How do we decide which assumptions warrant the most attention and should be tested vigorously? Jon Fjeld was a long-time tech industry executive, and he now teaches at Duke's Fuqua School of Business. He has a simple method for determining which assumptions need to be scrutinized first. He argues that three factors are critical:
1. Severity: How big is the impact on the project if the assumption is not true?
2. Probability: How likely is it that the assumption is not true?
3. Cost: How expensive and time consuming is it to test the assumption?
Fjeld uses these three factors to create a simple ratio that can be used to rank your assumptions. His equation is: (Severity x Probability)/Cost. The higher the ratio, the more important it is that your prioritize the testing and validation of that assumption. While we don't actually have a clear way to quantify these three factors, the concept of this ratio makes good sense. By thinking about these three factors, and their relationship to one another, we can do a better job of deciding how we want to test, experiment, and prototype before making a big bet.



