1. Quantitative Risk Analysis for Aerospace Industry
Intaver Institute Inc.
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2. Common Issues with Space System Projects
Multiple risks and uncertainties
Many uncertainties are event-driven
Historical data mining should include relevance analysis

3. Existing Methodologies
PERT
Monte Carlo Simulation
Bayesian approach
Scenario analysis and Decision Trees

4. The document is courtesy of NASA/Goddard Space Flight Center
Project Example
Laser Interferometer Space Antenna (LISA) project
The document is courtesy of NASA/Goddard Space Flight Center

5. Heuristics and Biases in Project Management
Decision makers use “heuristics”, or general rules of thumb, to arrive at their judgments.
The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel 2002
In certain instances, this will lead to systemic biases.
Daniel Kahneman

6. 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

7. 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.

8. 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.

9. Event Chains
Events can cause other events, which will create event chains. These event chains can significantly affect the course of the project.

10. 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

11. 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.”

12. 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

13. Performance Tracking with Event and Event Chains
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

14. Event Chain Diagrams
Event Chain Diagrams are visualizations that show the relationships between events and activities and how the events affect each other

15. 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

16. 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.

17. 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.

18. Project Management Workflow using Event Chain Methodology
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.

19. Project Management Workflow using Event Chain Methodology
4. Perform a quantitative risk analysis using Monte Carlo simulations.
Analyze the results of the quantitative risk analysis: perform a sensitivity analysis and identify the crucial tasks and critical risks.

20. 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

21. 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.