*6.3.1 Scenario technique: Monte Carlo simulation*

The Monte Carlo method is based on statistics which are used in a simulation to assess the risks. This is a statistical technique whereby randomly generated data is used within predetermined parameters and produce realistic project outcomes. The overall project outcome is predicted by randomly simulating a combination of values for each risk and repeating the calculation a number of times and all outcomes are recorded. After completing the simulations required, the average is drawn from all of the outcomes, which will constitute the forecast for the risk. It is important to realise that parameters and appropriate distribution within which the random data is simulated is itself a series of subjective inputs. Accurate and realistic project outcomes will not be generated if inaccurate parameters are set. Different scenarios are generated by simulation are used for forecasting, estimations and risk analysis. Data from already executed projects is normally collected for simulation purpose. The data for variables is presented in terms of pessimistic, most likely and optimistic scenarios depending upon the risks encountered, i.e. pessimistic value means lot of risks and optimistic value means least risks. The result from this method is a probability of a risk to occur is often expressed as percentage. The most common way of performing the Monte Carlo simulation is to use the program Risk Simulator Palisade Software, where more efficient simulations can be performed.
