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ASSESSING ENTERPRISE
PROJECT RISK
Probability of Program Success P(s)
Assessing Schedule Risk is One Step
2
Probability of Success P(s)
Assesses a project’s
performance using 4 simple
metrics.
It is the Planning metric that
can be assessed using two
methods deployed by Lewis &
Fowler
 Monte Carlo Simulation
 Schedule Health
3
The Data Elements of a Project are Random Variables
Cost, Schedule, Technical Performance and Risk
 Each is drawn from a
probability
distribution.
 The shape of this
distribution has direct
impact on the
confidence of the
outcome.
 Modeling this
probability
distributions and
their outcomes is
what a Monte Carlo
tool does.
The Schedule Assessment Process
 Topology
 Task with no successors
 Tasks with no
predecessors
 Constraints
 Must Finish On
 Finish No Later Than
 Must Start On
 Start No Later Than
 Margin analysis
 Task duration
probability
distributions
 Confidence of
completing on or
before a planned
date
Schedule Health Schedule Risk
Every Manager Should Know…
5
 When will this project finish?
 Is the project’s schedule realistic and achievable?
 What will it cost when we are done?
 How is the project performing against its plan?
 What deliverables are slipping?
 How are we going to get the deliverables back on schedule?
 What does past performance say about the future performance?
 What is the impact on the schedule of any change requests?
 Is there enough schedule slack and reserve to cover the risk?
 Is there enough management reserve to cover any overrun?
 Where is the risk in the schedule?
 How can we get the work done sooner to reduce risk?
 How can we recover from any foreseen delays?
 How can we work around a problem?
EXAMPLE SCHEDULE RISK
ANALYSIS
7
Monte Carlo Risk analysis starts with a credible
schedule and defines the probabilistic behavior of
each activities and how it drives the deliverables
The Risk+ tool sets the upper and lower bounds of the possible durations
8
Date: 2/25/2009 3:34:12 PM
Samples: 300
Unique ID: 30
Name: Final Testing
Completion Std Deviation: 5.51d
95% Confidence Interval: 0.62d
Each bar represents 2d
Completion Date
Frequency
CumulativeProbability
Tue 2/11/03Mon 1/20/03 Mon 3/3/03
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16 Completion Probability Table
Prob ProbDate Date
0.05 Wed 1/29/03
0.10 Fri 1/31/03
0.15 Tue 2/4/03
0.20 Wed 2/5/03
0.25 Wed 2/5/03
0.30 Thu 2/6/03
0.35 Fri 2/7/03
0.40 Mon 2/10/03
0.45 Mon 2/10/03
0.50 Tue 2/11/03
0.55 Wed 2/12/03
0.60 Thu 2/13/03
0.65 Fri 2/14/03
0.70 Fri 2/14/03
0.75 Mon 2/17/03
0.80 Tue 2/18/03
0.85 Wed 2/19/03
0.90 Thu 2/20/03
0.95 Tue 2/25/03
1.00 Mon 3/3/03
The output of Risk+ is a Probability Distribution Function and a
Cumulative Distribution of all the possible dates that “watched”
activity could take.
This shows the Confidence in the target date – 2/10/3
It shows 40% chance of completely on or before 2/10/03
Beneficial Outcomes
 A confidence metric that the project will complete
on or before the planned date
 Measures of the integrity of the activity network
 Overly constrained plan
 Activities with no dependencies
 Visibility into the Probability of Success from a
schedule point of view

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Assessing Enterprise Project Risk

  • 2. Assessing Schedule Risk is One Step 2 Probability of Success P(s) Assesses a project’s performance using 4 simple metrics. It is the Planning metric that can be assessed using two methods deployed by Lewis & Fowler  Monte Carlo Simulation  Schedule Health
  • 3. 3 The Data Elements of a Project are Random Variables Cost, Schedule, Technical Performance and Risk  Each is drawn from a probability distribution.  The shape of this distribution has direct impact on the confidence of the outcome.  Modeling this probability distributions and their outcomes is what a Monte Carlo tool does.
  • 4. The Schedule Assessment Process  Topology  Task with no successors  Tasks with no predecessors  Constraints  Must Finish On  Finish No Later Than  Must Start On  Start No Later Than  Margin analysis  Task duration probability distributions  Confidence of completing on or before a planned date Schedule Health Schedule Risk
  • 5. Every Manager Should Know… 5  When will this project finish?  Is the project’s schedule realistic and achievable?  What will it cost when we are done?  How is the project performing against its plan?  What deliverables are slipping?  How are we going to get the deliverables back on schedule?  What does past performance say about the future performance?  What is the impact on the schedule of any change requests?  Is there enough schedule slack and reserve to cover the risk?  Is there enough management reserve to cover any overrun?  Where is the risk in the schedule?  How can we get the work done sooner to reduce risk?  How can we recover from any foreseen delays?  How can we work around a problem?
  • 7. 7 Monte Carlo Risk analysis starts with a credible schedule and defines the probabilistic behavior of each activities and how it drives the deliverables The Risk+ tool sets the upper and lower bounds of the possible durations
  • 8. 8 Date: 2/25/2009 3:34:12 PM Samples: 300 Unique ID: 30 Name: Final Testing Completion Std Deviation: 5.51d 95% Confidence Interval: 0.62d Each bar represents 2d Completion Date Frequency CumulativeProbability Tue 2/11/03Mon 1/20/03 Mon 3/3/03 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 Completion Probability Table Prob ProbDate Date 0.05 Wed 1/29/03 0.10 Fri 1/31/03 0.15 Tue 2/4/03 0.20 Wed 2/5/03 0.25 Wed 2/5/03 0.30 Thu 2/6/03 0.35 Fri 2/7/03 0.40 Mon 2/10/03 0.45 Mon 2/10/03 0.50 Tue 2/11/03 0.55 Wed 2/12/03 0.60 Thu 2/13/03 0.65 Fri 2/14/03 0.70 Fri 2/14/03 0.75 Mon 2/17/03 0.80 Tue 2/18/03 0.85 Wed 2/19/03 0.90 Thu 2/20/03 0.95 Tue 2/25/03 1.00 Mon 3/3/03 The output of Risk+ is a Probability Distribution Function and a Cumulative Distribution of all the possible dates that “watched” activity could take. This shows the Confidence in the target date – 2/10/3 It shows 40% chance of completely on or before 2/10/03
  • 9. Beneficial Outcomes  A confidence metric that the project will complete on or before the planned date  Measures of the integrity of the activity network  Overly constrained plan  Activities with no dependencies  Visibility into the Probability of Success from a schedule point of view