A Nobel Prize-winning psychologist explains why it's nearly impossible to hire the perfect person for every job

When Daniel Kahneman was 22 years old, he was hired by the Israeli Defense Forces to help improve their interviewing process for new recruits.

The system he designed required interviewers to measure young men on six dimensions in a specific order, and only then use their intuition to imagine what kind of soldiers the men would make.

Sixty years later, the system is still in place - a testament to the power of structured interviews in predicting performance on the job.

Yet Kahneman, a psychologist who won a Nobel Prize in 2002 for his pioneering work in the field of behavioral economics, says there's a limit to our ability to make these kinds of judgments.

In an interview with Dan Pink at the Wharton People Analytics Conference on April 7, Kahneman explained that some portion of people's job performance is unpredictable - and we'll probably never be able to pick the perfect candidate for every position.

He cited Google as an example of a company that uses structured interviews and takes pains to make hiring decisions that are as accurate as possible. For example, Google has multiple people evaluate each candidate, so as to reduce the influence of one person's faulty judgment.

"I don't feel that psychologists have much to tell Google that it doesn't know," he said.

At some point, he added, "the problem is not that we're poor at predicting; the problem may be that [performance is] unpredictable."

"There are chaotic interactions between the characteristics of the individual and the events that happen to them on the job that change them and that change the way they are viewed and treated by other people."

There is no way, he said, that by further testing the individual you can achieve greater accuracy.

In other words, organizations should use the most advanced systems they can - but should also accept that human behavior will never be 100% knowable.

In terms of guessing how people will perform on the job, he said, "whether we can do radically better than we are doing now, I'm quite skeptical."