Confirmation Bias

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I’ve always been fascinated by confirmation bias

The human minds ability to seek out only information supporting our preconceived hypotheses, while ignoring contradictory information, is impressive. All of us are susceptible to this, and it’s incredibly challenging to mitigate confirmation bias when we are evaluating information. 

We live in biased bubbles where it’s easy to confirm what we believe to be true by using “credible” data sources.

Our search inputs are biased.

The algorithms we rely on to serve up information are biased.

The information sources we get data from are inherently biased. 

You almost need to go out of your way and spend extra time in order to find information that contradicts your internal beliefs.

I recently saw a fascinating example of confirmation bias in action related to the WeWork IPO. After my last post, I had a handful of folks send me Ben Thompson’s take from Stratechery. It was great.

Ben makes a compelling argument for why WeWork is the real estate equivalent of AWS and a viable long-term business.  Side note – this is brilliant positioning, and WeWork should have hired Ben to write their S1 positioning points. See my prior post on positioning here.

I wasn’t the only person who found his post compelling.

So many people, eager to find data to support WeWork’s imminent success, cited Ben’s post and the AWS comparison. However, nearly all of these same people ignored the warnings, and negative feedback permeating throughout Ben’s post.

Ben even felt compelled to follow-up in a second post saying something to the effect of “hey guys, did you read the rest of what I wrote? I think you missed my point. This company is still a shit show. Here let me show you.”

From an analytical standpoint, confirmation bias often sneaks up because we conduct analyses with preconceived frameworks and conclusions. 

For example, when evaluating the value our products provide customers, most of us approach this exercise with the lens of: “How do I prove that my customers are receiving value.” 

This lens frames the entire analysis with a bias. If you are looking data that shows your customers receive value, you will probably find them.  But in an effort to prove value, you miss red flags that indicate major issues with your product.

We have to challenge ourselves and our teams to look at information with an objective view and challenge our own confirmation biases.

Unfortunately, this is much easier said than done.

That’s all for today. Have a great weekend everyone!

Danielle

About the author

Danielle O'Rourke

Recovering Investor. Mom. Wife.

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Danielle O'Rourke

Recovering Investor. Mom. Wife.

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