CASE Brainstorming Session: Complex Systems Primer
(39 attendees)
The session was moderated by Jimmie McEver, JHU/APL. Presentations were given by
Mr. McEver and Mat French, Rolls Royce. Overviews were provided in the briefings,
followed by group discussions and a wrap-up session to summarize and discuss next
steps.
Theme: The session was intended to engage with other CASE participants to share
resident knowledge and experiences about complexity, its challenges, and its
opportunities. The CASE events following this session would provide opportunities to
follow-up on ideas and cross-cutting themes introduced here.
Presentation: A Complexity Primer for Systems Engineers, Jimmie McEver
 The Complex Systems Working Group (CxSWG) of the International Council on
Systems Engineering (INCOSE) has been working to develop a primer to
introduce systems engineers to relevant concepts, frameworks, and methods
emerging from the study of complex and complex adaptive systems.
 Increasing complexity of systems requires more than simple extensions of
classical systems engineering (SE) practice.
 There is no consensus on a definition of complexity.
 Two definitions of complex systems are found to be useful:
o A system not describable by a single rule. Structure exists on many
scales whose characteristics are not reducible to only one level of
description. A system exhibiting unexpected features not contained within
its specification. (http://www.calresco.org/glossary.htm)
o A system with self-organization, analogous to natural systems, that
grows without explicit control, and is driven by multiple locally
operating, socio-technical processes, usually involving adaptation.
(Adapted from Braha et al, 2006)
 The opposite of “complex” is “decomposable,” not “simple.”
 A complex system (e.g., a traffic jam) is not decomposable, whereas a
complicated system can be understood by how its components interact with each
other.
 A number of hallmarks of complexity and their impacts on decision-makers were
discussed.
o Included such terms as interdependence, nonlinearities, open boundaries,
multi-scalarity, causal and influence networks, self-organization,
emergence, complex goals, adaptation and innovation, and opacity.
o Interdependency is the fundamental driver of complexity.
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o Opacity indicates that you don’t know everything about the system.
Complexity was discussed in terms of its sources, the relationship of objective
complexity to the cognitive challenges of subjective complexity, and how it affects
systems development
Complex systems were described in terms of Cynefin domains (Source: Kurtz
and Snowden, “The new dynamics of strategy: Sensemaking in a complex and
complicated world,” IBM Systems Journal, 42 (3), 2003)
The presentation addressed numerous selected guiding principles, the use of SE
methods, and the addition of analytic tools to the complex SE tool kit.
In a complex system, cause and effect are only coherent in retrospect and do not
repeat. It is characterized by interdependence, self-organization, and
emergence, Hence, new tools and approaches are needed.
In a complex system, the challenge is to define metrics in many different ways.
Deal with influence and shaping vs. design and control.
Use an adaptive stance.
o Identify and create variation
o Observe system behavior
Look at a system with different levels of granularity
Each representation of a system has its own perspective and you can’t know
them all in advance.
Complex systems engineering requires more than just tools.
A key role of the systems engineer is to facilitate understanding across
stakeholder communities.
The primer is in working draft form, but has not yet been vetted by the INCOSE.
Presentation: Aerospace Challenges, Mat French
 Discussed the work of the AIAA Aerospace Systems Integration Working Group
(ASI-WG)
o Has been developing a guide on challenges in aerospace systems
integration for the industry that addresses:
 Why/how traditional practice (typically) fails
 Guidance on what does work
 When (under what conditions) do new practices work
 How new practices should be done
 Why new practices work
 Mr. French’s presentation was intended to present some current issues being
experienced by industry; to foster awareness of the guide; and to seek inputs for
the guide from this group.
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Mr. French further explained the Cynefin framework using two current complex
systems for illustrative purposes:
o Commercial air travel, with its autonomous interacting parts, fuzzy
boundaries, self-organization, increasing complexity with time, and
changing environmental safeguards and security measures over time.
o Unmanned aerial vehicles, with their autonomous interacting parts, fuzzy
boundaries, self-organization, and increasing complexity with time.
Innovation in complex systems requires common focal domains for collaborative
consensus.
o Otherwise, competition for focal domains becomes based on preference
for action with a strong pull to domains based on individual capabilities &
perspective, and
o Innovation may be stifled through inappropriate application of capabilities,
tools, methods, organizational structure.
A set of industry observations on the sources of unexpected behaviors was
presented.
Aerospace development and integration challenges rely on
o Knowing the source of unexpected results;
o Identifying appropriate focal domains based on observation.
Group Discussions / Wrap-Up
The following questions were posed to the audience:
 State your name, organization, and what do you hope to obtain from this
conference?
 Have you experienced, or how would you approach recognizing, emergent
behavior? Did you plan for it, utilize unique techniques to exploit it, stumble across
it, etc?
 Have you implemented, or how would you approach, implications or corrective
actions for emergent behavior? Did you test for it, build into designs, utilize modelbased engineering, etc?
 Have you experienced, or how would you try to recognize, evolving or selforganizing interfaces that change during the course of operation and evolve due to
boundary interactions with the environment?
 Have you implemented, or how would you try to recognize, implications for evolving
or self-organizing interfaces? Were your tools, processes, organizational structure,
etc sufficient to capture evolving behavior?
 Can you think of a problem where you would want to design in emergent behavior?
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Insufficient time was saved to address each of the questions in turn, so general inputs
were solicited and offered: (No context was captured for the abbreviated comments
below.)
 There is much interest in solving…(the rest of the sentence wasn’t captured.)
 Human interactions and human behaviors
 Observing self-organizing behaviors
 People parts of an organization and how the organization affects SE
o Government often agrees, then changes position because superiors won’t
agree.
 Culture in organizations exhibit evolving behavior
o Use culture to work around evolving behavior
 It was noted that some experts won’t come to CASE because we aren’t speaking
their language.
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