If you are looking to introduce a higher level of strategic and risk management to your business, you need to be aware of the Monte Carlo analysis (otherwise known as Monte Carlo simulation). The Monte Carlo simulation is a risk analysis technique which is used to identify the quantitative risk level of a project or a business.

Most books and articles don’t talk about this technique in depth, because it is quite a complex risk analysis technique, which requires aid from software.

What Is Monte Carlo Simulation?

The modern(-ish) version of Monte Carlo analysis has quite dark beginnings. It was designed by Stanislaw Ulam in the late 1940s while he was working on nuclear weapons projects at the Los Alamos National Laboratory. This idea came while he was investigating radiation shielding and the distance that neutrons would likely travel through various materials. Despite having most of the necessary data, physicists were still unable to solve the problem using conventional mathematical methods. So, came Monte Carlo Simulation!

Monte Carlo analysis is a mathematical technique that allows you to account for risks in your decision-making process, by running simulations many times and identifying the range of possible outcomes in different scenarios.  This analysis can be used to perfect project schedules as well, where simulations create for worst-case, best-case and the time it might take. Also, this analysis Monte Carlo methods can be used in option pricing, default risk analysis.

For business decision making, financial planning and strategic business management Monte Carlo analysis is good to analyse the impact of risks on your forecasting models and can be used to further your scenario planning to create an even more compelling and possibly accurate forecast.

Limitations of the Monte Carlo Simulation

Monte Carlo simulation has its own set of limitations:

  • Input Bias. To run Monte Carlo simulation, you need to have a level of input for this activity. If you show some bias determining the input, your result will not give you a correct result.
  • Cannot be applied to a single activity! Monte Carlo analysis cannot be an applied to a single activity, you need to have all activities and the risk assessment for each.
  • You need computer assistance! In order to successfully complete a Monte Carlo analysis, you need computer assistance to run the same problem with multiple outcomes at least 10 000 times is not a very manual job.

Benefits of the Monte Carlo Simulation

The Monte Carlo simulation method has many benefits:

  • Increased accuracy of a risk assessment that you are performing.
  • Helps to predict failure, cost or overrun.
  • It helps to decide on a realistic budget and schedule.
  • It gives more objective data for your decision making.



The Monte Carlo analysis is a great tool and technique to get the best results out of your decision-making process. It helps you get the most objective, quantitative data even for small or medium sized projects.

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