What is a Monte Carlo Simulation?

July 25, 2020
Fahad Usmani
Monte Carlo Simulation

The Monte Carlo simulation is an important technique in risk management that many PMP and PMI-RMP exam study books do not describe in detail. 

Most of the guides say it is a complex technique that requires a computer’s assistance, and so aspirants don’t dig further. This assumption is not true; it is a straightforward technique. 

Monte Carlo Simulation

The Monte Carlo simulation is a quantitative risk analysis technique used in identifying the risk level of achieving objectives. 

This technique was invented by an atomic nuclear scientist named Stanislaw Ulam in 1940, it was named Monte Carlo after the city in Monaco that is famous for casinos. 

Monte Carlo Simulation is a mathematical technique that allows you to account for risks in decision-making. It helps you determine the impact of the identified risks by running multiple simulations and finding a range of outcomes. 

Every decision has a degree of uncertainty, and Monte Carlo Simulation helps you in such situations. It makes your decision sound and avoids surprises later. You can run this simulation to analyze the impact of the risks on cost, schedule estimate, etc. 

This technique gives you a range of possible outcomes and the probabilities that will occur for any choice of action.

Example

Let’s discuss the Monte Carlo Simulation’s use in determining the project schedule. Suppose that you have three activities with the following estimates (in months):

table-1-monte-carlo-simulation

From the above table you can see that, according to the PERT estimate, you can complete these activities in 17.5 months. 

In the best case, you can complete them in 16 months, and in the worst case, 21 months. 

Now, if we run the Monte Carlo Simulation for these tasks, five hundred times, it will show us the following results:

table 3 for monte-carlo-simulation

(Please note that the above data is for illustration purpose only and it is not from an actual simulation test.) 

You can see that there is a:

  • 2% chance of completing the project in 16 months
  • 8% chance of completing the project in 17 months
  • 55% chance of completing the project in 18 months
  • 70% chance of completing the project in 19 months
  • 95% chance of completing the project in 20 months
  • 100% chance of completing the project in 21 months 

This technique provides you with a more in-depth analysis of your data, and you can make a better-informed decision.

Limitations of the Monte Carlo Simulation

The Monte Carlo simulation has a few limitations, for example: 

  • The results depend on the quality of your estimates, so if the data are biased, the simulation will give a false result.
  • The Monte Carlo Simulation shows the probability of completing the tasks, not the actual time to complete.
  • This technique is not useful for a single activity; you need to have many activities with risk assessments completed.
  • You will need to buy an add-on or a software program to run the Monte Carlo simulation.

Benefits of the Monte Carlo Simulation

The Monte Carlo simulation method has many benefits in project management, such as:

  • It helps you evaluate the risk of the project.
  • It helps you predict the chances of failure, and schedule and cost overrun.
  • It converts risks into numbers to assess the risk impact on the project objectives.
  • It helps you build a realistic budget and schedule.
  • It helps you gain management support for risk management.
  • It helps you in decision making with objective evidence.
  • It helps you to find the chances of achieving project milestones or intermediate goals.

Summary

The Monte Carlo Simulation is an essential technique in risk analysis that helps you make decisions under uncertain conditions. Although this technique is often not used in projects, if used it increases the chances of achieving project success within the approved baselines. 

Have you used the Monte Carlo Simulation in your projects? How was it useful? Please share your thoughts in the comments section.

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Speak Your Mind

  • Thanks to brother Fahad and the reader. I have gone throgh the article and coments. Think it’s easy to conceptualize the main idea.

  • Hi Fahad,

    You are right, most books just give a brief description and also there are no questions on this topic in most of study material I have been through. Can you please let us know what kind of questions are encountered on the PMP exam?

    Regards,
    Manny

  • Thanks Fahad. This just gave me happiness after a long search for MC. Now please, help explain the limitations of MC carefully to me, especially point 1 & 3.

    A. Why always 3 estimates/assumptions? On what basis can these estimates be based—-on past knowledge, pattern knowledge or future knowledge?

    B. What do you mean by simulation cannot be performed on Single activity but all activities. And then again, risk assessment must be performed on each activity? Do you mean, one must know all the activities that must be carried out to complete a task, the run MC simulation(risk analysis) on each of these activities? Why can’t MC be run on all these activities together at once so one can have a more holistic result that would show the effect of interconnectedness?

    C. Can MC be used also for operational (day to day) decisions as it seems it’s good for only strategic decisions?

    Thanks a lot for quick response. I would be very grateful.

    • A) PERT technique reduces the biases so we use it.

      B) This is not a tool to use for every single activity.

      C) We mainly use it for finalizing budget and schedule for a project

  • it is my understanding that in the PMP exam we will not have access to simulation software. is there a manual method for exam purposes?

    • In this blog post, this is an assumed data. You will get the real data when you enter correct data in Monte Carlo simulation software.

  • If you are asking about how the Monte Carlo Method is working
    It is working by generating random (according to predefined probabilities) samples then calculating the overall probability

    For example assume that you have a board and a circle drawn on that board
    Let’s throw darts and see how many fell inside or outside the circle
    We can calculate the circle area by multiplying the % of darts fell inside by the total area of the board

  • Hi Fahad,

    I have a small concern, what would be the inputs that are mandate to run this tool. For example Calculating the schedule we would need all the activity with there estimates, risk assessment done for all the activities and what else that is required.

    Please help me on this

  • Assalam o Aleikum, Brother,

    In above example, Activity A will have pert estimate equal to 5 instead of 4.3.

    {4+(4×5)+6}/6 = 5

    Thank you for sharing . It was very informative.

  • Dear Fahad sb,
    Assalam o Aleikum,

    First of all, Jazak Allah Khair for writing this important blog post explaining technique used in quantitative risk analysis process.

    1) In this blog post, I’m not understanding that how does Monte Carlo Simulation actually works and calculate chances of completion (%ages) ?
    2) Any mathematical calculation or example or formula ?
    Also, which software is required to run this simulation ?

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