#10: All systems are complex systems

On false distinctions.

I’m Luke Craven; this is another of my weekly explorations of how systems thinking and complexity can be used to drive real, transformative change in the public sector and beyond. The first issue explains what the newsletter is about; you can see all the issues here.

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Hello, dear reader,

Well, we are ten weeks in. I really didn’t expect to get this far! In the two years preceding the first issue of Pig on the Tracks, I only managed to publish eight blog posts. None of them came easy. Now, ten weeks into a weekly writing routine, I feel like I am only beginning to scratch the surface of the things I want to say. I’ve heard directly from many of you about particular issues that have resonated or made an impact. Please keep that feedback coming. While sometimes I am a scarily habitual human, I don’t think I can go another 42 weeks of lobbing missives and half-baked polemics into the void without hearing more from you! So be like Bruce Almighty and answer my prayers. Take this opportunity to let me know what you think, what you’d love to hear, or how you think this publication could improve.

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In the meantime, my aim in this issue is to tackle three interconnected points that speak to some common misconceptions about systems thinking and complexity.

1. All systems are open systems

An open system is a system that has interactions with an external environment. Those interactions can take the form of information, energy, or material transfers into or out of the system boundary. Because everybody loves a binary, it is common to distinguish open systems from their closed or isolated counterparts. In closed systems, nothing escapes the boundaries of a particular interaction and there are no external influences on its dynamics. To be bold, closed systems do not exist. Even the examples commonly cited—experiments in classical mechanics or reactions occurring in a test tube—are produced by and depend on particular forms of data production and analysis. They can’t be understood in isolation from context, culture, and history. That is the definition of an informational transfer. Their boundaries exist conceptually or analytically, but not in practice. While I’ve seen the idea of a “closed system” used as a convenient strawman by those looking to build awareness about complexity and systems thinking, even that’s a stretch. All systems are open systems.

2. All open systems are complex systems

If all systems are open systems, then all systems are complex. I’ve seen so much efforted wasted trying to distinguish complex systems from those that are “simple” (a.k.a. closed), “complicated”, or chaotic. These are false distinctions at best. All systems are complex, just complex in different ways. This doesn’t mean we shouldn’t try to draw boundaries around particular elements and dynamics to understand and influence them. Nor does it mean that everything is unknowable or beyond our control. What it does highlight, as Paul Cilliers, beautifully put it is that:

Boundaries are simultaneously a function of the activity of the system itself, and a product of the strategy of description involved. In other words, we frame the system by describing it in a certain way (for a certain reason), but we are constrained in where the frame can be drawn. The boundary of the system is therefore neither purely a function of our description, nor is it a purely natural thing. We can never be sure that we have ‘found’ or ‘defined’ it clearly, and therefore the closure of the system is not something that can be described objectively. An overemphasis on closure will also lead to an understanding of the system that may underplay the role of the environment. (p. 610)

Because what boundaries are and where they are drawn are always products of human description and behaviour they are inescapably complex. So too are the systems they seek to describe.

3. Complex systems can exhibit linear behaviour

Nonlinearity is so wound up in the idea of complexity. Complex systems are often called nonlinear systems. Nonlinear systems are often described as complex. Perhaps, then, it’s no surprise that so many people assume that complex systems cannot exhibit linear dynamics. When people say, for example, that linear, reductionist thinking is “bad” because the world is “very complex,” they imply that linear relationships between cause and effect don’t exist in complex systems. There is no evidence to support this implication. Just because some relationships in a complex system are nonlinear, doesn’t mean others can’t be linear, depending on where the boundary of a particular system is drawn. Cooking a meal involves complex, nonlinear interactions between ingredients with an emergent result but the process of turning a 2-person recipe to a 5-person dinner is a linear one. Complexity and linearity are both, at least in part, products of description. It doesn’t do us any harm to accept that linearity and complexity can and do coexist in the world. It does, after all, contain multitudes.

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By the way: This newsletter is hard to categorise and probably not for everyone—but if you know unconventional thinkers who might enjoy it, please share it with them.

Find me elsewhere on the web at www.lukecraven.com, on Twitter @LukeCraven, on LinkedIn here, or by email at <luke.k.craven@gmail.com>.