Introducing Failure Bias

Most people and organisations suffer from confirmation bias. Confirmation bias prevents us from learning, it means that we seek out information that confirms our belief, and fail to learn as a result. If you or your organisation want to learn, you need to develop a failure bias. A failure bias means that you seek out information that confirms our beliefs are wrong, or have failed. This does not mean we seek to fail but rather we seek the information that we may have failed.

The consequences of the failure bias are:

1. We actively look for information that refute our beliefs. We need to see failure.
2. We construct experiments that optimise our learning rather than prove that we are right.

Seeing Failure

Our natural inclination is to seek information that confirms our beliefs. Unfortunately, confirmation bias is a subconscious activity. We are unconsciously competent in the beliefs we trust the most. This means that we must put a great deal of effort into spotting things that refute our beliefs. Even more than that, we must construct strategies that even allow us to perceive the information that refutes our beliefs. This is the heart of the “Break the Model” part of Feature Injection.

Optimising Learning

Claude Shannon’s information theory tells is that learning is greatest when uncertainty is greatest. We learn the most when the chances of success are 50/50. When developing products we have two phases, the first is to learn about our customers, and the second is to exploit that learning. During the learning phase, the experiments should be focused on learning (50/50) rather than confirming our belief. This is a huge challenge in risk averse cultures where failure is not tolerated. Executives in risk averse cultures should focus to ensure that there is a healthy balance of failure and success. During the learning phase they should ensure that confirmation bias does not obliterate learning. Given the nature of risk averse cultures, they should hold up a lack of failure during the learning phase as the worst kind of failure.

The failure bias is what separates startups from traditional organisations. It also separates those that will survive from those that will not.