Transcript Quantitative Methods in Project Management

Quantitative Risk Analysis for Aerospace
Industry
Intaver Institute Inc.
303, 6707, Elbow Drive S.W.,
Calgary AB Canada T2V 0E5
www.intaver.com
Common Issues with Space System Projects
• Multiple risks and uncertainties
• Many uncertainties are event-driven
• Historical data mining should include relevance analysis
Existing Methodologies
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PERT
Monte Carlo Simulation
Bayesian approach
Scenario analysis and Decision Trees
Project Example
Laser Interferometer Space Antenna (LISA) project
Calendar Year
2002
==>
Proj ect Phasing
2003
4 1 2 3
Pre-Phase A
2004
2 3 4
Phase A
1
2005
2 3
1
FAD
NASA HQ Milestones
4
1
2006
2 3 4
Phase B
1
2007
2 3
ICR/CA
FAD HQ
4
2008
2 3
1
4
1
2009
2 3 4 1
Phase C/D
2010
2 3
4
2011
2 3
1
MDR
SCR
ESA MOU (F)
PDR
CDR
Obs 1 PER
MRR
ORR
Briefing
Partnering Phase
Acquis ition
RFI
SRR
TRR
S/C1 PER
Execution Phase
Prep Phase
RFP D Sel
RFP
2012
4
PCA
NAR
M is s ion Re vie w s
SE&I Contractor
4
MOR
LRR
PSR FRR
Sel
Te chnology
LISA T est Package (SM2)
ST 7 DRS (SM2)
Interferometry Measurement
System
System Verification
Disturbance Reduction
System
Payload
Space craft
CDR
Deliver to SM2
SM2 Launch
Deliver to SM2
SM2 Launch
LISA Demo
PDR
CDR
Trades
Subs
Assy
Test
Model Envr R2
Model Envr R1
Trades
Subs
GRS TRL5
Tgt Std
Assy
Rqts/Architecture/Trades
ITT
Award
ESA Definition Phase
Obs e rvatory I&T
Cons te llation Te s ting
Launch Cam paign
DRS Demo
TRL6
TRL5
Model Envr R3
Testbed Demos
GRS TRL6
Test
PDR
ITT
Award
CDR
Design
PDR
CDR
EM 1
Build / Test
EM
1
2
3
2 3
ESA Implementation Phase
EM 1 2
3
Preps
Observatory I&T
1
2 3
Preps
Constellation Testing
LRD
Launch Preps
The document is courtesy of NASA/Goddard Space Flight Center
1
Heuristics and Biases in Project Management
The Bank of Sweden Prize in
Economic Sciences in
Memory of Alfred Nobel 2002
Decision makers use
“heuristics”, or general
rules of thumb, to arrive
at their judgments.
In certain instances, this
will lead to systemic
biases.
Daniel Kahneman
Examples of Heuristics in Project Management
• Representativeness – unwanted appeal to detailed scenarios
• Availability – access the probability of an event by the ease
with which instances can be brought to mind
• Anchoring – human tendency is to remain close to the initial
estimate
Event Chain Methodology
Event Chain Methodology is a method of
modeling uncertainties for different time-related
business and technological processes including
project management for space systems.
Moment of Risk and State of Activity
An activity (task) in most real life processes is not a continuous
uniform procedure. Tasks are affected by external events,
which transform an activity from one state to another.
Event Chains
Events can cause other events, which will
create event chains. These event chains
can significantly affect the course of the
project.
Monte Carlo Simulations
Once events and event chains are defined, quantitative
analysis using Monte Carlo simulation can be performed to
quantify the cumulative impact of the events.
Information regarding the uncertainties
expressed as an event is supplemented
with distributions related to duration,
start time, cost, and other parameters
Critical Chains of Events
The single events or the event chains that have the most
potential to affect the projects are the “critical events” or
“critical chains of events.”
History Matching and Relevance Analysis
• Similar events or event chains are found based on historical
data
• Analysis based on Bayesian approach is performed and
relevance parameter is calculated
• Project manager defines relevance of each event or event chain
for the current project
• Both calculated and user defined relevance parameters are
used to determine probability and impact of the events for the
current project
Performance Tracking with Event and Event Cha
During the course of the project, the probability and time of the
events can be recalculated based on actual data.
Actual performance data and
original estimate is used
forecast duration of activity
with risks
Event Chain Diagrams
Event Chain Diagrams are visualizations that show the
relationships between events and activities and how the events
affect each other
Repeated Activities
Common scenario for real life projects: sometimes a previous
activity must be repeated based on the results of event in a
succeeding activity
Event Chains and Risk Mitigation
Mitigation plan can be assigned to an event or event chain. These
small schedules will be triggered when an event chain occurs.
Resource Allocation Based on Events
Event: the reassignment of a resource from one activity to
another
Example: if an activity requires more resources to complete it
within a fixed period, this will trigger an event to reallocate the
resource from another activity.
Project Management Workflow using Event Cha
Methodology
1.
2.
3.
Define a detailed project schedule with resources and costs
assigned to the activities
Define a detailed risk breakdown structure and assign risks to
the activities. The probability of each event can be taken from
historical data.
Define the activities associated with mitigation efforts and
then assign costs and resources to them.
Project Management Workflow using Event
Chain Methodology
4. Perform a quantitative risk analysis using Monte Carlo
simulations.
5. Analyze the results of the quantitative risk analysis: perform a
sensitivity analysis and identify the crucial tasks and critical
risks.
Project Management Workflow using Event
Chain Methodology
6. Perform reality checks: compare the results of analysis with
outside independent expert reviews and historical experience.
7. Monitor the course of the project on a regular basis, perform
repeated quantitative risk analysis, reassess the event and
event chain parameters
Acknowledgements
Intaver Institute Inc. is thankful to Kevin N. Miller, Deputy Project
Manager/Resources, Laser Interferometer Space Antenna (LISA)
Project, NASA/Goddard Space Flight Center, for providing data
necessary to illustrate the methodology discussed in the paper.