRODICTA is not

PRODICTA is not a personality test. We do not ask candidates to rate themselves, agree with statements, or describe their preferences. We do not measure traits, types, or psychological profiles.

What PRODICTA is

PRODICTA places candidates into realistic Day 1 scenarios and observes how they actually perform. The behavioural data we analyse is what candidates do, decide, write, and prioritise during real work simulations, not what they say about themselves.

This is the difference between asking ‘are you good under pressure?’ and watching how someone actually responds when their inbox is overflowing, a deadline is moving, and a stakeholder is pushing back.

1

Work sample simulations

PRODICTA replaces CV screening and theoretical assessment with realistic job simulations.

The science
Work sample tests, where candidates perform real job tasks, are among the most predictive indicators of job performance.
Schmidt and Hunter (1998; updated 2016)

In comparison:

  • Years of experience has low predictive value, around 0.18
  • Education level has low predictive value, around 0.10
What this means

Traditional hiring relies on proxies:

  • CVs
  • Qualifications
  • Self-reported answers

Work simulations measure something fundamentally different: Observed performance in job-relevant situations.

The PRODICTA approach

PRODICTA places candidates into Day 1 scenarios where they must:

  • Prioritise tasks
  • Make decisions under pressure
  • Respond to real constraints
  • Communicate in context

Not what they say they would do, but what they actually do.

2

Behaviour depends on context

Research shows behaviour is shaped by the situation.

The science
Performance is influenced as much by context as by personality.
Mischel (1968)

The same individual may behave differently depending on:

  • Pressure
  • Competing priorities
  • Stakeholder expectations
  • Organisational environment
What this means

Assessing candidates outside of real context limits accuracy. To understand performance, behaviour must be observed in realistic conditions.

3

From traits to behaviour

Research shows that while personality traits describe general tendencies, observed behaviour in real situations provides a stronger and more reliable signal for predictive analysis.

Personality-performance research demonstrates moderate correlations between traits and job outcomes (Barrick and Mount, 1991), while behavioural science shows that performance is highly dependent on situational context (Mischel, 1968).

Meta-analyses of hiring methods further show that approaches based on real job tasks, such as work sample tests, are among the most predictive indicators of performance (Schmidt and Hunter, 1998; 2016).

What this means

Personality provides useful insight, but it does not capture how someone behaves when it matters. Observed behaviour in context provides a stronger, more reliable signal.

4

Assessment centre methodology

PRODICTA reflects principles used in assessment centres, a long-established approach in high-stakes hiring.

The science

Assessment centres evaluate candidates through:

  • Simulations
  • Role-based exercises
  • Real-world tasks
Research shows these methods have strong predictive validity and are widely trusted for evaluating job performance.
Thornton and Rupp (2006)
What this means

Assessment centres are effective but traditionally:

  • Expensive
  • Time-intensive
  • Difficult to scale
The PRODICTA approach

PRODICTA brings the same principles into a scalable, digital format:

  • On-demand simulations
  • Role-specific scenarios
  • Consistent evaluation
5

Experiential performance

Research in experiential learning shows that performance is best understood through action.

Kolb (1984)

What this means

People demonstrate capability most accurately when:

  • Actively performing tasks
  • Making decisions in context
The PRODICTA approach

PRODICTA captures behaviour as it naturally occurs during real work simulation.

6

Decision-making under pressure

Real-world performance depends on how individuals operate under constraint.

The science

Decision science shows that behaviour is influenced by:

  • Time pressure
  • Incomplete information
  • Cognitive load

Kahneman (2011); Sweller (Cognitive Load Theory)

What this means

Traditional tests do not reflect real working conditions.

The PRODICTA approach

PRODICTA introduces:

  • Time constraints
  • Competing priorities
  • Imperfect information

To reveal true decision-making behaviour.

7

Behaviour vs intention

Behavioural science shows that individuals do not always act in line with their self-perception.

Kahneman and Tversky

This is why personality tests, behavioural questionnaires, and self-assessment surveys have limited predictive value. People answer how they imagine themselves, not how they actually behave.

What this means

Self-reported answers:

  • Can be biased
  • May not reflect real behaviour
Why trait-based models fall short

Research shows that hiring systems based on inferred traits or self-reported inputs:

  • Can lack consistency
  • May not reflect real-world behaviour
  • Depend heavily on subjective interpretation

Understanding how someone behaves in theory is not the same as seeing how they perform in practice. This is the limitation of personality assessments, behavioural questionnaires, and trait inventories: they tell you what someone is like, not what they will do.

The PRODICTA approach

PRODICTA measures actual decisions, not stated intentions.

8

AI-driven behavioural analysis

By ‘behavioural analysis’ we do not mean personality questionnaires, behavioural surveys, or self-reported preference tests. PRODICTA analyses observed behaviour during real work simulations, what candidates actually do, decide, write, and prioritise when faced with realistic job pressure. The difference is fundamental: self-reported behavioural data tells you what someone says they would do, observed behavioural data shows you what they actually did.

PRODICTA combines behavioural science with modern AI to interpret candidate performance.

The science

Research in AI and HR analytics shows:

  • Data-driven hiring improves consistency and decision quality
  • Behavioural data provides stronger signals than self-reported input
  • Structured evaluation reduces bias and variability

Supported by:

  • IBM Smarter Workforce Institute
  • McKinsey research
  • Frontiers in Psychology (2022)
What this means

AI is most effective when applied to observed behavioural data captured in real work conditions, rather than relying on abstract or self-reported questionnaire responses. The distinction matters: self-reported answers can be biased, rehearsed, or AI-generated. Observed behaviour during actual work tasks cannot be faked the same way.

The PRODICTA application

PRODICTA analyses what candidates actually do during real work simulations:

  • Decision patterns when facing trade-offs
  • Prioritisation behaviour under time pressure
  • Risk awareness when stakes are visible
  • Consistency under pressure across multiple tasks
  • Communication style in real workplace situations

This is observed performance, not self-reported preference. The data comes from how candidates actually behave during the simulation, not from questions about how they would behave.

9

AI, data, and modern hiring

Research shows that:

  • AI improves hiring speed and efficiency
  • Predictive analytics improves workforce outcomes
  • Data-driven organisations make better talent decisions
The critical insight

AI is only as powerful as the data it is trained on.

Traditional systems rely on:

  • CV data
  • Keyword matching
  • Static inputs

PRODICTA uses observed behavioural data from realistic job scenarios.

What this enables
  • Deeper pattern recognition
  • Early identification of risk
  • Stronger prediction of performance and retention
  • More consistent and defensible decisions
10

The commercial reality

Hiring accuracy has direct financial impact.

Industry benchmarks

CIPD reports:

  • Average cost per hire around £6,000
  • Manager-level hires around £19,000

REC benchmarks indicate:

  • Typical bad hire cost between £30,000 and £50,000
  • Mid-management failures can exceed £100,000
What this means

Even small improvements in hiring accuracy:

  • Reduce cost
  • Protect revenue
  • Improve retention
  • Strengthen client relationships
11

Self-perception vs performance

Research shows that self-reported ability does not reliably reflect real performance. In some studies, individuals who rated themselves most highly performed worse in practical assessments.

What this means
  • Confidence does not equal competence
  • CV claims do not guarantee performance
  • Interviews capture perception, not behaviour
The PRODICTA approach

PRODICTA measures observed performance, not self-perception. The candidate who claims to be ‘great under pressure’ gets the same simulation as everyone else, and we measure how they actually respond.

12

Realism and ecological validity

Research in psychology shows that assessments which reflect real-world conditions provide more accurate insights. This concept, known as ecological validity, is one of the strongest principles in modern assessment science.

What this means

The closer an assessment is to real work:

  • The more accurate the prediction
  • The more meaningful the results
  • The higher the trust from employers, HR teams, and hiring managers

Generic personality tests, situational judgement questionnaires, and abstract problem-solving exercises score low on ecological validity because they don’t resemble real work.

The PRODICTA approach

PRODICTA creates realistic, role-specific environments that mirror real decisions, real constraints, and real job conditions. A Marketing Manager candidate works on actual campaign briefs. A Finance Manager reviews actual variance data. A Solicitor advises on actual contract clauses. The simulation environment matches the work environment, high ecological validity, high predictive power.

Bringing it together

Across research and industry evidence:

  • Personality provides general signals
  • Behaviour depends on context
  • Real work reveals performance
  • Experiential methods improve accuracy
  • Observed behaviour during real tasks strengthens prediction (not self-reported answers or personality questionnaires)
  • Self-perception does not reliably predict real performance
  • Realistic, role-specific scenarios produce higher predictive validity than abstract testing
  • AI enhances consistency and insight
The PRODICTA principle

We do not test personality or theory.

We put candidates into real job situations and measure how they actually perform.

Final thought

Hiring should not rely on:

  • What candidates say
  • What their CV suggests
  • Abstract testing alone

It should be based on: What candidates actually do when placed in real job situations.

PRODICTA brings real work into the hiring process so decisions are based on evidence, not guesswork.

Get started →See the demo

References

  • Schmidt, F. L., and Hunter, J. E. (1998; 2016) Psychological Bulletin
  • Barrick, M. R., and Mount, M. K. (1991) Personnel Psychology
  • Mischel, W. (1968) Personality and Assessment
  • Thornton, G. C., and Rupp, D. E. (2006) Assessment Centre Method
  • Kolb, D. A. (1984) Experiential Learning
  • Kahneman, D. (2011) Thinking, Fast and Slow
  • Kahneman, D., and Tversky, A. Behavioural decision theory
  • Sweller, J. Cognitive Load Theory
  • Christian et al. (2010) Personnel Psychology
  • McDaniel et al. (2007) Personnel Psychology
  • Webster et al. (2020) Medical Education
  • IBM Smarter Workforce Institute research
  • McKinsey research on data-driven decision-making
  • Frontiers in Psychology (2022)
  • CIPD Resourcing and Talent Planning Reports
  • REC industry benchmarks