Deciding with only a wristwach in thick fog
When uncertainty thickens and time gets short, decision-making becomes a struggle. Different schools of thought collide: rationalists, intuitionists, data believers, champions of tactical agility. Should we build models, trust our gut, delegate to machines, or simplify to the extreme? Here’s a cross-cutting overview to help you stay in control—even in the fog and under pressure.
Black Swan, (2010) ; Antifragile: Things That Gain from Disorder, (2012) by Nassim Nicholas Taleb
Thinking, Fast and Slow, by Daniel Kahneman (2011)
Blink: The Power of Thinking Without Thinking, by Malcolm Gladwell (2005)
The Signal and the Noise, by Nate Silver (2012)
Willpower: Rediscovering the Greatest Human Strength, by Roy Baumeister & John Tierney (2011)
Superforecasting: The Art and Science of Prediction, by Philip Tetlock & Dan Gardner (2015)
The Paradox of Choice, by Barry Schwartz (2004)
1. Predict the unpredictable… without drowning in it
Uncertainty is often framed as a math problem to be solved. Since Blaise Pascal and his “expected value” theory, rational decision-makers have tried to tame unpredictability with probability. While it’s impossible to foresee everything—our brains simply can’t process all available information (as Herbert Simon’s theory of bounded rationality reminds us)—we can still estimate risks and decide accordingly. The smartest path? Choose the option with tolerable error costs, and favor two-way doors over one-way bets.
Blind spot: models help—until the day they fall apart. History is full of examples where top-tier probabilistic models collapsed under the weight of the unexpected. In 2008, financial models claimed the subprime crisis was “near impossible”… and yet it happened.
2. Trained instinct: the misunderstood genius
Popularized by Malcolm Gladwell in Blink, the intuitionist school champions a simple idea: the human brain, a true parallel-processing machine, can instantly assess thousands of variables and produce an answer—without us realizing it. In other words, the best decision is often the one made in a split second, without overthinking it. Pilots, emergency doctors, firefighters: they recognize patterns before they can explain them.
Blind spot: instinct outside its home ground is a recipe for disaster. Daniel Kahneman, Nobel laureate and pioneer of the heuristics and cognitive bias theory, reminds us that our brain loves shortcuts—some of which mean riding for a fall. Instinct works well when you’re an expert. But when you’re not? You’re inviting disaster.
3. The algorithm is always right (until it isn’t)
Some advocate for the supremacy of data and mathematical models. Human judgment—riddled with biases and emotional noise—should give precedence to algorithms, with their consistency and statistical precision. In fields like finance, aviation, and medicine, algorithms often outperform human experts: in medicine, for instance, AI-assisted diagnostics are beginning to prove more reliable than those of top radiologists.
Blind spot: Algorithms do make mistakes—sometimes spectacular ones. Who decides which data they’re fed? Who monitors their errors? And above all, in a crisis, can we really wait for a model to tell us what to do? In 2009, Captain Chesley Sullenberger didn’t ask an algorithm for its advice before making an emergency landing on the Hudson River.
4. Embark on tight loops: Observe, Orient, Decide, Act
Others advocate a more flexible approach. Inspired by military strategy, John Boyd’s OODA loop—Observe, Orient, Decide, Act—prioritizes learning speed over initial perfection. It’s about cycling through decisions quickly, adjusting on the fly, and keeping feedback loops short and tight. The goal isn’t to be right from the start, but to adapt faster than the competition. Without real-time learning, though, the method is just an empty slogan.
Blind spot: the model assumes the ability to analyze quickly and adjust decisions continuously. But in a sudden crisis, there may be no time to cycle through the loop…
5. Chaos as a playground
Nassim Nicholas Taleb, one of the most influential thinkers on uncertainty, suggests a different take: instead of trying to predict the unpredictable, we should build systems that thrive on chaos. This is the core of his concept of antifragility: the smartest strategy isn’t control, but resilience. That means diversifying revenue streams, testing options without risking it all, and developing the ability to adapt fast. A rigid company breaks at the first shock, while a nimble startup that can pivot turns a crisis into a growth opportunity.
Blind spot: Antifragility is an uncomfortable stance. It requires embracing failure and letting go of the illusion of control. Yet most leaders, investors, and policymakers are trained to chase stability—not to welcome chaos.
6. The minimalist option: wait and see
What if, in the face of uncertainty, the best decision was… to hold off on making one? This is the gist of the Chinese philosopher Lao Tzu’s quote: “Practice not-doing, and everything will fall into place.” Instead of charging headfirst into the unknown, wait for clarity to emerge. It’s a common approach in geopolitics and management: when the situation is too unstable, staying still may be the smartest move to avoid making things worse.
Blind spot: inaction can quickly turn into decision paralysis. Barry Schwartz, in The Paradox of Choice, describes how too much uncertainty and too many options often lead to inaction—sometimes with worse consequences than making the wrong call.
7. So, what do we do?
Too many options kill clarity. Faced with uncertainty, some people stop deciding altogether. Decision fatigue wears down mental sharpness: the more choices we have to make, the more our brain gets exhausted — resulting in procrastination or random choices. That’s why Barack Obama only wore grey or blue suits: it helped preserve his mental energy for more strategic decisions. Add in the Dunning-Kruger effect1 (where the least competent overestimate their abilities) and a culture of overthinking, and you’ve got the perfect recipe for paralysis.
Blind spot: too many options, too much doubt = paralysis.
“It is better to make an imperfect decision than to remain indecisive in the illusion of perfection.” — General de Gaulle.
Whatever the case, the best approach depends on the context: if you’re an expert and the decision must be made in a split second, intuition is your best ally. If you have time and reliable data, let the numbers speak. If you’re in a fast-changing environment, the OODA model will help you adjust your decisions in real time.
Think of three simple tactics: reduce the number of choices, standardize routine decisions, and save cognitive energy for decisions that truly matter. And when the game gets messy, strategic minimalism — wait, observe — can help avoid costly mistakes, without ever turning into a doctrine of inaction.
Because in times of uncertainty and pressure, the worst decision is no decision at all. Prioritize reversible actions and rapid learning by combining trained judgment with statistical tools. There’s nothing wrong with pausing when the fog is thick — but remaining inside it is not an option. Act, adapt, learn — then do it again.
In practice: 7 moves to decide better and faster
- Embrace the fog – aim for what gets you moving, not for certainty.
- Maximize reversible decisions – avoid one-way doors whenever possible.
- Run short OODA loops with real-world feedback metrics.
- Sharpen intuition through training and tight debriefs.
- Keep algorithms under human control – with data audits and stress-test scenarios.
- Build antifragility – diversify bets, start small, allow for fast failure.
- Ease complexity – limit options, create routines that save cognitive energy.
Reminder: 5 Major barriers to climate action
You know the numbers. You’ve read the IPCC reports. You see your competitors making bold commitments. And yet, inside your leadership team, action is stalling. Why? Because the real hurdle isn’t rational—it’s psychological, structural, and strategic. You don’t have a data problem. You have a mindset problem. A decision paralysis problem.
Short-term obsession, fear of learning, the belief that change is pointless unless collective, the gap between personal values and professional decisions, and the trap of so-called realism — these five barriers feed inaction. Breaking free starts with a decision: dare to transform, disrupt, choose a bold course — and stick to it.
See also: “5 Major Barriers to Climate Action (and How to Break Them)”, Business Digest No. 327, Spring 2025.
- The Dunning-Kruger effect, also known as the overconfidence effect, is a cognitive bias whereby the least competent individuals in a group tend to overestimate their abilities in a given domain. (Wikipedia) ↩︎
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