Inventor of predictive personality trait software
People are different.
People who buy Chevrolet in Illinois are different than the people who buy Chevrolet Mississippi and Iowa.
The dominant traits in Illinois are cause and positive emotion oriented. While dominant trait in Mississippi our motion, work and clout oriented.
People who are motion oriented, Have traits that tend to be active, enthusiastic and always on the move. I believe this is consistent with the brand that GM portrays.
And customers don’t just leave a product — they switch to something else.
Or is this correct?
There are inherent traits that predisposed us to switch or change. People that have a high degree of openness to experience, one of the big five personality types, can be predisposed to change more so than others.
It’s in these switching moments that the deepest customer insights can be found and are easiest to uncover.
I agree. I just think it’s easier to segment people into groups of openness to experience versus not at the very least. That information can be calculated and predicted before an interview. How people see the world is very different based on their traits and personality.
Christian’s work on this document is great. I think his work would be more powerful with an empowering technology.
What a great document to find from Harvard business review.
In summary the best teams have cognitive diversity and feel safe to explore and create. These are the teams that create the best work environment and produce results. My own research on the subject to next personality traits to successful teams and the results are very similar.
Matching diverse and skillful personality traits results in high performance teams. Often these teams are best because they’re nurtured from great executive teams as well. They don’t just happen.
Talent management teams can do a lot to balance where to place the right people. There are cases when you need safe teams that keep the lid down and focused.
Further research on this subject might indicate that emotions are not the drivers. Emotions are temporary states. Personality and more important traits are stable over long periods of time and are causal to why great teams exist.
How good are they pulling this off?
All 4 understand the customer at a deeper level than most. They are leaders and have made efforts to use personality and trait theory to better understand why people decide.
Leading companies embrace understanding people at a far deeper level than ever before. Execution is still far from the vision of their executive teams but it gets better with each year. Are we still reminded to buy something we bought; yes. What comes next is far better.
Disney predicts personality and has made some efforts to better understand people. eBay understands predictive frameworks. Their inventory issues do make it hard but they could think different. Netflix stands out as the poster child for personality and trait theory. They can design their products vs. resell something. They can get product to market in relatively short order. Amazon gets it and drives it back to what matters; customer delight. It’s a great KPI for measuring results. Since Amazon can be taken down by China, et al (collectively, his suppliers), his focus on customer delight and brand equity is very important.
I expect these 4 to lead for a while but in 5 to 10 years, who knows. If they do not move fast enough, the theory of disruptive innovation tells us they can be taken down.
Examining US cities is not something that I find to be good research but could not help myself. I am curious about these places. Capitals often have a perceived ‘vibe’ that is different than the rest of the State. In general, cities are too big, too diverse but maybe capitol cities have a feel . They do have a certain ‘vibe’ and I was curious to pressure test my software, treating capital cities like organizations. I did find some interesting patterns; Demographics and financial aspects of cities have nothing in common with their psychometric traits.
GDP, medium income, poverty rate, population, household income, crime index, general health condition, Education Gini index, median resident age and living index all have little in common with the high indexing, psychometric traits of cities.
Below are clusters or groups of like cities based on their collective personalities. I found many ways to define clusters but 10 seems to fit well. All metrics are curent to 2017 numbers. Cluster 2 is generally less affluent than others, especially Cluster 8.
Below are the personality trait clusters for each cluster of capital city. Below are the 1st tier traits and a brief description of each trait. This information along with much more was rolled up into a cluster analysis of all 50 cities.
The traits you see below are in order density. Think of it as a collective scoring marker. Cities can be diverse and diverse within each city but commonalities independent of demographics do connect. Does Salam and Lincoln have similar people, the research indicates yes.
If you are interested in the entire research file, please contact me @ [email protected]
On Sept 17th, Ben Guarino published an article called ‘Scientists identify four personality types’. This is valuable research into an important subject matter
“In a report published Monday in the journal Nature Human Behavior, researchers at Northwestern University in Illinois identify four personality types: reserved, role models, average and self-centered.
Social psychologists dispute whether personality types exist. Traits are another matter. Personality traits “can be measured consistently across ages, across cultures,” said Amaral, co-director of the Northwestern Institute on Complex Systems. The five best-established traits, or Big Five, are openness, conscientiousness, extroversion, agreeableness and neuroticism.
My research indicates the 4 and 5 model personality types are too few and wide when used to quantify decision making, specifically buying things. Myers-Briggs, 16 type model is too narrow. MBTI works well but is hard to describe and execute. My software calculated the traits of millions of people, connecting a theory of traits to why people decide. I am pleased to see further evidence from this work and curious who else is exploring trait theory and decision making.