Examining Monte Carlo Analysis for Projects
Monte Carlo Analysis is a technique used by Project Managers to make predictions about the optimistic, most likely and pessimistic estimates for variables in the model and simulate various outcomes of the project schedules to a statistical distribution of the calculated results.
In addition to what-if-scenario analytical method, this is the other most common on simulation type. This analysis does not produce a single result but calculates a range of possible results.
In more general business terms, Monte Carlo Analysis refers to not one single analysis method but to a wide class of techniques, mostly making use of sophisticated computers and inputs of random numbers, probabilities and algorithms.
It has a wide range of applications in many fields including finance and engineering because it works effectively with a large input of members. It is well suited for complex project management problems in which more than a few inputs such as costs, activity and duration are unknown.
A typical example…
Stakeholders asked George Allen, a Project Manager to estimate how long it will take to produce a project involving three tasks and inexperienced team. The first task is scheduled to take 30 days; the second task is scheduled to take 60 days, and the third task is scheduled to take 90 days but with inexperienced resources, the task duration is optimistic and could take more time.
Using a software application, George will run a Monte Carlo simulation analysis using these inputs and probability that each task will be completed early on time, and late.
After running the Monte Carlo Analysis repeatedly to generate a range of results, he estimates that this project has a 40% probability of being completed within 170 days, a 60% probability of being completed within 180 days and an 80% probability of being completed within 200 days.
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