Integration of scenarios and Monte Carlo simulation in risk analysis

To make good decisions, it is necessary to consider future consequences of decision alternatives. Monte Carlo simulation is typically used in a very narrow way without consideration of different courses of action. To broaden the perspective, we propose integration of scenarios and Monte Carlo simulation. Scenarios differ in variables or in values of the variables. Key outputs are probability distributions of each scenario and total probability distribution including statistical characteristics which offer enough information to make decisions. Sensitivity analysis identifies the most important key factors for each scenario which enables effective measures to reduce risks. Described proposition of integration of scenarios and Monte Carlo simulation is demonstrated on example of production expansion capacity in the pharmaceutical company with three scenarios. The main outputs are displayed and described.