Print this page Monte Carlo Simulation of Project Schedules
Brian Steve Smith, PE, PMP, MBA
Course Outline
The course begins with a description of the general utility of Monte Carlo simulation, and its advantages over “point case” models. The data and tools required for the Monte Carlo simulation are described, and illustrated through a simple project schedule example. The course illustrates the construction of the schedule model, the definition of task duration distributions and the model’s output, and how to set up the parameters required to run the Monte Carlo simulation.
Using screen shots and data tables, the course illustrates how to obtain and interpret the simulation results applied to the sample project schedule. In addition to the stochastic model itself, the course also illustrates the value (and process) of performing a sensitivity analysis on the schedule model. Finally, suggestions are given related to the presentation of the simulation to project stakeholders.This course includes
a multiple-choice quiz at the end, which is designed to enhance the understanding
of the course materials.
Learning Objective
At the conclusion of this course, the student will:
- Understand the importance of quantifying project schedule risk;
- Learn to convey project completion schedules in terms of probabilities;
- Recognize the advantages of risk analysis compared to simply adding “fat” to project schedules;
- Be able to identify the project tasks to which the overall project is most sensitive;
- Make informed decisions about how to most effectively mitigate project schedule risk based on statistical analysis;
- Develop proficiency at interpreting and presenting Monte Carlo simulation results; and
- Learn how to use stochastic modeling to create a competitive advantage for your firm.
Intended
Audience
This course targets project engineers, project managers, engineering managers, and project sponsors.
Benefits
to Attendee
Rather than thinking of project completion schedules in terms of a single date, this course enables the audience to think of project schedules in statistical terms, around probabilities that provide a more realistic view of probable project outcomes.
Course Introduction
The course introduces the application of Monte Carlo simulation techniques to project schedules to estimate a probability distribution of possible completion dates. Assuming a prerequisite knowledge of the basics of project schedule development, participants will learn to move beyond simple “deterministic” project duration estimates and begin applying stochastic models for a more realistic and meaningful analysis of probable project completion dates.
Course Content
The course content is in the following PDF file:
Monte Carlo Simulation of Project Schedules
Please click on the above underlined hypertexts to view, download or print the document for your study. Because of the large file size, we recommend that you first save the file to your computer by right clicking the mouse and choosing "Save Target As ...", and then open the file in Adobe Acrobat Reader.
Course Summary
Too often, project stakeholders, sponsors, and managers are content to think of project schedules in terms of fixed milestone and completion dates, and measure the success or failure of the project by whether these milestone dates are achieved or not. With the risk analysis tools presented in this course, students can confidently manage project schedule performance using date ranges and probabilities, recognizing and managing the uncertainty inherent in most project tasks.
Related Links
For additional technical information related to this subject, please visit the following websites:
www.riskamp.com. This is the website for the simulation tool used in the course examples.
Quiz
Once you finish studying the above course content, you need to take a quiz to obtain the PDH credits.
DISCLAIMER: The materials contained in the online course are not intended as a representation or warranty on the part of PDH Center or any other person/organization named herein. The materials are for general information only. They are not a substitute for competent professional advice. Application of this information to a specific project should be reviewed by a registered architect and/or professional engineer/surveyor. Anyone making use of the information set forth herein does so at their own risk and assumes any and all resulting liability arising therefrom.
