Insights Discovery

Have you been speaking to my Mum and Dad....?.

Is something we hear frequently when handing out the Insights Discovery Personal Profiles as part of an interactive workshop.

The narrative of each profile is unique to the individual, and each chapter is written in a personable and meaningful way as if a relation or close friend of the recipient had contributed their thoughts. We frequently have to reassure people that we do not have a team of researchers following them around taking notes and documenting their quirks and idiosyncrasies. 

The truth is that the Insights Discovery profile evaluator and resulting personal profiles are continuously assessed for accuracy. Insights Discovery is proudly recognised by the British Psychological Society (BPS) for use in the workplace as well as counselling, career guidance and general health, life and well−being. This makes the model so much more than just a work-orientated development tool - it's positively life-enhancing.

So let's take a look at how the model gets validated without letting any of the Discovery magic out of the bag.

External Assesment

In 2005 the University of Westminster’s Business Psychology Centre performed an extensive study of the 'Insights Discovery Evaluator (IDE) English Version 3.0'. Key statistical analysis was used to study the IDE’s “item analysis”, “norm data”, “reliability” and “validity”.

For a more comprehensive review of the IDE’s properties, please read “An Overview of the Development, Validity and Reliability of the English Version 3.0 of the Insights Discovery Evaluator” produced at the University of Westminster’s Business Psychology Centre (BCP) which is available upon request.

Item Analysis.

There are 100 colour items spread over the 25 frames in the IDE. Item analysis involves empirically testing the quality of these 100 items and replacing weaker items with stronger ones. This is measured by assessing the responses of participants with clear colour preferences, i.e. those whose average across all 25 frames is greater than 5 in one out of the four colours (“Sunshine Yellow”, “Fiery Red”, “Earth Green” or “Cool Blue”). This figure image shows one of the improvements made in the items from IDE S1.0 (UK) to IDE S2.0 (UK). 

Data on Norms

The norm data for the IDE is of good quality, being segmented by the language of the evaluator completed; the country a respondent is based in; age (in ten-year bands) and occupation. The occupational norm data provides predictive validity. As expected but although not exclusive, those in charge of financial data tend to have a preference for objective thinking (either Red or Blue as a top two colour preference), using facts and performing detailed analysis. It should be noted whilst this data indicates that people in certain roles tend to have a preference for certain colours, it does not correlate or necessarily relate to how well they are doing their job or how capable they are in fulfilling that role. It also does not limit a certain colour energy from being good in a role that falls outside of this observation.


Cronback-Alpha coefficients, α, measure the error variance on the average inter-item correlations. When the error variance is low, which is desirable, the alpha coefficient approaches 1.00. A value of 0.70 is the commonly accepted inferior limit. Analysing 24,224 completed evaluators shows the four colours to have very high Cronbach- Alpha coefficients, providing evidence of reliability.

Test-retest reliability is determined through the administration of the same evaluator across time. It helps gauge how robust the items are. Such tests are generally expected to yield reliability coefficients ranging between 0.70 and 0.90. The results of the test-retest analysis performed on the four colour scores show very high reliability, translating into coefficients ranging from 0.81 to 0.86 for the Pearson correlation coefficients and 0.89 to 0.92 for the Cronbach-Alpha reliability coefficients for the same data. Validity Confirmatory Factor Analysis was used to test the hypothesised factor structure of the Insights Discovery model. Specifically, it is hypothesised that the four sets of 25 colour based items in the IDE should load onto the factors such that the polar opposite nature of the ‘Fiery Red’ vs. ‘Earth Green’ items is apparent and the polar opposite nature of the ‘Sunshine Yellow’ vs. ‘Cool Blue’ items is apparent. The four colours should load onto their appropriate factor only.

Ongoing Assessments/Validations

The constant evolution of language means that the Discovery Evaluator will continually evolve. The Insights Research Team monitors the Insights Discovery Evaluator in its 30+ languages on a daily basis. Examples of the Statistical Reliability and Validity tests can be obtained from Insights Learning & Development Ltd on request.


Over the past decade, the work of Carl Jung has attracted increasing interest as people seek to improve interpersonal dynamics on both personal and professional levels. The scientific research of the Discovery System demonstrates that both Jung’s original typology theory, and Insights’ ongoing research to enhance it, has both strong psychological foundations and modern scientific application. Depth psychology and empirical science unites within the Insights Discovery System. 

James Hampton (He/Him)

James Hampton (He/Him)


Our areas of specialism.


  • Self-awareness

  • Resilience

  • Personal Development

  • Change

  • Decision making

  • Growth mindset

Team development.

  • Hybrid team working

  • Communication

  • Meetings

  • Feedback

  • Collaboration

  • Trust

Leadership development.

  • Leadership styles

  • Psychological safety

  • Leading change

  • Mission, vision, values

  • Culture

  • Mentoring