Enhance Productivity and Efficiency with Stephen’s Innovation Insights

Innovation Insights by Stephen Shapiro

Today we continue the “Test”” part of the FAST Innovation Model (Focus, Ask, Shift, Test).

In the last video I mentioned the need to focus on experiments. Unfortunately most experiments lead to ultimate failure due to a psychological tendency we have.

Be sure to watch the previous videos!


Today I am going to talk about why the brain is designed to cause you to run faulty experiments, which will ultimately lead to your failure…

In the world of innovation, we seem to think that “Yeah, but…” is the enemy of innovation. But guess what, it’s not!

We need disproving evidence. We need people to prove why maybe our ideas are bad.

The real enemy of innovation is the, “Wow! This is a great idea.” Here’s why…

When you believe you have a great idea, the brain kicks in. It’s called confirmation bias. What ends up happening is the brain finds all the reasons why your idea is a great idea, and all of the evidence that proves it’s a bad idea gets rejected.

This is what confirmation bias is all about. And so, what we need to do is recognize that the brain is not designed to be our friend when it comes to our experiments.

When we have a strong belief that this is a great idea, we will run experiments that are going to prove that it is (a great idea), when, in fact, it might not be, leading to failure.

One of my favorite quotes, when it comes to innovation, is from Scott Cook at Intuit. He said, “For each of our failures, we had spreadsheets that looked awesome.” I absolutely love that quote, and it is the reason why failures actually happen. We can justify anything. We can create spreadsheets to justify our beliefs.

But if our beliefs are built on faulty assumptions, it’s not going to be successful. Confirmation bias is the reason why we tend to run very poor experiments, because we want to believe what our ideas are and that they’re great.

In the next episode, I’m going to talk about some specific techniques you can use to overcome confirmation bias, to help you run better experiments.

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