The focus of this workshop is how to improve model performance and confidence in model results . First, we look at the process of matrix generation and the clues it provides about your model: Are your outputs being calculated correctly? Do you have missing yields? Is your model needlessly large because of landscape themes that provide no value? Are all your actions being considered? Next, we look at strategies for debugging your model, and finding errors in syntax and logic: Are the transitions creating development types that lack yields? How do you know if a development type is linking to the correct yield table? Finally, we look at various reports and assorted tips that can be used to track down hard-to-find problems in your models.