Monte Carlo Simulation

The Monte Carlo Simulation encompasses “any technique of statistical sampling employed to approximate solutions to quantitative problems” (Monte Carlo Method, 2005). The Monte Carlo method simulates the full system many times, each randomly choosing a value for each variable from its probability distribution. The outcome is a probability distribution of the overall value of the system calculated through the iterations of the model. A standard approach to risk management of projects is outline by Project Management Institute (2004) that includes six processes: Risk Management Planning, Risk Identification, Risk Qualification, Risk Quantification, Risk Response Planning, and Risk Monitoring and Control. Monte Carlo is usually listed as a method to use during the Risk Quantification process to better quantify the risks to the project manager is able to justify a schedule reserve, budget reserve, or both to deal with issues that could adversely affect the project. Monte Carlo simulation, while not widely used in project management, does get some exposure through certain project management practices. This is primarily in the areas of cost and time management to quantify the risk level of a projects budget or planned completion date. In time management, Monte Carlo simulation may be applied to project schedules to quantify the confidence the project manager should have in the target competition date or total project duration. In cost management, the project manger can use this simulation to better understand project budget and estimate final budget at completion. The primary advantage of using Monte Carlo simulation in projects is that it is extremely powerful tool when trying to understand and quantify the potential effects of uncertainty of the project. Monte Carlo simulation aids the project manger in quantifying and justifying