January is typically awash with analysts’ forecasts, predictions and prognostications. As the month ended, I was left not with admiration for the perspicacity of any of these punters but bewilderment at their misguided confidence.
Wondering whether this feeling was grounded in anything substantial, I used our AI-driven iN/Ntelligence platform, which trawls news and media sources and sorts text and video content by topic and keyword, to look for recent (non-sports-related) predictions, forecasts and outlooks – and to see which of these included references to doubt or uncertainty.
Among the top ten topics covered in such forecasts, in only one – inflation – did a majority of predictions (nearly two-thirds) also include references to doubt or uncertainty. Some two-fifths of people talking about China also seemed at least somewhat unsure of themselves. But on most topics the percentage of content that also referenced doubt was in single digits.
Top 10 topics* in news and media predictions, forecasts and outlooks from 1 December 2023 to 31 Jan 2024, ranked by proportion of results including “doubt” or “uncertain/uncertainty"
Source: iN/Ntelligence. *By volume, i.e. how frequently topic is tagged in content with heading that includes “prediction” or “forecast” or “outlook”, published within date range by top 100 global news and media sources (by traffic volume). Results include finance or geographic topics only.
This conviction is surprising given the volatile situation facing global markets, as various crises threaten to derail economic growth. A recent survey of economists by the WEF showed 53% thought the global economy would weaken in 2024, while 43% thought it would maintain or gain momentum. The more the horizon clouds over, the harder certainty is to justify.
The iN/Ntellligence data is a relatively crude measure of certainty, I admit, but a revealing one. The world of thought leadership seems to be populated by people who are very sure of themselves. Absolute certainty is often deemed a signifier of authority, and in today’s content-saturated world, some see arrogance as a necessity.
Few would agree with Reuters Breakingviews’ Peter Thal Larsen, who admitted while promoting the group’s annual set of predictions for the year ahead that “accuracy is not the objective”. Such honesty is rare. But I think it’s time to acknowledge the value of uncertainty, not least as a means of reinforcing the appeal of what you say.
Benjamin Franklin was right
Of course, businesspeople exude self-assurance because there is often money riding on whether their interlocutors believe them. They think they can’t afford to admit doubt, or prevaricate. Investors speak of “high conviction” positions, not punts based on guesswork.
Yet if you asked them to be honest, most people would admit they are never entirely certain about anything (apart from death and taxes, as Franklin quipped). And while hedging your language too often can make for weak prose, dogmatism is equally as liable to be seen as bluster as it is expertise – at least among the type of thoughtful audiences our B2B clients are trying to reach (I make no confident assertions about what draws some people to support extreme political views.)
Indeed, among discerning audiences, you are likely to win more respect from recognising uncertainty than from pretending you know everything. In this, it helps to acknowledge first that you can’t know everything, and second that pretty much everything is probabilistic.
When is good enough enough?
Aswath Damodaran, a professor of finance at NYU (and possibly the best lecturer I’ve had the privilege of learning from) neatly summed up the first point in his most recent annual data update, on risk:
“Know when to stop digging for data: In a world where data is plentiful and analytical tools are accessible, it is easy to put off a decision or a final analysis, with the excuse that you need to collect more information… It is therefore healthy to know when to stop researching, accepting that your analysis is always a work-in-progress and that decisions have to be made in the face of uncertainty.” [Italics added.]
That he tackles this ambiguity head-on is a small part of what makes him a fantastic teacher, subtly adding credence to the rest of his analysis. His point is also a foundation of productivity: if you keep digging for more data in a desperate attempt to increase certainty, you never get around to doing anything.
Some axioms of effective thought leadership follow: know when you know enough, and don’t try to convince people you know it all. Of course it’s always possible to continue your research, speak to more people, read more books, watch more informative YouTube videos… But at some point you must decide you have enough, even if you don’t know “the full story”.
If the universe is chaotic... so are you
Indeed, there is likely to be no way of getting to the full story, so claims to know the whole truth are almost always suspect. Absolute certainty isn’t to be found even in ostensibly deterministic systems such as the movement of the stars and the planets. It turns out that even this is chaotic to some degree, so predictions about the movements of celestial bodies must still be probabilistic.
By the same token, chaotic results can stem from simple, axiomatic rules. Even something as elementary as a double pendulum will never move in the same way twice. From such premises arise novel emergent (that is, unpredicted) properties of systems like AI large language models, as well as intractable problems like the impossibility of predicting weather patterns.
In the face of such uncertainty, it pays to demonstrate a touch of humility, presenting the strongest possible case you can but also admitting where your knowledge, experience or research hits its limits. Doing so will make your audience much more likely to trust you when you do make a strong point. And when you are wrong – as we all must be, from time to time – there are two benefits: you will look less foolish admitting it, and people will be more likely to believe you when you say you will learn from your mistakes.
But then again, I may be wrong.
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