This document discusses complexity challenges in integrating systems and organizations. It begins by looking at whether systems engineering needs an overhaul due to increasing system size, complexity, and globalization of engineering teams. It then examines complexity from an outside perspective, discussing different definitions of complexity from fields like information theory, computation, dynamics, and decision making. The document ends by discussing how multi-disciplinary research shows how complexity affects team behavior in socio-technical systems.
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Challenges of Integrating Complex Systems and Organizations
1. Complexity Challenges in the Integration
of Systems and Organizations
Does Systems Engineering need an Overhaul?
NASA PM Challenge 2012
1
2. Agenda
Complexity Challenges in the Integration of
Systems and Organizations
• Does Systems Engineering Need an Overhaul?
• Looking at Complexity from the Outside In
• Complexity & Teams
• Dialogue
2
3. Does Systems Engineering Need
an Overhaul?
Michael C. Lightfoot
NASA Langley Research Center, Hampton, VA
PM Challenge 2012, Orlando, FL February 22, 2012
3
4. Systems Engineering is Being Placed Under
the Microscope
There is a growing number of engineering communities who are asking
tough questions about the current practice of Systems Engineering.
Tough Questions:
Why do the current SE processes, if rigorously applied, not guarantee
us safe, effective, robust systems delivered on time and within budget?
What is it about our methods, processes and tools that seems to fail in
newsworthy fashion when we attempt to design and build large-scale
systems.
Has our SE system somehow evolved to become a system that defies
our control?
Why the tough questions now?
4
5. Systems Engineering Trends
System Size and Complexity has increased:
One Example*: F-16, 15 Subsystems, 103 Interfaces
F-35, 130 Subsystems, 105 Interfaces
Organizations:
• Size increase (100’s to 1000’s),
• most likely global teams,
• different cultures w/ different incentives
• multiple companies,
• many reporting structures,
• sometimes competing incentives
Subsystems that were once modular in design are now
irreducibly entwined (tightly coupled)
Many systems are one of a kind (NASA) or limited quantity
productions
* Data courtesy of United Technologies Research Center:
https://www.fbo.gov/download/9cb/9cb78f01aa9db1fe92e093e786bc6733/Abstraction_Based_Complexity_Management_Final_Report_Dist_A.pdf
5
8. Characteristics of Large-Scale Complex
Engineered Systems
Increased Engineering Complexity
Highly-coupled interfaces, many of which are only discovered during integration &
testing or system operation.
Design Cycles are Longer and More Complicated
Significant Cost and Risk
Extremely high political and monetary risk
Low tolerance for failures or degraded performance
Public fear of catastrophic failure is high
Limited opportunities to experiment (trial and error)
Very Large, Dispersed Engineering Organizations
Yet organizations are expected to function synergistically
Coordination and data exchanges are greater in frequency and volume of data.
Unlike the early days of SE, no one Chief SE is able to keep the entire system view in
his/her head.
8
9. Classes of Engineered Systems
(Relative Comparisons, Not Rigorous Definitions)
Simple System: Consist of few parts,
Small number of interfaces
Interactions well understood & well controlled,
Typically used as building blocks for more sophisticated parts & components
Complicated Consist of many parts, components, subsystems
System: Moderate to large number of interfaces
Interactions/reactions understood for controlled cases
Vigilant control required to properly construct
V & V is the basis to accept/reject bad parts, components, subsystems
Global system behavior is mostly predictable; Part decomposition & analysis
leads to reasonable global property predictions
Complex Can possess extreme numbers of parts, components, subsystems
System: Extreme numbers of interfaces- sometimes impossible to identify
Interactions understood for limited number of highly controlled cases but
mostly unknown due to dynamic adaptations
Vigilant control often exercised but system sensitivity is nonlinear &
dependent on initial conditions (path dependent).
Current analysis tools are poor predictors of system behavior
Complete system V & V not possible.
Global system behavior can be emergent (reductionist approaches fail)
9
10. Complicated System Example
Star Caliber Patek Phillipe mechanical watch.
We understand:
how it is constructed,
the required tolerances,
the order of assembly.
Each component works in unison
to accomplish a global function: keep
time precisely.
We can take a reductionist path to
define the smallest required parts
and can further write equations of
motion to predict the performance
and functionality of the watch.
10
11. Complex Systems
Through a Complexity Science Lens
• Dynamical systems
Dynamical/non-linear
Highly-coupled
• System response is non-linear & sensitive to initial conditions
• Consist of many parts, components, or subsystems (agents) that interact
Adaptive
with each other & the environment
Can be Self-
organizing
• They learn & adapt their behaviors to survive
If the adaptation strategy is good they continue to exist
If the strategy is bad or non-existent they cease to exist
Global behaviors
happen without a • They can move from an ordered to disordered state
centralized controller unpredictably, and can be self-organizing
Reductionist • No centralized controller
approaches do not
describe global
behaviors
• Knowledge of the inner workings of each agent typically shed no
information about the global behavior/response of the system
11
12. Examples of Complex Systems
Dynamical/non-linear • Ant colonies
• Rain forests
Highly-coupled
• Communities where you live
• U.S. Power Grid
• The World Wide Web
Adaptive
• The Stock Marker
• Propagation of infectious diseases
Can be Self-
organizing • The Global Economy (financial system collapse 2008)
• The Occupy ?? Protest Groups
• Multinational corporations
Global behaviors
happen without a • The NASA employees and contractors who supported the
centralized controller Constellation Program
The various engineering organizations that developed specific flight
Reductionist hardware for Pad Abort Activities
approaches do not The NASA PM and SE groups that supported Constellation
describe global
behaviors
Complex Systems can be Technical(Engineered),
Biological, Social or some combination
12
13. Domains of Complexity
Social Technical
Complex Engineering
Organizations
Socio- Technical
Creating Complex
Engineered Systems
13
14. Why is a Complexity Science Framework
Important to the SE Community?
Current SE processes consists of experientially-based guidance.
Although this guidance is tailorable, it is not deterministic.
There currently is no theory, nor “science of system engineering” that
enables us to predict the efficacy, resilience or robustness of the systems
we produce.
Our gut tells us that organizations impact the products we create but
we have no analytical tools to express the relationship between the two.
A complexity science framework encourages us to question the
existence of dynamical relationships where we formerly assumed no or
linear relationships existed. This includes interactions between social
systems and technological systems.
Many of the basic tenets/tools of complexity science are quite familiar
to engineers that work in dynamical systems (chaos, non-linear behavior,
neural networks, genetic algorithms, graphical modeling & simulation
tools tools, etc.)
14
15. What are the building blocks needed to grow a
competency in Complex Engineered Systems?
??????
Listen, Share and Solve Explore, Understand,
problems across Integrate social systems
disciplines & use new complexity into our decision
tools in novel ways. making & SE processes
Holistic Systems Uncertainty-Based Statistical Thinking &
Thinking Modeling and Simulation Probabilistic Uncertainty
[ embrace non-linearity ] Tools and Techniques Analysis
15
16. Potential Domain Infusions
Science of Trans-disciplinary
Socio-Technical Engineering
Systems Science
Social Technical
Complex Engineering
Organizations
Socio- Technical
Creating Complex
Engineered Systems
Engineering of Systems Engineering
Activities
16
17. NSF/NASA Workshop on Design of
Large-scale Complex Engineered
Systems
February 7-8, 2012
Arlington, Virginia
Organizers:
Steven McKnight, NSF Vicki Crisp, NASA
Christina L. Bloebaum, NSF Anna-Maria McGowan, NASA
George Hazelrigg, NSF Michael Lightfoot, NASA
Paul Collopy, University of Alabama, Huntsville
17
18. Workshop Overview
Objective:
• Examine the challenges unique to large-scale complex engineered
systems
• Examine how we can better prepare for a future of growing system
complexity?
Four Topic Areas Explored:
1. New approaches to system complexity by framing it through a
‘complexity science’ lens.
2. Current developments in design science and how might they help
us in designing within the SE process.
3. Awareness of what is known in organization science and how the
engineered product is a function of the organization.
4. How decision science can provide a more rigorous approach to
decision making in large-scale project teams.
18
19. Who Attended the NSF/NASA Workshop
on The Design of Large-Scale Complex
Engineered Systems?
• A total of ~115 people in attendance
• Government:
NSF, NASA, DoD (ODASD, AFRL, AFOSR, ONR, NRL, ARL), V-DOT
• Academia (25):
University of Illinois at Urbana-Champaign, University of Minnesota, George Mason University, University of Maryland, Northwestern University,
University at Buffalo – SUNY, Purdue University, Schulich School of Business, York University, North Carolina State University, Georgia Institute of
Technology, Pennsylvania State University, Texas A&M University, Oregon State University, Stevens Institute of Technology, Johns Hopkins
University, University of Virginia, University of Michigan, University of Florida, Brigham Young University, Massachusetts Institute of Technology,
Iowa State University, Stanford University, George Washington University, Mills College
• Industry & Others:
Lockheed Martin, Boeing, MITRE, SpaceWorks, Global Project Design, Google, NAE and
others
• Disciplines Represented:
Engineering, Social Science, Cognitive Science, Organization Science,
Anthropology and Economics
19
20. My Workshop Takeaways
• Systems Engineering as practiced is laden with human decision making which
could be enhanced by the understanding & practice of decision science
• SE needs to embrace nonlinearity and embrace a future where the systems we
build will not be fully testable (within the current practice of V&V).
• In order to better design & build large-scale complex engineered systems of the
future we need to 1st build better relationships between:
– Complexity Science Researchers
– Engineering Design Science Researchers
– Organizational Science Researchers
– Systems Engineers (PM+SE)
– Optimization Researchers
– S & T Leaders within Government Agencies
• Government participant agreed to form a Community of Practice to exploit unique
strengths that NSF, NASA, and DoD can bring to the challenge of large-scale
complex engineered systems.
20
21. Agenda
Complexity Challenges in the Integration of
Systems and Organizations
Does Systems Engineering Need an Overhaul?
• Looking at Complexity from the Outside In
• Complexity & Teams
• Dialogue
21
22. Looking at Complexity from the Outside In
a fresh look including outside our current processes
Ed Rogan
NASA PM Challenge
February 22, 2012
www.gpdesign.com | info@gpdesign.com
30. Agenda
Complexity Challenges in the Integration of
Systems and Organizations
Does Systems Engineering Need an Overhaul?
Looking at Complexity from the Outside In
• Complexity & Teams
• Dialogue
30
31. Complexity & Teams
What multi-disciplinary research shows
about behavior in socio-technical systems
Bryan Moser
NASA PM Challenge
February 22, 2012
www.gpdesign.com | info@gpdesign.com
Slide 31
44. Agenda
Complexity Challenges in the Integration of
Systems and Organizations
Does Systems Engineering Need an Overhaul?
Looking at Complexity from the Outside In
Complexity & Teams
• Dialogue
44
Our systems are bigger, more expensive, more visible and have become critical to our economic well being and national defense.
4. How if coupled with a ‘value driven design’ approach a team can reduce the dynamics of reactionary & ad-hoc decision making especially when design rework is required.
We have relied on process – how do we pay attention to empirical evidence? Have we painted ourselves into a process and IT corner?
Research from U Tokyo mid 1990s. Industrial experience. 12 years. 100s of projects. 1000s of models.New actors and architecture leads to surprising demands for coordination – unlike what was previously embedded from years of stability
[Fayol 1916] Fayol, Henri, (in French), Administration industrielle et générale; prévoyance, organisation, commandement, coordination, controle, H. Dunod et E. Pinat, Paris, 1916. English translation, General and industrial management, Pitman, London, 1949[Tuck 1912] Addresses And Discussions At The Conference On Scientific Management held October 12 . 13 . 14 Nineteen Hundred And Eleven, Dartmouth College. The Plimpton Press, 1912[Weber 1924] Weber, Max, The Theory of Social and Economic Organization (1947 translation by. A.H.Henderson and Talcott Parsons), Simon & Schuster, New York, 1924[Simon 1962] Simon, Herbert A., The Architecture of Complexity, Proceedings of the American Philosophical Society, Vol. 106, No. 6. (Dec. 12, 1962), pp. 467-482, 1962[Burton 1995] Burton, R. and Obel B., Strategic Organizational Diagnosis and Design: Developing Theory for Application, Kluwer Academic Publishers, Boston, 1995
Capacity and behavior! The characteristics of human attention and learning. The aggregation of results, rather than just decomposition.
[Malone 1994] Malone T. and Crowston, K., “The Interdisciplinary Study of Coordination”, ACM Computing Surveys, March, Vol. 26 No. 1, pp. 87-119, 1994
Team size, experience, capacity, time zone, differences in coordination behaviors,…
Screenshots from GPD’s TeamPort and a recent industrial case
(the need for information is pent up; if the teams involved have not interacted over years then their shared tacit knowledge is small, and thus demand to interact suddenly very high)
deNeufville and Scholtes, Flexibility in Engineering Design, 2011, MIT Press[Moser 1998] Moser, B., Kimura, F. and Suzuki H., "Simulation of Distributed Product Development with Diverse Coordination Behavior", Proceedings of the 31st CIRP International Seminar on Manufacturing Systems, Berkeley, California, May 1998[Moser 2009] Moser B., Grossmann W., and Murray P., “Simulation & Visualization of Performance across Subsystems in Complex Aerospace Projects”, Proceedings of the 2009 PMI Global Congress, Orlando, Florida, USA, 2009