BJ Fogg’s Inverted Behavior Model

If you haven’t checked out BJ Fogg’s work on behavior design, do it. What is most fascinating in his research is his “formula” for behavior.

If you’ve ever tried applying this formula to design specifically for an intended behavior, you’ll know that it is pretty fun and extremely powerful. Essentially, Fogg is advocating that an intended behavior will only happen if there is enough motivation from the users, if their ability to accomplish the behavior is sufficient, and if there is a prompt for them to do so. When applying it to forecasting, we can invert it so instead of trying to design for an intended behavior, we can leverage the formula to predict any unknown or unintended behaviors, and then forecast what consequences that behavior might trigger.

Start out listing out the prompts for which you want to forecast. These can be features or they can be holistic products. Then write out the motivating factors that might come into play with that prompt. With those two categories, try predicting some behaviors that might result. After, try to analyze and see what consequences might result from those behaviors. You can also calculate the ability levels for those behaviors to happen, and rank them from most likely to occur to least likely to occur. You can also play with ranking by the severity of the behaviors you’ve generated.