Monte Carlo Simulation Modelling

Monte Carlo Simulation analysis is a form of modelling which quantifies risk associated with a project or investment decision. By explicitly incorporating uncertainty into model variables by allowing a range of outcomes in any given model run, and running the model thousands of times, Monte Carlo modelling can assist stakeholders make better decisions by understanding the risk associated with an investment. 

While Monte Carlo modelling is already required in some project assessment processes, such as construction cost estimations, it can be applied more broadly. At the early stages of a decision-making process, where inputs and assumptions are often based on initial information or data, Monte Carlo modelling can improve the completeness and integrity of modelled outputs.

When applying Monte Carlo modelling it is important to consider the following:

• Is the model structured correctly? A poorly structured model will not capture the benefits of the analysis.
• Do the probability distributions match the data or information? There is a range of probability distributions available including those ‘fitted’ to historical data.
• Do the correlation assumptions reflect the relationship between inputs? For example, which variables are independent and which are supplementary?
• Do the outputs make sense? The outputs should reflect your understanding of the project.