Similarity-based forecasting methods involve asking individuals to rate how similar a decision or asset is to past decisions or assets. These similarity ratings are then aggregated across individuals using simple statistical procedures to generate forecasts (for revenues, completion time, or costs) depending on the goal. Since these methods rely on past decisions and outcomes, they are a form of case-based decision analysis as well.