Best Practices

How to reveal all the potential of Monte Carlo Analysis



By Julie Luso

SKEMA Business School

Paris, France



Decision making is still a struggling topic for companies. The aim of Monte Carlo Analysis is to answer to it but the goal is still not completely reached. This paper aims to give the key points to improve the use of Monte Carlo Analysis through software to help decision making which is a vital topic. In order to found out those keys we used a multi attribute-decision-analysis comparing different Monte Carlo software. Thanks to this method, we could highlight the importance of the documentations and the help support to permit a full knowingly use of the software by the user. Thanks to a strong help user services that can answer to every questions, it appears that anyone can use a Monte Carlo Analysis and be efficient to his decision-making.

Keywords: Monte Carlo simulation, Forecasting model, Benefit Monte Carlo Analysis, Mathematics for business, Risk assessment, Decision Making, Parameters, Variables.


Omit probable scope and risks and unrealistic optimistic assumptions are responsible for 74% of Cost Growth according to a RAND Study[1]. Naturally, a Cost Growth is an important break for the development of a project jeopardizing it until his total failure. This highlights the need to simulate uncertainties as best as possible to improve the assurance of the success of the project. The main goal of the well-known Monte Carlo Simulation Software (MCS), created and first used by scientists working on the atomic bomb in the 40’s, was to answer at this need. It must help in quantitative analysis and decision making taking in regard the risk thanks to mathematics.

In order to implement it, the user has to follow 6 steps: “Identify the key project risk variables, Identify the range limits for these project variables, Specify probability weights for this range of values, Establish the relationships for the correlated variables, Perform simulation runs based on the identified variables and the correlations, Statistically analyze the results of the simulation run.”[2]


In theory, based on his knowledge and his experiences, the user should be able to fill those steps and so properly use the MCS to receive a great forecast of the likelihood of his different options. Thanks to this, the user can forecast risk or try different decision and finally choose the best one according to the different result of the MCS.

The MCS is designed to be easy to use in order to be a great assistant of the decision making. Practically, as the RAND STUDY told us, risk assessment is still a vital and spread issue that many companies are struggling with. So, regarding to this, it is surprising that the MCS built such a strong reputation of success.

Problem definition

There are 2 possible sources of mistakes that can explain a misuse of Monte Carlo Analysis that deceives companies: the software and the human mistake.

Normally, one of the roles of software is to guide the user for a free-mistake right and efficient use. If this role is not made in a convenient way, the risk for a higher mistake that will make a wrong forecast leading to a wrong decision is higher as well. So the 2 possible sources are linked.

To summarize, this paper has been designed to research, analyze and answer the following two questions in order to find a response to these mistakes to help the companies in their decision-making:

  • How can we effectively use and apply Monte Carlo Simulation Software?
  • What can we consider as a good Monte Carlo Software?


To read entire paper, click here


Editor’s note: Student papers are authored by graduate or undergraduate students based on coursework at accredited universities or training programs.  This paper was prepared as a deliverable for the course “International Contract Management” facilitated by Dr Paul D. Giammalvo of PT Mitratata Citragraha, Jakarta, Indonesia as an Adjunct Professor under contract to SKEMA Business School for the program Master of Science in Project and Programme Management and Business Development.  http://www.skema.edu/programmes/masters-of-science. For more information on this global program (Lille and Paris in France; Belo Horizonte in Brazil), contact Dr Paul Gardiner, Global Programme Director [email protected].

How to cite this paper: Luso, J. (2018). Best Practices: How reveal all the potential of the Monte Carlo Analysis, PM World Journal, Volume VII, Issue X – October.  Available online at https://pmworldjournal.net/wp-content/uploads/2018/10/pmwj75-Oct2018-Luso-how-to-reveal-potential-of-monte-carlo-analysis.pdf


About the Author

Julie Luso

Paris, France




Julie Luso, French Swiss of 24 years old, studied at SKEMA in MSc Project and Program Management and Business Development, graduating in April 2018. After 2 years in preparatory class, Julie integrated SKEMA Business School (ranked top 8 France in 2017). The first year in Sophia Antipolis (Nice) was dedicated to association activities adding to the classes. After this, she left France for a few months to live in Thailand for a communication internship and discover a new world.

She came back to school the next scholar year starting by Brazil (Belo Horizonte) in a SKEMA campus to go then for the next semester in China (into the SKEMA Campus in Suzhou) where she participated in a humanitarian association for children before travelling alone during 2 months over there. Julie then used her gap year to return to Brazil for a stronger cultural immersion. To reach that goal, Julie chose to work in a Farm hotel far from famous places to discover a hidden Brazil and to control the language. Enjoying contrasts, after this experience Julie worked for 6 months in Paris Champs-Elysées at Ogilvy Paris, an international advertising agency. Working in the Public Relations unit, Julie was part of a development team working to improve the (e-)reputation of great corporations creating and implementing communication campaigns targeting journalists and influencers and so readers and communities. Following this gap year, Julie started then her MSc. at Skema in Paris.

Currently certificated by AgilePM and Prince2 for PM, Julie has worked during this MSc to actively improve her assets by organizing event like the Video Games day and participating to the *Amazon Campus Challenges 2017 adding to her class, assignments and Thesis.  (*The Amazon Campus Challenge is a challenge that asks by team to find a startup to create and implement its Amazon e-store and make a commercial strategy to boost its sells during 6 months.)

Julie’s main long term goal is to be able to help ethical and environmentally friendly organizations to grow in a complex market as an accomplished and ethical Project Manager. Challenger, passionate, expressive and audacious are her personal assets that will help her to reach her goals.  Julie can be contacted at [email protected] or www.linkedin.com/in/julie-iuso


[1]Edward W. Werrow. (1983). Cost Growth In New Process Facilities. Retrieved from https://www.rand.org/content/dam/rand/pubs/papers/2005/P6869.pdf

[2]Marom , S. (2010, July 8). Project Risk Management and the application of Monte Carlo Simulation. Retrieved from http://quantmleap.com/blog/2010/07/project-risk-management-and-the-application-of-monte-carlo-simulation/