Strategic Thinking & Strategic Action

Fostering strategic thinking and strategic action by organizational leaders since 2007.

Remember, history is written by the survivors
Decision biases cases Lee Crumbaugh Decision biases cases Lee Crumbaugh

Remember, history is written by the survivors

We are urged to learn from history. But what if the history is biased? Here’s a case showing how slanted history can lead to bad decisions. In the Cuban Missile Crisis, U.S. advisors were mislead by the fallacy of silent evidence, that is, not seeing the full story when looking at history, just seeing the rosier parts of the process reported by the “winners.” U.S. policy was tragically misguided because of survivorship bias, that is, concentrating on and giving undue credit to the people, things or interpretations that "survived" the process and inadvertently overlooking those that didn't because of their invisibility.

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Beliefs about a group matter
Decision biases cases Lee Crumbaugh Decision biases cases Lee Crumbaugh

Beliefs about a group matter

Here’s a story about what can go wrong when we hold beliefs about a group and attribute these beliefs to the members of the group. The Battle of Little Bighorn, also called Custer's Last Stand, took place in Montana Territory on June 25-26, 1876, between the Lakota, Northern Cheyenne, and Arapaho tribes and the 7th Cavalry Regiment of the U.S. Army. The Battle of the Little Bighorn was a stunning victory for the Native Americans. The 7th Cavalry, casualties numbered 268 dead, including Custer, and 55 wounded. How Custer viewed the Indians opposing him led him astray.

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Not knowing we don’t know
Decision biases cases Lee Crumbaugh Decision biases cases Lee Crumbaugh

Not knowing we don’t know

To lack relevant knowledge without realizing it can have disastrous consequences. Consider, for example, the underestimation of the risk of a nuclear accident when constructing the Fukushima Daiichi Nuclear Power Plant power plant in Japan. The Fukushima Daiichi Nuclear Power Plant disaster offers a stark example of what can go wrong when we rely on a small and biased sample of data.

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