The point is that simpler explanations are more likely to be the better choice than complicated and lengthy explanations. The simpler something is, the easier it is to follow and there is less room for mistakes. Complicated explanations are more likely to make mistakes. This is of course when both theories explain the data or situation equally well. For example, if you walk into the kitchen and the cat food has been spilled and divided on the floor, you will need to evaluate the different explanations. If between two explanations, the cat jumped on the counter and knocked it over or the dog unlocked its kennel, pushed a chair towards the counter and then jumped on the counter, this tool advises you to opt for the first option . Both explanations are reasonable and would explain what happened, but the first explains it less.