People drive results. Psiconometria measures how, how much and with what certainty.

Psiconometria is an integrated approach that combines rigorous measurement of human characteristics with quantitative methods of economic analysis — to understand how people, behaviours, relationships and decisions influence business processes and outcomes.

See a step-by-step example Explore the connections Discover the method

A methodological proposal in development.

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Fig. 1The central idea in one line. Psychometrics ensures that the Factor measures what it claims to measure; econometrics ensures that β is estimated without misleading. Tap each term.

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The concept

Economic results are produced by systems — and by the people who lead, decide, learn and execute.

Psychometrics is the science of measuring human characteristics rigorously: defining what is to be measured, knowing how much of the measure is signal and how much is noise, and checking whether it is fit for the intended use.

Econometrics is the set of methods for estimating relationships in economic data: how much one variable moves another, with what uncertainty, and when an association can be read as a cause.

Separately, each solves half the problem. The first measures well but rarely reaches the business indicator. The second models indicators but tends to treat people as just another number. Psiconometria brings the two together to answer a management question: which human factors move this result, by how much, and with what degree of certainty?

Psychometrics
The science of measuring human characteristics rigorously: validity, reliability, fairness.
+Econometrics
Quantitative methods for analysing economic data: uncertainty, causality, forecasting.
=Psiconometria
The integrated proposal: investigating how human factors influence business processes and outcomes.
  1. Level 1People
  2. Level 2Behaviours
  3. Level 3Relationships
  4. Level 4Processes
  5. Level 5Indicators
  6. Level 6Business value
Fig. 2Human factors become behaviours; behaviours move processes; processes move indicators. The further along the chain, the more other causes (strategy, market, capital) enter the result.

Ten convergences between two disciplines that rarely talk to each other

    Three ways to explore

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    An example, step by step

    Why do some teams redo almost twice as much work as others?

    Illustrative example with fictitious data. A customer service network has 24 teams that follow the same process.

    1. The business question

      Rework varies from 6% to 12% of deliveries across teams. Before investing in yet another training programme, the board wants to know what explains the difference.

    2. Rule out the obvious

      Before looking at people, process, volume, tools and quality of inputs are checked. None of these explains the difference between teams that work the same way.

    3. Measure the human factor

      Hypothesis: where it is safe to admit a mistake, it is corrected before it becomes rework. Psychological safety is measured with a short, validated scale (Edmondson, 1999), answered anonymously and analysed only as each team's average. Before using the index, its reliability is checked.

    4. Relate it to the indicator

      Fig. 3Rework by psychological safety index, 24 teams. Fictitious data for teaching purposes. The line shows the trend estimated by simple linear regression.
      Estimated effect (β)−1.5 p.p. per point
      95% interval−2.9 to −0.2
      Variance explained (R²)0,20
      Sample24 teams

      The relationship exists, but it is modest and uncertain: the factor explains about a fifth of the variation, and the interval is wide. Above all, it is an association. More experienced teams may have both more safety and fewer errors. The next step controls for tenure and volume, and then tests.

    5. Test before scaling up

      Six teams adopt blameless error reviews; six similar teams carry on as before. Two quarters later, the change in rework in the two groups is compared (difference-in-differences).

    6. Decide

      If the effect is confirmed and exceeds the cost, the practice is scaled up. If not, the company has avoided a programme that would not have worked and learnt where not to look. Both outcomes have value.

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    Why it matters

    Companies measure revenue to the penny and people by impression.

    The biggest cost is the least measured

    In service companies, payroll is usually among the largest expense lines. Even so, hiring, development and leadership decisions are the ones least supported by data.

    Without comparison, every programme seems to work

    Those who took part were already different, the market improved, the team changed. Without a baseline and a comparison group, there is no way to separate the effect of the initiative from everything else.

    Measuring badly is worse than not measuring

    Instruments used outside their purpose produce unfair decisions about people and legal risk, with an appearance of objectivity.

    Featured case

    Q12 meta-analysis — engagement and outcomes

    Gallup, meta-analysis, 2020 (10th edition)

    Synthesis of hundreds of studies on the relationship between team engagement and business outcomes. Consistent associations between engagement and all the indicators studied, with relevant differences between units at the top and bottom of the distribution.

    Caveat: Statistical association does not mean that all effects are caused exclusively by engagement; causality probably flows in both directions; sponsored studies require careful reading.

    See the five cases with sources

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    Where it helps

    Seven common situations in companies, and how Psiconometria approaches each one.

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      Demonstration

      From the person to the indicator: a mechanism chain, not a leap of faith

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      Limits

      What we can measure — and what we should not promise

      We can

      • Measure perceptions, behaviours and team dynamics with validated instruments.
      • Relate human factors to operational indicators with explicit uncertainty.
      • Test interventions with pilots, comparison groups and baselines.
      • Learn from each cycle and recalibrate hypotheses.

      We do not promise

      • To predict a person's success from a psychological profile.
      • To link a personality trait directly to valuation, revenue or profit.
      • To replace professional psychological assessment with management questionnaires.
      • To treat correlation as causality — ever.

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      How to start

      Two ways to start, both small.

      Start an organisational diagnosis

      A non-clinical diagnosis of your company's measurement maturity: what you already measure, what is missing and where to begin. No psychological tests, no collection of sensitive data.

      Talk to us about your company

      Propose a pilot project

      One business question, one baseline, one intervention and indicators tracked with statistical honesty. This is how Psiconometria proves itself: on a small scale, in public.

      See the seven stages

      Methodological commitment and sources

      Every factual statement on this site states its source, year and type of evidence. We work from the American Psychological Association, AERA/APA/NCME, the Brazilian Federal Council of Psychology (CFP) and SATEPSI, OECD, World Bank, Google re:Work, Gallup and Our World in Data. Psiconometria is an authorial concept in development — not an officially recognised science nor an established academic discipline.