Updated: Apr 4
I developed the following lecture for the PLM Road Map & PDT Fall 2021 (cimdata.com). In it, I discuss how Systems Engineering is following a Blind Men and the Elephant paradigm, where we assume (wrongly) that individuals can understand the entirety of the system by understanding it's component parts. To understand complexity, Systems Engineering is not enough, we must adopt Systems Thinking.
From the conference program:
Rising to the challenge of engineering and optimizing . . . what?
How should we rise to the challenges currently facing mankind and society as complexity is increasing into limitations caused by resource constraints, sustainability and global warming? In this talk, Dr. Hillberg makes a distinction between Systems Engineering and Systems Thinking, and between Complicated-ness, and Complexity.
There is no more urgent task in developing a sustainable future than continually upskilling the new (and old) workforce. Are academic systems designed for this? And what about the classic Systems Engineering methods - are they ripe for a major disruption?
In this talk I speak on both the GM Ignition Switch and the Boeing 737 Max. For in-depth articles on same, see My Writing.
I was also interviewed by Craig Brown of The Digital Enterprise Society as part of their extensive podcast series: 141: Solving Complex Problems with Systems Thinking - Digital Enterprise Society.
Other Thinkers on Systems Complexity
Additional perspectives can be found at the Complex Aerospace Systems Exchange, including
Transdisciplinary Perspectives on Complex Systems
A Complexity Primer for Systems Engineers
Interactions Among Components in Complex Systems
Mastering Complexity Aerospace America Nov 2015
A Leader's Framework for Decision Making
(See the 3 minute video towards the end of the article.)
And this is a fun video on how pendulums will synchronize through systemic reinforcement, and towards the end of the video discusses the limitations of "Reductionism" (which is analogous to "Decomposition") in understanding complexity.