When solving an optimization model, it is often useful to understand the sensitivity of the computed solution to changes in the inputs. How would profits be affected if the price of a particular raw material increased significantly? Would I still be able to satisfy customer orders if one of my machines broke down? The most general form of this problem would fall into the domain of stochastic or robust optimization, but those fields bring significant complexity with them. The Gurobi Optimizer includes scenario analysis features that have a much more modest goal: to allow the user to specify a set of scenarios, and to compute optimal solutions for all of these scenarios as quickly as possible. These solutions often provide significant insight into how the solution would change as inputs vary.