Milena Dutra Kosciuk

There’s confirmation bias, the tendency to focus on data that confirms our hypothesis while over-looking data that could go in the face of it. There’s also HARKing (Hypothesising After The Results are Known), the inclination to believe that surprising data is obvious after the fact and retro-fitting our hypothesis in light of it.

Design like you’re right, test like you’re wrong is a simple encapsulation of the critical thinking required to run trustworthy experiments. We are attuned to our user needs as travelers ourselves, but when making data driven decisions, we have to recognize and guard against the biases that can impact our decision making.

It changes the conversation. When you add ‘thinking’ to the word ‘design, it’s no longer about color or decoration. It’s now about process. It’s about getting to a more intentional outcome. It’s about thinking about the experience of the customer, user, and employee.