Why you may not be as talented as you think you are
Postat de admin la 23 Jun, 2015 in categoria Abilitati, Personalitate, SelectieOur fascination with talent goes back a long way. Homer described the qualities of his heroes with a precision not reached by today’s profiling experts. For instance, Odysseus was brave, clever, quick-witted, and at times too focused on himself. In China, the Han Dynasty introduced an Imperial Examination for evaluating expertise, fit, and moral integrity for government jobs, much like modern assessment centers do today. And for at least 100 years the U.S. and European military pioneered the use of psychological tests to predict the performance of soldiers and generals, as well as their propensity to remain sane during combat. More recently, computer- generated algorithms have been used to match people to the right job in areas as diverse as sports, education, and business.
The Talent Equation
Though conceptions of talent vary, they tend to agree on one point: Talent is performance minus effort. In other words, if two individuals are equally motivated and expend the same amount of effort to accomplish something, the most talented individual will perform better.
By the same token, a person with more talent can achieve the same result with less effort than a person with less talent. And, of course, when two individuals are equally talented, only effort will make the difference. So the main point of talent is to account for people’s motivation.
For example, when someone says, “you’re not trying hard enough,” he’s implying that your talent exceeds your performance, or that you aren’t fulfilling your full potential.
The rest is just context-specific: Roger Federer may not have much talent for singing; Angela Merkel may not have much talent for stand-up comedy; and Jeff Bezos may not have much talent for neurosurgery. But this does not imply that they could not develop these talents over time, but rather that, in light of their potential, it would take quite a bit of time for them to do so.
Most organizations have a working model of talent, though not always explicitly. These models tend to decode high potential for key positions into specific competencies, which have often been put together by their HR department.
Though the list of possible competencies is as large as the number of nouns in a given language, all competencies can ultimately be reduced to four core talent categories:
- Technical skills (task-related expertise)
- Intrapersonal skills (managing yourself)
- Relationship skills (managing others)
- Leadership skills (managing the organization)
That said, there are generic talent qualities that influence all of these four categories, and not just in the world of business: Talented people tend to be smarter, more likable, resilient, and curious.
Despite our ability to define and measure the key attributes of talent, people are generally reluctant to accept this, not least when evaluations of their talent are less favorable than they would hope, and particularly when such evaluations are used to make decisions that don’t go in their favor.
There are well-established psychological principles to explain our reluctance to accept others’ take on our talent, namely:
Self-delusional Bias
We are generally less talented than we think. Indeed, studies comparing self-estimates of ability with actual ability measures report a very weak correlation between the two, mostly because of the common tendency for people to rate themselves more favorably than they should. This is particularly true for men, even in egalitarian cultures like Scandinavia.
Determinism
We are generally more predictable than we think. When we think of ourselves, we tend to believe that we are complex and unpredictable; but when we evaluate others, we find them rather consistent and predictable.
The idea that someone can measure our talent implies that they are somehow able to predict what we may or may not do in the future, and that idea hurts us. Of course, nobody can tell with 100% accuracy how we will perform in the future, but valid tools like psychological tests can be used to make forecasts that are 30% more accurate than chance. Such tests work, not because we are unable to choose our future, but because our choices are predictable. It is case of consistency rather than determinism.
Motivation Is More Stable Than We Think
Although our motivation fluctuates from time to time, there are clear baseline differences in motivation between people, which make our performance fairly predictable over time.
Talent alone is not enough because motivation can inhibit or empower our talents. But since our motivation levels are not totally erratic, our typical levels of drive and ambition can be factored in to predict how our talents are likely to be manifested in the future.
The last point is important and justifies the inclusion of motivation as a key feature of human potential. In fact, if talent is performance minus effort, potential may be thought of as talent plus effort, as you will only fully leverage your talents if you are motivated to work hard.
As Andrew Carnegie put it: “People who are unable to motivate themselves must be content with mediocrity, no matter how impressive their other talents.”
The Bottom Line
For nearly 30 years, Hogan has helped some of the most advanced and powerful organizations in the world get the right people in the right place. Now, Hogan Configure brings the same game-changing people analytics to you.
Hogan Configure leverages three decades of data to create the only competency-based solution that puts Hogan’s predictive power and scientific rigor at your fingertips. The easy-to-use, three-step process allows employers to create, customize and compare candidates in order to determine their key attributes, qualities and skills.
Competencies are the key to talent. Hogan Configure allows companies to decode that talent, and accurately identify those who will thrive in a particular position, whether it’s a new hire or someone within your organization.
For more information on Hogan Configure, contact your HART consultant.