Black Swans in our Supply Chain I

 

Summary of the Book ‘The Black Swan” by Nassim Nicholas Taleb

1. "Black swans" are highly consequential but unlikely events that are easily explainable – but only in retrospect.

2. Black swans have shaped the history of technology, science, business and culture.

3. As the world gets more connected, black swans are becoming more consequential.

4. The human mind is subject to numerous blind spots, illusions and biases.

5. One of the most pernicious biases is misusing standard statistical tools, such as the “bell curve,” that ignore black swans.

6. Other statistical tools, such as the "power-law distribution," are far better at modeling many important phenomena.

7. Expert advice is often useless.

8. Most forecasting is pseudoscience.

9. You can retrain yourself to overcome your cognitive biases and to appreciate randomness. But it's not easy.

10. You can hedge against negative black swans while benefiting from positive ones.

Could the Tail Wag the Dog?

Taleb claims that Black Swans are unlikely events explainable only in retrospect. His statement seems to be true, but does it have to be so? Taleb also claims that power-law distribution and other statistical tools are better suited to explain many important phenomena, while the often used normal curve is not. Combining the two statements leads me to speculate that opportunity lies in the tail of a (statistical) distribution. While everyone focuses on the majority of the outcomes – the “big pile”, maybe we should pay attention to the tail.

Goldratt relates an excellent (historical) example. Automobiles. Back in the 50ies and 60ies automobile quality was poor. Even then the automobile manufacturers did analyse sales and customer satisfaction statistics. These statistics showed that the vast majority of car owners were satisfied with their purchase - except for a very few. As Goldratt relates it .2% indicated strong dissatisfaction with the quality of cars they owned. Such a small part of the population complained that to improve quality was not even considered important by most manufacturers.

As we now know this was not a good decision. What probably happened is a smart Japanese or German or both looked at this distribution and understood the dissatisfaction of those extremely critical people way out there in the tail. If those people expressed their dissatisfaction, then everyone else might have the same problem – those people did not know that much better quality is possible – they did not complain. They accepted the level of quality as normal. (It’s like the story about how to cook a frog. If you throw a frog into boiling water he will immediately leap out again. However if you put him in at room temperature and then slowly raise the water’s temperature he will enjoy the nice warm bath and become more and more lethargic. Eventually he is so sleepy, so dopey, that he forgets to jump out and is cooked – just like the western automobile industry was.)

The Japanese started to build quality cars and export them to the West. Some few people frustrated with poor quality bought them - after all the prices of Japanese products were low. Probably none of these people expected superb quality – Deming, Juran and others were not known yet. These first customers were pleasantly surprised. Japanese cars are really good. They spread the story and a trickle of sales became the flood we all know about. The rest is history (despite Toyota’s recent difficulties with brake pedals).

Maybe we need to learn where to look for the Black Swan. He certainly does NOT lurk in the big heap. Don’t blame 6-Sigma or TQM – outliers and skewed distributions are part of the subject matter. We are at fault – is it because we feel safe in the big heap?

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