q n u schedule risk management by ursula kuehn, pmp, evp uqn and associates
TRANSCRIPT
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QNU
Schedule Risk Management
By Ursula Kuehn, PMP, EVPUQN and Associates
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QNU
How We Tend To Develop a Schedule For Our Projects
• Identify tasks• Get estimates of durations• Network tasks• Crash the schedule, if needed• Baseline the schedule• Execute the schedule• Do what we can to keep the schedule
on track
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QNU
Getting Estimates
I need yourestimates bytomorrow.
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QNU
Let’s see...I haveto do this, and then do this.That should take me 2 days,
but I better say a weekbecause I always underestimate.
How We Tend To Estimate
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QNU
How does aweek sound?
How about Igive you twoweeks?
I’ll bet he’spadded it some, but
I’ll pad it a little more to be sure.
What Tends To Happen Next
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QNU
I have so many tasks to do. I’ll
start this task next Thursday. That
gives me 2 days to finish it. I think I
can finish it in that time.
Parkinson’s Law
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QNU Let’s Try An Example
• Changing an oil filter
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QNU
Polaris Submarine Missile Experiment for Estimating
Task Duration Simulation
0
5
10
15
20
25
30
35
Optimistic Most Likely Pessimistic
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QNU
The Mean and Standard Deviation
6
4(mean) *PERT
PMLO
6(std.dev.)* PERT
OP
* Program Evaluation and Review Technique
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QNU
What We Got From That Geeky Guy Named Gauss
-1σ
50% 84% 97.7% 99.8%16%2.3%0.2%
68+% Range
+1σ
Probability of Success
+2σ
+3σ
-1σ
-2σ
-3σ
95+% Range
99+% Range
Me
an
Using the normal curve to determine probability of success
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QNU
Range Estimating Using PERT
• Ask for four (4) pieces of information when estimating– The “most likely” estimate, i.e., how long will
it most likely take to do the work– The “optimistic” estimate, i.e., if everything
goes perfectly how long will it take to do the work
– Two or three things that could go wrong, i.e., risk identification
– The “pessimistic” estimate, i.e., if these things happen, how long will it take to do the work
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QNU PERT Example
Tasks Optimistic
Most Likel
y
Risks
Pessimistic
(O+4ML+P)6
P-O6
A 8.0 10.0 20.0
B 5.0 7.0 15.0
C 20.0 25.0 40.0
D 2.0 3.0 8.0
E 5.0 10.0 25.011.7
3.7
26.7
8.0
11.3
3.3
1.0
3.3
1.7
2.0
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QNU
Determining the Probability of Meeting a Due Date using PERT
• Uses the summation of events rule of statistics
• Due to the “mutually exclusive” portion of this summation rule PERT can only be performed on a single path of the schedule
)(Mean Mean Packages Work Critical(project)
)( Packages) Work (Critical(project) Dev. Std.2
Std.Dev.
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QNU PERT Example
Tasks Optimistic
Most Likel
y
Risks
Pessimistic
(O+4ML+P)6
P-O6
((P-O)/6)2
A 8.0 10.0 20.0
B 5.0 7.0 15.0
C 20.0 25.0 40.0
D 2.0 3.0 8.0
E 5.0 10.0 25.0∑((p-o)/6)2=
SQRT(∑((p-o)/6)2)=
5.4
11.7
3.7
26.7
8.0
11.3
3.3
1.0
3.3
1.7
2.0
11.0
1.0
11.0
2.9
4.0
29.061.455.0 Mean=Project
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QNU
Determining the Probability of Meeting a Due Date
-1σ
50% 84% 97.7% 99.8%16%2.3%0.2%
68+% Range
+1σ
Probability of Success
+2σ
+3σ
-1σ
-2σ
-3σ
95+% Range
99+% Range
Me
an
Using the normal curve to determine probability of success
61.445.2 50.6 56.0 66.8 72.2 77.6
Our Most Likely date of 55 has less than a 15% chance.
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QNU …And That Is Just One Path
• How many of you have only 5 tasks on your critical path?
• How many of you have only one path through your schedule?
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QNU Merge Bias
Task I2 Days
Task H3 Days
Task E7 Days
Task G3 Days
Task B8 Days
Task D9 Days
Task A6 Days
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QNU Statistical Sum
BP x APBAP
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QNU Merge Bias Demonstration
Task I
Task H
Task E
Task G
Task B
Task D
Task A
50% Chance
50% Chance
25% Chance at the merge point
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QNU
Monte Carlo Simulation
• Randomly generates durations based on optimistic, most likely, and pessimistic estimates of each individual work package
• Runs the simulation of the entire project schedule a number of times (e.g., 1,000 times)
• Computes the frequency data of the end dates• Determines probability based on frequency
data curve
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QNU
Example of Monte Carlo Results
Date: 3/31/2004 2:38:36 PMSamples: 350Unique ID: 1706Name: Systems Analysis and Design Contracts Awarded
Completion Std Deviation: 9.22 days95% Confidence Interval: 0.96 daysEach bar represents 3 days
Completion Date
Fre
quency
Cum
ula
tive P
robability
Tue 7/6/04Fri 6/11/04 Tue 8/17/04
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 Date0.05 Thu 6/17/040.10 Fri 6/18/040.15 Tue 6/22/040.20 Wed 6/23/040.25 Thu 6/24/040.30 Fri 6/25/040.35 Mon 6/28/040.40 Tue 6/29/040.45 Thu 7/1/040.50 Thu 7/1/04
0.55 Tue 7/6/040.60 Wed 7/7/040.65 Wed 7/7/040.70 Fri 7/9/040.75 Tue 7/13/040.80 Thu 7/15/040.85 Mon 7/19/040.90 Mon 7/26/040.95 Mon 8/2/041.00 Tue 8/17/04
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QNU
Try Working With Two Project Plans
• Most project management software tools allow for a number of different baselines in the same project file
• To avoid Parkinson’s Law have one baseline with the “most likely” estimates, which will be the one used to direct the team member’s tasks
• The second baseline will use the calculated “mean” estimates, which will be used to status the progress of the project
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QNU Conclusions
• If we base our schedule on single point duration estimates, we’re not giving ourselves a chance to be successful
• We should challenge our team members to their most likely estimates
• Using risk identification, mitigate the risk of being unsuccessful by having a second baseline that has a higher probability of success