Monte Carlo Simulation for Understanding Risk in Project Management

Dr. Deepak Subedi; Dr. Uday Tate

doi:10.65301/dias.2018.15.1.244

Articles 29th Edition of DTR Apr 2018 – Sep 2018

DOI 10.65301/dias.2018.15.1.244

Monte Carlo Simulation for Understanding Risk in Project Management

Authors

Professor of Quantitative Methods and Operations Management College of Business Marshall University Huntington Professor of Marketing College of Business-Corbly Marshall University Huntington

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Published 2018-09-30

Pages 28-36

Abstract

This article develops an algorithm for assessing the risk in project management. The main risk considered here is the risk of a project not finishing on time. This algorithm can be considered as an extension of the classical methods like Critical Path Method (CPM) and Project Evaluation and Review Technique (PERT). This extension can provide a richer understanding of risk inherent in any project planning. Specifically, the present article discusses the classical project management tools such as CPM and PERT by pointing out to their applications as well as shortcomings in the context of risk management. It then shows the steps to conduct a Monte Carlo simulation of CPM using EXCEL spreadsheet. To conduct the simulation, first CPM is recast as a couple of optimization (linear programming) problems. And then the scripts written in Visual Basic for Applications (VBA) in Excel is used to run the CPM for one hundred times. The simulation gives a range of project completion times as well as the probability for each activity becoming a part of critical path.

Keywords

Project Management Critical Path Method Linear Programming Risk Simulation

References

Albright, S. Christian (2001). VBA for Modelers: Developing Decision Support Systems with Microsoft Excel. Duxbury, Thomson Learning.
Critical Path Method.
https://en.wikipedia.org/wiki/Critical_path_method
(accessed on 6/15/2017).
Gido, Jack & Clements, James P. (2013). Successful Project Management (6th ed.). Cengage Learning.
Galli, Brian J. (2017). Risk Management in Project Environments: Reflections on the Standard Process. Journal of Modern Project Management, September/December, 40–49.
Jamshidia, Afshin; Ait-Kadib, Daoud; Ruizc, Angel (2017). Advanced Dynamic Risk Modeling and Analysis. Journal of Modern Project Management, May/August, 6–11.
Lawrence, John A. Jr., & Pasternack, Barry A. (1998). Applied Management Science: A Computer-Integrated Approach for Decision Making. John Wiley & Sons Inc.
FrontLineSolvers.
https://www.solver.com/excel-solver-linear-programming
(2018).
Pich, Michael T., Loch, Christoph H., & De Meyer, Arnoud (2002). On uncertainty, ambiguity, and complexity in project management. Management Science, 48(8), 1008–1023.
Pritsker, A. A. B. (1966). GERT: Graphical Evaluation and Review Technique. RM-4973-NASA. National Aeronautics and Space Administration, Rand Corporation.
https://www.rand.org/content/dam/rand/pubs/research_memoranda/2006/RM4973.pdf
Triangular Distribution.
https://en.wikipedia.org/wiki/Triangular_distribution
(accessed on 6/15/2017).

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How to Cite

Dr. Deepak Subedi, Dr. Uday Tate . (2018). Monte Carlo Simulation for Understanding Risk in Project Management. DIAS Technology Review, 15(1), 28-36.

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[1] Albright, S. Christian (2001). VBA for Modelers: Developing Decision Support Systems with Microsoft Excel. Duxbury, Thomson Learning.

[2] Critical Path Method.

[3] https://en.wikipedia.org/wiki/Critical_path_method

[4] (accessed on 6/15/2017).

[5] Gido, Jack & Clements, James P. (2013). Successful Project Management (6th ed.). Cengage Learning.

[6] Galli, Brian J. (2017). Risk Management in Project Environments: Reflections on the Standard Process. Journal of Modern Project Management, September/December, 40–49.

[7] Jamshidia, Afshin; Ait-Kadib, Daoud; Ruizc, Angel (2017). Advanced Dynamic Risk Modeling and Analysis. Journal of Modern Project Management, May/August, 6–11.

[8] Lawrence, John A. Jr., & Pasternack, Barry A. (1998). Applied Management Science: A Computer-Integrated Approach for Decision Making. John Wiley & Sons Inc.

[9] FrontLineSolvers.

[10] https://www.solver.com/excel-solver-linear-programming

[11] (2018).

[12] Pich, Michael T., Loch, Christoph H., & De Meyer, Arnoud (2002). On uncertainty, ambiguity, and complexity in project management. Management Science, 48(8), 1008–1023.

[13] Pritsker, A. A. B. (1966). GERT: Graphical Evaluation and Review Technique. RM-4973-NASA. National Aeronautics and Space Administration, Rand Corporation.

[14] https://www.rand.org/content/dam/rand/pubs/research_memoranda/2006/RM4973.pdf

[15] Triangular Distribution.

[16] https://en.wikipedia.org/wiki/Triangular_distribution

[17] (accessed on 6/15/2017).