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Missing the Mark: The Hidden Dangers of Survivorship Bias

January 10, 2023
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You can’t be what you can’t see.

LinkedIn is a great online space for the Diversity, Equity and Inclusion (DEI) professional community, and I’m delighted to be connected with so many thousands of professionals in this emerging field across the world. From them, I keep up with current trends, success stories, career trajectories, and everything else this community offers.

There is a trend on LinkedIn particularly, however, that some might call ‘toxic positivity’. While I enjoy a bit of inspiration, there is a tendency online to only post one’s successes – to focus only on the influencers, the ones who have worked and thrived in this field. On the initiatives that have worked, and been successful. On the top companies who do DEI right. 

Who doesn’t love a good success story?  Who wouldn’t want to share their triumphs, more than their mistakes?

Nevertheless, when we only take the good, and only consider what has worked in the past, we run the risk of running into an issue called ‘survivorship bias’.  Let’s talk more about this as it relates to DEI.

On the 13th of December, 1950, Abraham Wald was killed in a plane crash. This will become more relevant shortly.

Abraham Wald was a Hungarian-Jewish mathematician, called upon by the United States Airforce during World War II to work out how to reinforce the bomber aeroplanes returning from missions riddled with bulletholes across their wings and tails, motors and cockpits virtually untouched. How, wondered Command, could the wings and tails be reinforced to prevent bulletholes?

Wald was quick to point out that they were looking at the wrong planes. The point being, there was no information on the planes not returning.

His report read:

“What you should do is reinforce the area around the motors and the cockpit. You should remember that the worst-hit planes never come back. All the data we have come from planes that make it to the bases. You don’t see that the spots with no damage are the worst places to be hit because these planes never come back.”

Abraham Wald

When we focus on successes – the aeroplanes that make it back, the CEOs who build multinational businesses despite overwhelming odds, and indeed, the DEI initiatives that are wildly successful, we’re missing out on much – perhaps even most – of the information that is out there. We talk about success against the odds, and this is the crucial point: many of these success stories are exceptions to the rule.

Survivorship bias also tricks our brains into believing a level of causation that is not necessarily reflective of reality.  We like to believe that people who are successful are successful because of hard work, intelligence and good management – and, it follows, that those who fail are failing because they are poor managers, foolish or lazy. We like to ignore the elements of chance and external circumstances that lead to failure.  

Cultural Infusion’s Diversity Atlas platform designed our inclusive datasets with the intention to leave nobody out. I propose that we extend this intention to the entire DEI field.  

I believe we can learn as much, if not more, from our failures as from our successes, which is lucky because there are plenty of them, from poorly implemented DEI strategies, to DEI manager burnout and large corporations cutting their diversity funding. These are symptoms of wider failures. We need to consider the data we cannot see, as well as the data we can see. In doing so, we can get the bigger picture, and know where to spend our efforts in order to improve.  

If we want to improve our settings and grow as a community of DEI practitioners then it’s time to share what didn’t work and collectively conjecture on why it didn’t work so we can avoid repeating the same mistakes.

On LinkedIn, in Forbes and the Harvard Business Review – everyone is sharing what they find is working. There is much to be gained in uncovering what is not working, too, so more effort is spent reinforcing the weakest parts of our collective aeroplane.  

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