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The 'Survivorship Bias'.

Can you solve this puzzle?

Observing the most commonly shot areas on an aircraft, how would you innovate this design to improve survival rates?



During World War II, engineers considered how to minimize aircraft losses to enemy fire and would examine the damage to aircraft that had returned from missions.

To many it seemed logical to reinforce the aircraft where the most damage had been incurred.

However, a statistician, Abraham Wald, recommended adding armour to the areas that showed the least damage - the opposite solution to what we immediately assume.

The bullet holes in the returning aircraft represented areas where an aircraft could take damage and still fly well enough to return safely to base.

Therefore, Wald proposed they reinforce areas where aircraft were unscathed, inferring that planes shot in those areas were the ones most likely to be lost.

Basically, this diagram studies only the planes that had returned - you don't immediately consider the planes that had been shot down (which you cannot study).

Hence, this decision-making blindspot has been labelled the 'survivorship bias'.


The logic of only studying what is directly in front of us is scarily common within organisations and cripples their potential to innovate effectively.

Leaders relying on quantitative analysis to drive innovation, dismiss 'silent evidence' that isn't on the spreadsheet.

To facilitate effective innovation, creative decision making must be allowed to inform your process in order to drive optimal outcomes.

In this case, reinforcing all the red dots on an aircraft would compound the problem you were looking to solve.

Whether you're innovating aircraft or designing app UX... creative thinking is a free resource and offers unlimited potential for effective solutions.


To learn how I help Executive Leadership Teams leverage their creative intelligence for optimal outcomes, visit my services here...

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