Masters Strength
Methodology

How our assessments work

Every Masters Strength assessment is built the same way: a framework with a real research tradition behind it, a question format chosen to resist the known biases of self-report, and scoring that is fully deterministic — the same answers always produce the same result, with no black box in between.

The Strengths Profile

The strengths test maps how you naturally contribute, across four archetypes:

Pioneer Encourager Servant Steward

It sits in the strengths-based development tradition: the well-replicated finding that people grow further by investing in what they naturally do well than by grinding at their weakest areas (Buckingham & Clifton, 2001; Clifton & Harter, 2003). The four-archetype team lens follows the team-roles tradition begun by Belbin (1981): teams perform best when the work of starting, connecting, sustaining and completing are all covered — by different people.

Why every question forces a choice

You never rate yourself on a 1–5 scale here. Every question makes you choose between options that are all genuinely positive — there is no "good" answer to gravitate towards. This forced-choice format is one of psychometrics' oldest tools against self-flattery and social-desirability bias, with roots in Thurstone's (1927) law of comparative judgment and a modern statistical literature of its own (Brown & Maydeu-Olivares, 2011). The result describes the shape of how you contribute — which strengths lead — not a ranking of ability. No strength is better than another, and the test cannot say you "lack" anything.

Team Insights aggregates members' profile shapes — never their answers — to show where a team is over- and under-weighted, the risks that come with its mix, and what kind of contribution a next hire would add. That composition lens reflects the team research consensus that who is on the team, in what combination meaningfully shapes outcomes (Belbin, 1981; Mathieu, Tannenbaum, Donsbach & Alliger, 2014).

The EQ Assessment

Emotional intelligence entered the research literature with Salovey and Mayer (1990), who defined it as the ability to perceive, understand and manage emotions — your own and other people's. Goleman (1995) brought it to a wide audience, and his later work with Boyatzis organised the workplace competencies into the four-domain model our assessment uses (Goleman, Boyatzis & McKee, 2002):

Self-Awareness Self-Management Social Awareness Relationship Management

Two layers, two measurement problems

Measuring EQ has a famous trap: simply asking "are you self-aware?" mostly measures confidence, because accurately judging yourself is the very skill being tested. We use two formats, each chosen for the bias it defends against:

  • Forced pairs (24 questions) — two equally attractive statements from two different domains; you pick the one more true of you. Because both options are positive, there is nothing to flatter yourself with. This yields your lean: which domains you naturally reach for first. Like the strengths test, it describes shape, not level.
  • Situational judgment (16 questions) — realistic scenarios where you choose what you would actually do, scored against a keyed ranking of responses. Situational judgment is the format the EI measurement literature reaches for when it wants demonstrated capability rather than self-perception (MacCann & Roberts, 2008). This yields your demonstrated judgment per domain — and unlike a personality trait, it is a skill that grows with practice.

EQ results are private, with no exceptions. On team bookings, each member's EQ result is visible to them alone — there is no sharing option and no team-level EQ view; the team admin sees completion status only. Honest answers need that guarantee, so it is enforced in the data layer, not just the interface.

The Cognitive Ability test

Where the other two assessments describe how you're wired, this one measures reasoning under time — across three kinds of problem:

Abstract reasoning Numerical reasoning Verbal reasoning

These tap what researchers call general mental ability (GMA) — the common factor that runs through diverse reasoning tasks (Spearman, 1904; Carroll, 1993). The abstract section uses matrix problems in the tradition of Raven's Progressive Matrices, the most language-neutral, "culture-fair" measure of fluid reasoning (Raven, 2000); the numerical and verbal sections add quantitative and language-based reasoning.

What a cognitive score does — and doesn't — predict

GMA is, after roughly a century of research, among the strongest single predictors of job performance — and especially of how quickly someone learns a new role — with the relationship strongest in complex, cognitively demanding work (Schmidt & Hunter, 1998). The exact strength is debated: classic estimates put the correlation near 0.5, while a careful recent re-analysis argues it is closer to 0.3 once earlier statistical corrections are fixed (Sackett, Zhang, Berry & Lievens, 2022) — still meaningful, but far from destiny. It explains a slice of performance, not most of it, and says little about reliability, integrity or how someone works with people. The best evidence is unanimous on one point: cognitive ability predicts best when combined with other valid signals — structured interviews, work samples, and measures of conscientiousness and emotional intelligence.

How we report it, and the limits we're honest about. The result is an indicative score on the familiar 100-average, 15-spread scale (100 is average; most people fall between 85 and 115). It is not a clinical IQ: it has not been normed on a representative population or validated against job outcomes, so we frame it as one signal among many, never a verdict. Two honest caveats: the abstract section is the most culture-fair, while the verbal section depends on language and prior knowledge; and because the law in several jurisdictions (including South Africa's Employment Equity Act) restricts using cognitive tests to make selection decisions, this should always sit alongside human judgment, never replace it. Items are generated fresh for every sitting, so no two tests are alike and answers can't be shared — and scoring stays fully deterministic, like everything else here.

The standards we hold ourselves to

  • Deterministic, transparent scoring. Your questions are frozen the moment your test starts, and your result is computed by fixed arithmetic from your answers — reproducible at any time, with no model or human judgment in the loop.
  • Continuous psychometric refinement. Question banks are versioned and reviewed against standard targets — internal-consistency reliability, test–retest stability, item-level performance, plain-language readability, and fairness across language and cultural backgrounds. Items that underperform are revised or retired; forced pairs are checked so that neither statement is the more flattering one.
  • Honest claims. These are development tools: they describe how you tend to contribute and how your judgment shows up, to fuel growth and better-fitting teams. They are not clinical instruments, and no assessment — ours included — should ever be the sole basis for a hiring decision.
  • Privacy in the data layer. Individual answers are never visible to anyone but you — not to teammates, team admins, or platform administrators. Strengths sharing is opt-in and limited to your top two strengths; EQ results are never shared.

References

  • Belbin, R. M. (1981). Management Teams: Why They Succeed or Fail. Heinemann.
  • Brown, A., & Maydeu-Olivares, A. (2011). Item response modeling of forced-choice questionnaires. Educational and Psychological Measurement, 71(3), 460–502.
  • Buckingham, M., & Clifton, D. O. (2001). Now, Discover Your Strengths. Free Press.
  • Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor-Analytic Studies. Cambridge University Press.
  • Clifton, D. O., & Harter, J. K. (2003). Investing in strengths. In K. S. Cameron, J. E. Dutton, & R. E. Quinn (Eds.), Positive Organizational Scholarship (pp. 111–121). Berrett-Koehler.
  • Goleman, D. (1995). Emotional Intelligence: Why It Can Matter More Than IQ. Bantam Books.
  • Goleman, D., Boyatzis, R., & McKee, A. (2002). Primal Leadership: Realizing the Power of Emotional Intelligence. Harvard Business School Press.
  • MacCann, C., & Roberts, R. D. (2008). New paradigms for assessing emotional intelligence: Theory and data. Emotion, 8(4), 540–551.
  • Mathieu, J. E., Tannenbaum, S. I., Donsbach, J. S., & Alliger, G. M. (2014). A review and integration of team composition models. Journal of Management, 40(1), 130–160.
  • Raven, J. (2000). The Raven's Progressive Matrices: Change and stability over culture and time. Cognitive Psychology, 41(1), 1–48.
  • Sackett, P. R., Zhang, C., Berry, C. M., & Lievens, F. (2022). Revisiting meta-analytic estimates of validity in personnel selection. Journal of Applied Psychology, 107(11), 2040–2068.
  • Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185–211.
  • Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology. Psychological Bulletin, 124(2), 262–274.
  • Spearman, C. (1904). "General intelligence," objectively determined and measured. American Journal of Psychology, 15(2), 201–292.
  • Thurstone, L. L. (1927). A law of comparative judgment. Psychological Review, 34(4), 273–286.