Monte Carlo Schedule Analysis

1
Monte Carlo Schedule Analysis

• The Concept, Benefits and Limitations

Intaver Institute 400, 7015, Macleod Trail S.W.,
Calgary, Alberta, T2H 2K6, Canada
2
What is Monte Carlo Analysis?

• Monte Carlo simulation is a mathematical method
  used in risk analysis. Monte Carlo simulations
  are used to approximate the distribution of
  potential results based on probabilistic inputs.

3
Monte Carlo Simulations
Monte Carlo simulations use distributions as
inputs, which are also the results
4
Monte Carlo Schedule Analysis
Monte Carlo simulations take multiple
distributions and create histograms to depict the
results of the analysis
5
Two Approaches to Estimating Probabilities

• The relative frequency approach, where
  probability equals the number of occurrences of
  specific outcome (or event) divided by the total
  number of possible outcomes.
• The subjective approach represents an experts
  degree of belief that a particular outcome will
  occur.

6
Two of Approaches for Defining Uncertainties

• Distribution-based approach
• Event-based approach
• Monte Carlo can be used to simulate the results
  of discrete risk events with probability and
  impact on multiple activities

7
What Distribution Should Be Used?

• Also useful for Monte Carlo simulations
• Lognornal
• Beta

8
Ignoring Base-Rate Frequencies

• Historically, the probability that a particular
  component will be defective is 1.
• The component is tested before installation.
• The test showed that the component is defective.
• The test usually successfully identifies
  defective components 80 of the time.
• What is the probability that a component is
  defective?
• The correct answer is close to 4, however, most
  people would think that answer is a little bit
  lower than 80.

9
Role of Emotions
Emotions can affect our judgment
10
Eliciting Judgment About Probabilities of Single
Events

• Pose a direct question What is the probability
  that the project will be canceled due to
  budgetary problems?
• Ask the experts two opposing questions (1) What
  is the probability that the project will be
  canceled? and (2) What is the probability the
  project will be completed? The sum of these two
  assessments should be 100.
• Break compound events into simple events and
  review them separately.

11
Probability Wheel
Use of visual aids like a probability wheel can
aid in the increasing validity of estimates
12
Eliciting Judgment Probability Method
13
Eliciting Judgment Method of Relative Heights
Plotting possible estimates on a histogram can
help improve estimatesc
14
How Many Trials Are Required?

• Huge number of trials (gt 1000) usually does not
  increase accuracy of analysis
• Incorporate rare events
• Use convergence monitoring

15
What Is The Chance That a Project Will Be on Time
And Within Budget?
16
Analysis of Monte Carlo Results

• Sensitivity and Correlations
• Critical Indices
• Crucial tasks
• Critical Risks
• Probabilistic Calendars
• Deadlines
• Conditional Branching
• Probabilistic Branching
• Chance of Task Existence

17
Crucial Tasks
Crucial tasks for project duration
Monte Carlo analysis identifies task cruciality,
how often tasks are on the critical path.
18
Critical Risks
19
Conditional Branching
20
Monte Carlo and Critical Chain
Monitoring Project Buffer
21
Tracking Chance of Project Meeting a Deadline
22
When Monte Carlo Is Useful

• You have reliable historical data
• You have tools to track actual data for each
  phase of the project
• You have a group of experts who understand the
  project, have experience in similar projects, and
  are trained to avoid cognitive and motivational
  biases

23
Additional Resources
Project Think Why Good Managers Make Poor
Project Choices
Project Decisions The Art and Science Introductio
n to Project Risk Management and Decision
Analysis
Project Risk Analysis Made Ridiculously Simple
24
Questions?