Sensitivity analysis determines how sensitive the optimal solution is to changes made to the original linear programming model after obtaining the optimal solution. It is important because it allows analysts to check how changes to the data in the model, such as the coefficients, constraints, or variables, would affect the optimal solution and gives the model dynamic characteristics to handle potential future changes.