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Director of Design, Dawson Andrews,
Nov '18 | 5 Min Read
The Big Five Personality Traits, sometimes referred to as the five factor model (FFM), is a model commonly used by psychologists to describe individual personalities. The original model was constructed by Ernest Tupes and Raymond Christal in 1961 but it didn’t reach mainstream academic audiences until the 1980s and early 90s.
Multiple sets of independent researchers on human personality arrived at the same conclusion in naming the five factors that generally predict and explain behaviour which indicates the factors are valid as far as we know today.
Each of the five factors (O,C,E,A,N) are scored between 1–100 according to the individual ranked against average scores after completing a series of questions.
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The five factors are:
Every person maps differently to each of the OCEAN personality traits, and having an understanding of how others around you correlate is beneficial to your interactions with them. Not everybody is comfortable being open about the specific scores on each of the factors, particularly as some indicate socially negative traits such as anxiety and depression. Before co-founding our product design studio, each of the directors took the Big Five Personality test as a means to a) see how aligned/unaligned we were in our own individual personalities and b) as a means of empathising with each other in recognising our strengths and supporting our weaknesses. I understand that not everybody would be comfortable sharing something that is so personal to the individual, but we found this exercise has eradicated any talk of “I don’t understand [person]’s point of view” and “I don’t get where [person] coming from”.
For me, the tools and methodologies within the field of user experience are flawed in that they do not address concerns beneath a user group level. A truly meaningful experience would speak to the individual rather than taking a one-size-fits-all blanket approach.
We are great at understanding the needs and desires of groups of people, but even personas — the UX tool designed to help empathise with specific users — always bring us back into solutions that scale up to cater for groups based on the assumed needs of a single user. Designing an experience for Sarah, a junior shop assistant who likes long walks, often leads that the majority of users become Sarah and her intended experience is their experience. Job Stories are a relatively new entry into this space where they fix the problem of personas splitting audiences, getting in the way of shared goals. Job Stories are a good means of orienting towards tasks and for that reason remain compatible with an OCEAN approach to UX where Job Stories address universal functional requirements. It leaves room for a presentational layer and certain functional elements catered for individuals.
Applications could adapt their interfaces to individuals. Let’s imagine a fitness app with a audio guided run feature. Users in the upper percentiles of conscientiousness may benefit from the orderly, disciplined commands of a drill sergeant and from an app that stretches their goals slightly beyond their comfort zone pushing the user to compete at their best. For people on the other end of the conscientiousness scale, a softer approach would be necessary along with positive reinforcement to help them be the best that they can be without pushing them into territory that alienates them or makes them feel inadequate.
The same could apply for language and labels used within interfaces. Perhaps some colours appeal to certain personalities? Maybe there are images that intimidate people that inspire other sets of people?
Looking at the differences between individuals along OCEAN factors studies have shown that individuals high in agreeableness (people who give up time for others, make people feel at ease) are less likely to negotiate salary increases within their company. Perhaps we can create applications that help people move towards desired outcomes in adjusting elements in their personality that may be impeding on particular life goals.
One of the biggest challenges in pursuing this untapped area of UX is gathering the data required to determine a person’s scores along the Big Five Personality Traits. It’s not exactly ideal to have users answer a full personality test under the promise of a better user experience on the other side of this unique onboarding experience, and it’s certainly not ideal to gather this data in any way that negatively affects a user’s privacy. Maybe it’s something that happens over time where certain actions can produce a score against the OCEAN factors, or games, puzzles and quizzes may unlock this type of information. There is work to be done and design problems to figure out here.
Then there’s the question of how you store this information and what exactly you do with it. I don’t believe it is necessary to store this data on servers or let any company see a user’s scores. That is for the individual to know and for the product experience to react to it. It is potentially dangerous territory, but then again, so is everything we do:
"If ethics is about the question of how to act, and designers help to shape how technologies mediate action, designing should be considered ‘ethics by other means.’ Every technological artefact that is used will mediate human actions, and every act of design, therefore, helps to constitute moral practices."
– P. P. Verbeek, What Things Do, 2009
In other words, every design decision you make is loaded with your intent and bias. We’re already knee deep in the danger game whether you have realised this sobering fact already or not. Another one of the major challenges is engineering objectivity into this process, and whether this field is explored further or not, we should look to engineer objectivity into our work regardless.
I’m at the mystery stage of the knowledge funnel as described by Roger Martin in his 2009 book The Design of Business. I have identified that this is an area with great potential and the next steps are to build heuristics to see if we can mine the mystery for insights with the eventual hope of turning the research into a reliable, replicable algorithm give us the capability to create and resonate with the people who use the things we make.
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