So, let’s face it, when we look at personality measurement, a casual conversation usually leads to a few innocent individuals piping up that they’ve done the MBTI and are YMCA or PTSD – or something along those lines. Yes, the MBTI is well-known has been around since the second world war and seemingly just won’t go away. What also won’t go away is the whole concept of personality types. In fact, it didn’t start with Meyers and Briggs and the MBTI but with Hippocrates, the Greek philosopher who gave us the first four types of personality based on bodily fluids and a few millennia later translated into temperaments by the illustrious Wilhelm Wundt: melancholic, choleric, sanguine, and phlegmatic.
So, personality types have been with us for millennia – it seems as if it is natural for us to look for patterns (it is indeed natural for us to do this) and try to give order and box all human beings into a limited number of personality types. Surely this must be wrong – or must it?
But first what is it about personality types that is so appealing?
- They are simple– that counts for a lot: splitting people into a few groups is the simplest form of complexity. We know people are different and giving some obvious groupings gives us some form of orientation and a way to communicate and represent the complex world around us
- They feel intuitively right – we know some people are extraverted and some are introverted so it feels right to split people into these classes. Similarly, we all know some nerd who seemingly completely lacks human feeling or intuition and we all know a kindly soul who fails to grasp complex cognitive concepts. This gives us the humanist/cognitive dichotomy.
- People who are first introduced to them have an “aha” moment and many become die-hard cheerleaders of the first system they were introduced to.
- It helps in explaining and understanding outcomes – it simplifies the learning and analysis process of using personality assessments
- They are simple and feel intuitively right – I repeat this once more because these factors are so important to their popularity.
This may sound pretty harmless. Certainly, I confess, as a first step it does prompt the uninitiated to think about personalities and how we differ. This in itself is useful, really. But after this first step, personality typing or archetyping can actually be grossly misleading if not harmful. Let’s understand some of the limitations and dangers before going on to consider whether the new world of technology and big data can give us more insight, and what this insight could be.
What’s problematic about Personality Types?
- Personality types are often based on outdated ideas – the MBTI, for example, is based on Jungian theory. As much as Jung was an influential figure his ideas were not based on the sort of solid data and rigorous science that we can now apply to psychology or personality theory. Not to mention the massive leaps in cognitive and behavioural science since the start of the 20thcentury.
- Personality types may be fundamentally wrong. Consider the intuitive vs. cognitive dimension (that’s thinking vs feeling to our MBTI cult members). Many type models consider these a sliding scale. If you are intuitive, you are not cognitive, and if you are cognitive, you are not intuitive. This is just plain wrong. Intuition and cognition are processed in different parts of the brain and in different ways, so it is possible to be high on intuition and high on cognition. Indeed, our data from our Human Behavioural Framework shows that this is precisely what many high performers in business are: high on intuition and high on cognition.
Even types that are well researched such as extraversion and introversion fail to fully match how people behave. For example, some people, such as my daughter, are shy extraverts. She has externalised thought processes with people she knows i.e. she is very talkative and expressive but will be shy with new people. Most personality assessments and certainly personality typing will completely fail to capture this. Our data again shows that these patterns are surprisingly common.
- There is also a problem of extremes and averages – think again of the extraversion introversion scale – most of us fall somewhere in the middle and are in essence ambiverts sometimes more extraverted and sometimes more introverted. It is those extreme personalities who are most noticeable and end up tarring all of us with one brush or the other, showing some of the limitations of personality typing.
- Context is another issue – many of us have thought while answering personality questionnaire – “it depends”. It may depend on mood, it may depend on whether it is at work, with your friends, or with a romantic partner. We often have different personalities in different contexts. Personality types will fail to capture this.
- Coupled with the above is also the concept of stability. Let’s take emotional sensitivity. We may be most often calm, but at the end of a long day may end up being irritable – and, as those who have children will know and as I certainly experienced after having children, they can bring you to emotional explosion that you may not have experienced since puberty – or ever. This leads us to surmise that stability of personality is a feature that is not measured and should be. This may actually be more descriptive of our personalities than just the extremes.
This is just what we decided to do in our assessments – measure stability of personality over time. Personality types completely ignore this. However, the extremes are also always interesting!
- Intensity of personality traits and their facets may be much more descriptive of an individual than those that are moderate – it is, after all, the extremes that are noticed. What we have also noticed in our data is that those who class themselves at the extreme end of personality scales do this consistently, so these are often extreme and stable. Many personality types fail to show either extremes or scales of intensity.
- Third-person impact is also important to measure. Most personality assessments are self-reported – we know that what we report is often not objective or may be us as we would like to be. Therefore third-person data is extremely useful. This is also why we report core personality traits as those that differ most to the norm, are stable, and match third-person perspectives. Personality types fail to do this.
- Parts of the picture – when we first did our meta-analysis of personality traits and facets it became obvious that many of these are measured very often (for example, those to do with cognitive types or humanistic types are consistently measured by masses of assessments). However, other traits and facets were hardly measured at all – some of which could be critical to describing personality. For example, ability to approach conflict is rarely measured directly. Therefore, personality types only ever show part of the picture and may fail to capture important personality information. We, on the other hand, are committed to measuring 100% of personality.
But surely there are patterns?
Well, yes there are common themes, but these should be understood as clusters of strengths rather than a type. This is why we call these strength clusters and there is some use in showing these clusters and taking this into account in teams and organisations.
Our data shows that when matching to roles and functions that groups of granular data is more effective than large types or even classic large (and well-researched) traits such as the big five. In one project we were able to 100% identify quality teachers and low-quality teachers from a dataset we had of educators. This was done not through limited or generic types but 29 facets. Perhaps most importantly, it depended on taking into account sweet spots – the idea that higher (or more) of a desirable trait is not always better and there is such a concept of “too much of a good thing”.
Will big data solve our problems?
Some claim that big data and machine learning can solve these problems. And the answer is maybe. The biggest issue with big data is the notorious data problem: Rubbish in, rubbish out. We have to be able to search quality data in meaningful ways. I remain unconvinced we can do that at this moment in time. The Facebook data that hit the news with the Cambridge Analytics scandal showed this. This was using simple ‘big five’ traits. With only five traits it is impossible to look for deeper patterns because the comparison is always limited to these five traits. This is similar to what we said about granularity of data in identifying quality teachers.
Similarly, we have the problem of context driving outcome – when we go into a church, we are all quiet and considerate – context drives our behaviour more than our underlying personality. Without this understanding it will be difficult to gain deeper insight.
The final problem is similarity of behaviour with different underlying causes. An angry outburst is a behaviour which may label us as disagreeable personality. However, it could be justified, and the causation may be very different in different people: in one-person it may be an insult, in another a loss of freedom, in another tiredness, etc. Indeed this is indeed one of our pet theories of emotional drives – we measure this and then can predict how high frustration and or satisfaction will be within certain contexts – even so far in that we developed questionnaire that could predict reasonably accurately how sensitive individuals are to feedback in the corporate context and what types of feedback will stimulate what types of responses. Throwing big five data and feedback sensitivity at a machine learning algorithm I am sure will fail to identify the deeper underlying causes – this is where theory and deep understanding will still trump data.
That said we do strongly believe that technology will enable us to measure personality in different ways and be more accurate – for example there has been a successful attempt to measure neuroticism from motion sensors on smart phones: nervous people are more jittery. Similarly, tendency to choke under pressure has been related to eye blinking at rest which can be measured by a simple camera on a smart phone – not to mention all the other data sources such as email communication, smart phone data, social media usage, and health information form wearables. Obviously, this all comes with privacy concerns, but may yet be helpful in understanding personalities better.
Our view is that the better we can understand personality, strengths, drives, and values, the better we can match people to meaningful jobs where they can use their skills to their best, increasing their well-being and life satisfaction. Personality types, as they stand, are woefully lacking in their ability to do this. Our Human Behavioural Frameworkis a much better bet for this.
- Personality types are only ok for a simple first step into understanding personality
- Personality types are simplified, problematic and should never box you in
- Refined granular data is more effective especially in the context of team or organisation-wide dynamics
- A solid framework allowing the measurement of complete personality can do much more than personality types or even solidly researched models such as the big five.
- Not wanting to toot our own horn (well, I do actually) but we have a unique model and comprehensive framework to measure personality, stability of traits over time, strengths, and values. This data can help you and your business use personality data much more effectively than anything on the market at the moment.