Among the many qualities that distinguish successful leaders from millions of less-successful executives in the world is an awareness of the limits of their knowledge. They know what they know, they appreciate what they don't know, and they have a healthy respect for what they don't know they don't know. In short, they have great meta-knowledge.
Meta-knowledge can be thought of as a lack of hubris, an intellectual humility of sorts. Those who see the world probabilistically seem to better navigate volatile environments because they are wired to embrace uncertainty. They understand that they don't know anything with 100% certainty and are therefore open to ideas different from their own.
The psychologists Daniel Kahneman and Amos Tversky demonstrated quite convincingly that we human beings are not the model-optimizing "rational" actors that many economists historically believed we are. One of their key findings was that humans are consistently overconfident, suggesting that we generally have poor meta-knowledge. We tend to think we know more than we actually know. A corollary of this result is that we also tend not to know what we do not know.
In my experience, experts are among the least successful predictors in times of massive uncertainty. This is not to suggest that experts don't have significant and valuable knowledge; quite the opposite, they likely do. Rather, it implies that they think they know more than they actually do and therefore exhibit more confidence than is warranted. The result: a significant number of very visible expert predictions have gone embarrassingly wrong.
Consider for instance, two books that made it to the top of the bestseller lists: The Population Bomb and The Great Depression of 1990. The first, by Stanford biologist Paul Ehrlich, noted in 1968 that "the battle to feed all of humanity is over...in the 1970s, the world will undergo famines — hundreds of millions of people will starve to death...." Ehrlich failed to appreciate the possibilities of the "Green Revolution" which dramatically increased agriculture's productivity. Incidentally, the green revolution was already underway when Ehrlich wrote his book, he just didn't grasp the potential impact. The Great Depression of 1990, by Southern Methodist University economist Ravi Batra (which stayed on the bestseller list for 10 months in hardcover and over 19 months as a paperback), totally missed the technological developments that made the 1990s among the most productive decades ever.
Lest we conclude it's only doomsday experts that miss the mark, it's worth highlighting that Yale economist Irving Fisher noted on October 17, 1929 that "stocks prices have reached what appears to be a permanently high plateau," a mere days before the Great Crash welcomed the Great Depression. And of course, there's James Glassmann and Kevin Haskett's Dow 36,000, published in 1999, mere months before the Dow Jones Industrial Average began a slow, long, and painful decline.
Many of these "experts" adopted single-discipline approaches to developing insights; they were, to use the language of my prior HBR blog post, "specialists." They were truly knowledgeable within their domain, but it was often developments outside of their domain that derailed their predictions. They failed, it seems, to have a broad enough perspective.
Generalists, on the other hand, are those who have broad knowledge but lack deep domain expertise. Most generalists do not claim to be expert at anything, making them psychologically more receptive to ideas distant or different from their own. They are, it seems, more aware of what they do not know and understand that there is a large body of information that they do not know they do not know.
Why does this matter? When facing massive uncertainty, as exists in today's highly interconnected global economy, it is essential to appreciate both what one does know as well as what one does not know. Such logic is not shocking, but it has significant ramifications for how one should manage his or her career, and how organizations should manage their human resources. Specifically, the best decision-makers (i.e. leaders) in times of uncertainty are likely to be those who possess above-average skepticism and intellectual humility. Individuals should therefore seek career paths that constantly put them in unfamiliar roles and through which they can learn what they don't know. The feedback one receives through these roles will likely improve one's intellectual self-awareness.
Another interesting implication is that specialists and experts should be seen as resources to tap into when needed. They have a very valuable role to play; it just may not be as a leader. (Of course, the ideal would be to develop expertise in dozens of domains en route to becoming a leader, but that may make for a very long career trajectory.) My friend Michael W. Sonnenfeldt, founder of Tiger21, a peer-to-peer education group for high-net worth individuals, has eloquently observed a key insight: "Many of us have learned it's best to keep experts on tap, not on top."