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Thomas
@aviationdoctor.eth
Velocity in action and decision making is highly valued these days (Agile methodology, Zuckerberg’s motto “move fast and break things”, etc.). Yet what struck me the most working with a former boss and mentor of mine was how he kept postponing dealing with potential issues in a non-procrastinating way. He would often say things Iike “let’s wait and see”, “we’ll cross that bridge when we get there”, etc. Now that I’m in his shoes / his role, I’ve come to appreciate the value of Falkland’s law: unless you *must* make a decision, don’t make one. Prioritize patience and information gathering over making unnecessary decisions. Not only does it keep your options open for later, it also avoids you having to change your mind and confuse people with new directions. But more notably, I’ve often noticed that problems I was anticipating just… vanished before they could even materialize. The environment, priorities, resources available, constraints, etc had changed enough in the meantime.
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Luigi Stranieri
@luigistranieri
I completely agree. Let me add that I think there is a strong tendency in modern decision-making that does not take into account the objective responsibilities of people who should instead have a more conservative approach to them. As you rightly said, often, long before the problem becomes concrete, other events are added to the solution. Rushing to decide, without thinking about the consequences in the event of an error, or even worse, without making corrections is wrong and reckless.
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Thomas
@aviationdoctor.eth
Related to decision making is the ability to forecast / predict the future state of a given system. Some years ago, I read a book titled Superforecasting, based on a longitudinal academic study done on hundreds of participants who were asked to bet on some future event (Polymarket style, e.g., will Trump be re-elected). They found a bunch of outliers whose superior forecasting performance couldn’t be ascribed to chance. So they looked for reasons behind their talent. The found that these superforecasters (to your last point) had a natural inclination to hold non-binary views (e.g., they’d give a 60% chance to Trump, instead of all-or-nothing), and a Bayesian approach to refining their odds (e.g., modulating that to 55% after last night’s debate). They didn’t let their ego stand in the way of changing or updating their minds. So keeping a fluid and running Bayesian model in their head made them far better forecasters (and thus better decision makers) than everyone else
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