Human Insight

Scientific Research

Our research topics and professional passion

Since the 1980s, Human Insight has been studying how people behave and contribute to the execution of strategies. This has led to interesting findings with a direct impact on team performance, leadership development and cultural behaviour within organisations. You can read about these studies at scientific research.

Besides scientific research, we are responsible for interesting case studies in cooperation with partners and clients. In the case studies on this page, you can read how our assessments and tools have contributed to various complex issues.

Our four research areas

In short our passion and research takes us in four different areas:

These four research topics are what drives us to help our customers flourish and cultivate organisations that invest in their people. We are passionate about people because they make the difference. We want to work with companies that put their people and their development first, because we believe they make the difference for long term sustainable growth.

Scientific Research

Our research

The S-Curve and Why No One Has Time to Innovate

By Dr. Scott Hutcheson and Matthew D. Jones

Near the beginning of 2021, we surveyed 28 leaders (senior managers or executives) in small-to-medium manufacturing companies across the U.S., with the majority in the Midwest. We wanted to know how they felt about a myriad of things, but particularly in how digital technologies or digital innovations were being used,
developed, or invested in their respective organisations.

As part of this research, we included an outreach component where we invited each of the 28 leaders to consider whether they would like to participate in a short-therm pilot innovation project.. What we found out was surprising.

AEM-Cube® Validity Study - 2021

By Human Insight

How does the AEM-Cube compare to other globally used assessment tools? Several consultants, coaches, and practitioners working with the AEM-Cube have recently indicated an interest in how the AEM-Cube dimensions relate to dimensions of other frequently used instruments, such as the NEO-PI-3 (also known as Five-Factor Model, OCEAN or Big Five; Costa & McCrae, 1992), the Hogan Personality Inventory (HPI; Hogan & Hogan, 1992), and the DISC Theory (Marston, 2013). Investigating the relationship between the AEM-Cube and these questionnaires might provide valuable insight into the traits underlying the AEM-Cube dimensions.

Investigating the relationship between the AEM-Cube and these questionnaires might provide valuable insight into the traits underlying the AEM-Cube dimensions.

The Two Traits of the Best Problem-Solving Teams - 2018

By David Lewis and Alison Reynolds

How people choose to behave determines the quality of interaction and the emergent culture. Leaders need to consider not only how they will act, but as importantly, how they will not act. They need to disturb and disrupt unhelpful patterns of behaviour and commit to establishing new routines.

To lay the ground for successful execution everyone needs to strengthen and sustain psychological safety through continuous gestures and responses. People cannot express their cognitive difference if it is unsafe to do so. If leaders focus on enhancing the quality of interaction in their teams, business performance and wellbeing will follow.

Teams Solve Problems Faster When They’re More Cognitively Diverse - 2017

By David Lewis and Alison Reynolds

If cognitive diversity is what we need to succeed in dealing with new, uncertain, and complex situations, we need to encourage people to reveal and deploy their different modes of thinking. We need to make it safe to try things multiple ways. This means leaders will have to get much better at building their team’s sense of psychological safety.

There is much talk of authentic leadership, i.e., being yourself. Perhaps it is even more important that leaders focus on enabling others to be themselves.

How people contribute to Growth-Curves​

By Prof. Peter Robertson M.D. and Prof. dr. Wouter Schoonman

This article describes the basic statistical background
of the AEM-Cube and the longitudinal research of all assessment and reassessment data, within a time range between 1 and 12 years, that could be extracted from the 30.000+ assessments available today.

The result will show that there is a high level of stability and that assessment and reassessment data do not differ more than about 10 percentiles over the years for the two factors that describe the direct contribution to the Growth-Curve. The third factor, describing the contribution to the integration of Growth-Curves differs about 15-20 percentiles, which was to be expected because this factor reflects in a certain way a personal development as a consequence of career development and was never hypothesised to be stable in the first place.