The management library: Black Swan

Author: Nassim Nicholas Taleb
Links: goodreads, wikipedia, twitter

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I’ve heard a lot of things about Black Swan, a major commercial success in 2007, mostly in the startups universes. Many blog posts today are now praising the importance of failures, and that your success can be defined as unpredictable and potentially huge.

If you’ve never heard about Black Swan events (uppercase characters really matter), here are some elements to define them based on Taleb’s description:

  • An event that you can’t predict
  • This event has a massive effect
  • You can retrospectively predict and understand the event based on input data

Such events are named Black Swan due to the following metaphor: if you only see white swans and state that all swans are white, as a global and irrefutable statement, then your precision and accurate law will be astonished once a black swan will be observed for the first time.

The author has a deep rancor against those who try to predict the future, such as traders or economists. According to Nicolas Taleb, this is nothing different than roughly estimating small changes day after day, changes that everyone could do by reading basic Gaussian curves.

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Bell curves, For The Win, or For Being Wrong?

About Gaussian curves, by the way, I’d pay a lot to know what this dear Carl Friedrich Gauss would have thought about this book. Even if Taleb does not directly criticize the tool itself, but rather all the wrong usages of it, this sounds that he wants us understand that nothing can be purely modelized as a Bell curve.

This is exactly my main motivation to write an advanced review: this book is balanced between sciences, mathematics, philosophy, and prediction. You can find philosophical point of views about linear regressions or least-square sums. Mixing these different angles of science is definitely a great source of open-mindedness.

Prediction, not narration, is the real test of our understanding of the world.

This can sound as a side topic not strongly linked with management but I see at least a couple of points that definitely deserve to be considered in my opinion.

Another interesting developed angle was the psychological one. Taleb states, for example:

Plenty of mildly good news is preferable to one single lump of great news.

This is obvious that you can probably [try to] apply these statement to your own experience. I can’t say he’s right or not, but when managing the massive information stream we have to handle in our era, it’s relevant to take 2 minutes to have this kind of considerations about impacts of positive messages. A better understanding about psychological aspects of human behavior can give you great insights when thinking about your communication. Another interesting quote:

In order to make a decision you need to focus on the consequences (which you can know) rather than the probability.

This article is by far too short to explain all the great theories described by Taleb in his book, but you’ll probably love to learn more about the shared ideas. Those who are about to launch their business (or are already in charge) and have to take data-driven decisions, dealing with probabilities and impacts, will for sure find a decent mindset to consider. It offers a genuine way to examine differently external opinions that often appear to be too… well, common? (you know, all the stuff about good or bad idea, market studies, “you’re crazy this will never happen!”, etc.)

I have to admit that by these last 6 years I felt very interested in philosophy aspect of modern sciences. It’s interesting to see how intuition and interconnections between thinkers play a role in major theories. This was another reason which made me read Black Swan.

All along the pages, Taleb will tell you many short stories about idiocies, role played by charlatans. I strongly hope this can make some managers pay more attention to pseudo-scientific arguments that could be raised in meetings, by statistics specialists for example. Even if you disagree with him — and I did more than once — you’ll inevitably think a lot about all of this, and that’s a pleasant part to develop your own point of view.

You have to be prepared to fight against very rough arguments and point of views. There are even some aversions against TED in this book! (“a monstrosity that turns scientists and thinkers into low-level entertainers […]”). In a nutshell, I’d definitely recommend this book to everyone, but mostly for those who feel very confident in statistics, market studies or scholar theories related to figures and charts.

Electronic Music artist as Paranormind. Photography. Computer Science. Machine Learning & Data-related things.

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