Total Completion Time of the project is = 5,2 +6 + 8 + 3 = 22,2 Months.įor the best case, completion time of the project is PERT Estimate = ( Optimistic Estimate+ 4 x Most likely Estimate + Pessimistic Estimate) / 6Īfter calculating the duration of each activity, the table becomes as follows Then you calculate the duration of each activity by using PERT Formula You estimate optimistic, pessimistic and most likely durations for each activity as shown in the below table. Then you decided to use the Monte Carlo Simulation to analyze the impact of risks that will affect your project.įirst, you create the work schedule and estimate the duration of each activity by using the three-point estimating technique. You noticed that there is some degree of uncertainty exists in the activity duration estimates. Monte Carlo Simulation Exampleįor better understanding, let’s analyze the example below.Īssume that you are creating a work schedule for a research and development project. You can perform the Monte Carlo Simulation for schedule and cost estimates which involve various risks. This method’s main idea is to understand the behavior of a complicated system or process by using random inputs or parameters.
This method is commonly used to tackle a wide range of problems by practitioners in many fields such as finance, engineering, energy, project management, manufacturing, research and development, insurance, transportation, and the environment
#Monte carlo simulation download excel software#
Therefore they think that using computer software is a must to perform the Monte Carlo Simulation. Most of the PMP aspirants find this concept very difficult to understand. It is possible to create various scenarios by changing the range of possibility of risk occurrence.Īlthough the Monte Carlo Simulation is a commonly used technique in risk management, many practitioners are not aware of its importance. This mathematical approach allows considering the impact of risks during a decision making process. The Monte Carlo method was invented in the late 1940s by Stanislaw Ulam, who named it for the city in Monaco famed for its casinos and games of chance. In this article, we will analyze a Monte Carlo Simulation Example to help you to apply this method in your business field. It can be used to overcome a range of problems in almost every field. It is used to model the probability of various outcomes in a project (or process) that cannot easily be estimated because of the intervention of random variables.
The Monte Carlo Simulation is a quantitative risk analysis technique which is used to understand the impact of risk and uncertainty in project management.
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