That label is the problem, according to Kylie Seaman, Head of Client Solutions at Emergenetics UK & Ireland, part of the First Ascent Group.
"The tool isn't always the issue," she says. "What people do with the output is. Someone is told they're the creative one and eighteen months later they're left out of the budget-planning meeting because a manager remembers the word "creative" and files them accordingly. Nobody decided to limit that person's career. It happened by shorthand."
Seaman thinks the damage runs in two directions. Managers use labels to sort people, often subconsciously. Employees do it to themselves too and she reckons that's the more expensive habit.
"I hear it constantly," she says. "'I'm not a detailed person.' 'I'm no good with people.' 'My brain does not like working with numbers or spreadsheets.' Those aren't findings. They're sentences someone picked up in a workshop and never questioned. And they're used to opting out of exactly the work that could lead to a promotion."
Treating any single personality profile as the "right" one for a job can narrow people's sense of what's possible for them and shrink diversity within a profession. A tool designed to describe someone can end up fencing them in instead.
Seaman sees a particular pattern in how people read their own results. Show most people a report that says they lean towards big-picture thinking and they'll walk away believing they can't do detailed work. What the report probably says is that detail isn't where they go first.
"There's a gap between 'this isn't my preference' and 'I can't do this'," she says. "A preference is a starting position, not a limit. You can work outside your preferences. It costs more energy, so you might not enjoy doing it all day, every day. That's a workload conversation, not an identity."
According to Seaman, organisations should ask 9 questions when assessing or selecting a psychometric tool.
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A preference is a starting position, not a limit.
1. What population size and make-up informed the original research upon which the tool was based?
A minimum sample size should be 5000 and it should measure people from backgrounds relevant to the audience the tool will be used with.
2. How reliable and valid are the questionnaire questions? Are the results consistent over time?
Inter-Item Reliability: find out if the Cronbach’s Coefficient Alpha, used to measure inter-item reliability in reputable psychometric tests, falls within the range of 0.70 to 0.85
Test-Retest Reliability: refers to the stability of the survey over time; that is, whether a person's scores remain the same if they take the test more than once.
3. Are the norms recalculated as population trends evolve?
Many tools are decades old, or older and are not re-normed, even as the working population's characteristics (social attitudes, educational approaches and technology) evolve globally. We must regularly account for changing social norms, as we are a collective, evolving organism.
4. Does the tool provide a free, openly published technical report to explain its research and reliability?
Many tools are not open about their research background and reliability/validity results. They do this because they know it would expose poor (or no) research and weak design principles. Well-researched tools make their Technical Report freely available for anyone to access.
5. Are the questions and reports straightforward and written in plain language?
Some tools use jargon that only psychologists can easily understand. Additionally, the language can be negative and judgemental. Question design (words and structure) needs to be easy and reporting language needs to be straightforward and memorable. Negatively worded reports can be incredibly damaging and counterproductive.
6. Are there support tools available to enable participants to embed learning and impact?
Is anything provided other than the profile and the facilitation? How is it made practical and how is learning revisited to ensure understanding is not diluted or forgotten? Tools need to provide ongoing support mechanisms to maximise their learning impact.
7. Does the tool assume linkages between thinking and behaving attributes?
Many tools combine how we think and behave into one attribute (e.g., an analytical thinker will be assumed to be an introvert). Four-attribute models tend to fall into this trap because they must simplify to 4 traits. Research now shows thinking and behaviour traits are separate and independent.
8. Does the tool have a quality control infrastructure globally?
Most tools rely on certifying practitioners to deliver the end-user experience. Most tools do not run regular quality-control checks on their practitioners, who inevitably develop bad delivery habits or fail to keep up with research.
9. And finally, does the profile label people?
Many profiles assign labels (encouraging stereotypes) to certain personality types. Today, people quite rightly reject this approach because it oversimplifies us as humans and tends to discourage adapting our behaviours to suit the situation (i.e. the labels can be used as an excuse). Humans are far more complex and will shift preferences across situations, this needs to be one of the strong messages a reliable tool delivers.
Seaman’s advice for anyone still carrying an old label is blunt. Go find the original report, because the nuance almost always lives in the document, not in what you remember eighteen months later. Look honestly at what you've quietly stopped putting your hand up for. Then talk with your manager, your fellow leaders, your coach or mentor, because an unstated preference becomes an assumption and assumptions get written into who gets picked for what.
The end goal, she says, isn't self-awareness for its own sake.
"Self-awareness does not come from knowing your type. It comes from being able to explain how you work to the person sitting next to you and understanding them well enough to communicate more effectively. If a profiling exercise ends with people wearing badges, it's a failure."
