Shifting Patterns (Patterns of a Whole City)

Welcome to this first instalment of our 5-part interview series where we explore the question

‘How could eco-systems organise for greater impact?’

In this first instalment we chat to Sonja Blignaut and Tertius Nieuwoudt about how complex and adaptive systems and complexity thinking can guide our exploration of this question.

What are Complex Adaptive Systems?

Complicated vs Complex

Sonja – A good place to start is exploring the difference between two words we tend to use interchangeably in everyday language:  complex and complicated.

The root word for complicated is the word ‘plic’. It means enfolded.   If you imagine quite an intricate fold, like an origami fold, you can unfold it, fully understand it, and then replicate it.  So complicated systems can be figured out. They are typically closed systems; we know where they start and end and influence from the outside is limited. They can be controlled and are quite predictable. Examples would be machines like aircraft, IT systems and ordered processes like opening a new bank account. Human beings are unique in our ability to create these ordered systems.

This is the kind of the world that we imagine ourselves to be in most of the time, a linear and predictable world.  This is also what most of our schooling prepares us for: to be in a complicated, almost clockwork universe.

When we look at the word Complex, the root word ‘plex’ means entangled or braided together. Imagine brain neurons for instance. I can’t take your brain apart, look at the parts, look at the neurons to understand how your mind works, let alone something like consciousness.  If I tried, I would kill you, and I still would not have figured it all out, because mind, consciousness etc are emergent phenomena.

So complicated ordered systems are equal to the sum of their parts, but complex systems have emergent properties that I can’t understand just by looking at the parts. I can’t reduce these systems to their parts. They are messy systems, open to their environment and interconnected in ways we can’t fully observe or understand. Over the last two and a half years, with COVID we’ve been given a bit of a masterclass in entanglement and in this notion of nonlinearity, because we’ve all seen how something small can have a big, or even a system-wide impacts.

A Ship of Chaos

Think of the Ever Given for example, the cargo ship that got stuck in the Suez Canal. In the greater scheme of things, that was quite a small, localised event, but it caused disruptions throughout supply chains all around the world. This is an excellent example of non-linear, when we interventions in complex systems, small local actions can create quite a big impact. Whereas big system wide interventions can either do nothing or make things worse.

Complex systems require us to think beyond linearity and neat categories.  They are not organised in neat hierarchies like the ordered systems we’re used to. In our attempt to create order, we have created categories everywhere, think for example of disciplines in tertiary education and research, or silos in organisations.  The problem is that the challenges we face in cities and social contexts don’t honour our categories. For us to be able to respond to them, we should connect across boundaries. We must maximize diversity. We could work not only in interdisciplinary, but transdisciplinary ways.

How do these systems work?

Emile – The one thing that stands out is complex systems are greater than the sum of their parts. There’s an underlying synergy value. I suppose the counter of that is this underlying value could also be negative or is it necessarily positive? Is it necessarily the case that complex systems will arrange themselves for the greater good, or could this be the other way around? And if it is the other way around, how do you go about intervening in those systems where they become negative spirals instead of positive spirals?

Tertius – Most of these systems are myopic in a certain sense: short-sightedness that leads to self-destruction. The beauty is not the certainties, but the probabilities and the principles that you apply within the context. The self-organization of adaptive systems prioritise survival, but if we put a noble cause into the system, like you are doing now, then we can apply certain principles to almost manipulate the system, to create synergy, learn from nature.

When I explain the difference between complicated and complex, I try to say complicated is quantifiable, but complex has got the X in it, the ‘unknown’ in maths. There will always be the unknown, the mystery, and working with that.

Sonja– I agree with Tertius in that it’s very context dependent. When I’m asked a question and I’m not too sure about the answer, I respond with “the only answer that’s always right in complexity is ‘it depends’”. Linking back to the idea of nonlinearity and the way complex adaptive systems self-organize, they don’t always organise in ways that are intentional. Instead of defining them as positive or negative, which begs the question of ‘Who decides that?’ Dave Snowden talks about beneficial emergence and non-beneficial emergence, so positive and potentially negative spirals.

Donella Meadows talks about leverage points. I don’t necessarily have an issue with that, but what that language tends to do is perpetuates this idea that I can control the impact I have on a system. We should make peace with the fact that whatever you do, there will be unintended consequences. And you have a responsibility to mitigate those.  How? Try an experimental approach. Work small and local so that if you do trigger unintended consequences, they are manageable.

One of the most important things here is to shift the way that we look at these things from a linear problem solution, approach, or mindset. If we can shift from thinking about problems that we need to solve to patterns that we can influence things open up a little bit.  Take something like systemic poverty – if we see this as something to fix, or solve I’m almost immediately paralyzed because where do I even start? If I can see it as a systemic pattern with many different influencers, many different role players, some are connected, some are not. I am not as easily stuck.  I have many potential entry points. Network theory really becomes interesting. Who should be connected, that aren’t’?  I also like to apply a flow lens to this. What needs to flow? Is it information, data, feedback, resources?  Where are the blockages to flow at the moment?

When things connect in different ways, then different things can emerge, different things can flow. Shifting from this analogy of a linear domino effect and the impact of a single domino to Dave Snowden’s notion of magnets often uses brings different thinking.

Magnets Beneath the Table

Theorists believe is that complex systems aren’t causal i.e., they’re not cause, and effect driven in the way that complicated systems are.  Instead, they are modulated.

“Imagine a metal table with iron filings on top and powerful electromagnets underneath.  If the polarity or strength of the magnets change, the iron filings will form different patterns.  If these changes are predictable, the patterns will be too, in complexity the changes in magnets are not predictable and they influence each other in unexpected ways.  So, we also cannot predict the patterns that will form in response to the magnets.  In complex systems, we call those magnets, Modulators.”

These modulators are factors or forces that impact on the system in ways we don’t fully understand.  As they interact, they create emergent patterns. So instead of looking for drivers or root causes, a much more generative question to ask is: what are the magnets below my table?  What are the factors, the forces, the influences that’s influencing or contributing to the emergent pattern that I’m dealing with? And given those, where might there be useful entry points for me to influence the system or at least learn more about it? This approach helps you experiment and get out of feeling overwhelmed or stuck.

You’re less likely to get stuck when you think in terms of patterns to influence, rather than problems to solve.  You can change the direction of the evolution.

Tertius – For me listening to jazz, helps me understand complexity better. It is just a few principles that needs to be followed and doesn’t matter how those principles came about. If it was by training or talent or experience, the fact is when you engage with the other band members, you need to create a song that adds value. That’s always the primary question, “Does it add value?” In the complexity, in the unknown, in pruning the garden, does it add value to the other elements in the system, can I somehow sync with the beauty and add value?

Sonja – There’s this wonderful notion in complexity called coherence. The difference between noise and a song is the presence or absence of coherence. There’s coherence in beauty. It’s not necessarily perfect or symmetrical, but there’s a coherence. It makes sense.

Eco systems are meant to bring coherence to complexity. There is beauty in that.

What story is being told?

Emile – How would one go about identifying the forces beneath that table for a particular environment? Is there some paradigm or a couple of paradigms that we could use to explore that?

Sonja – You probably need to start with choosing what that environment is.  Remember, you are dealing with open systems.  For example, where does a city begin and end?  Where do I draw the boundary?  Which level of granularity will I look at … do I look only at social systems?  Or also at infrastructure, resources, the natural environment?  Where do you draw the line?  This can be hard, but you have to draw a line to make it workable. You always must remember though that where you drew the line has consequences.  There were probably bias involved, you may have excluded one or more variables that might prove to be important. So having broad and diverse scanning networks and data flow is important.

You can never fully model the complex system because it’s continuously adapting. The model would need to be as complex as the system itself.

One good way to understand complex human systems is doing a narrative inquiry. Collecting stories from the people and communities that are part of the system you are trying to shift.  What matters to them?  What are their everyday experiences.  It’s important to gather stories because stories are actionable.   Much of what we are trying to achieve in systemic change is less about changing individual behaviour and more about shifting broader system patterns. Often is we can shift the environment that community’s function in, or the interactions between them, we can bring about sustained change that includes how individuals see themselves and how they behave.

The Warmth of Truth

Nora Bateson’s warm data approach, for example, is a workshop methodology that works quite well when you have enough diversity in the room. Warm data is the data that sits in the relationships. It’s about stories and how people, ideas and relationships intertwine.  Taking a warm data approach means that you can’t look at a city without looking at families, at businesses, at food systems and transport systems and then at the broader context of their society, politics etc. Everything is connected – patterns don’t emerge in isolation.

Gardeners not Chess Masters

Stanley McChrystal in his book Team of Teams, wrote, we need to lead more as gardeners than chess masters. If you apply that analogy to how we intervene in systems, it means we have two considerations. One is how do we make the soil more conducive to receive our seeds by understanding the need? The second is how do we seed the space with ideas and cast vision into this fertile ground?

This requires that we:

  • Work systemically in the environment, building relationships and networks to understand what the real needs are.
  • Sow seeds (the interventions we try) that are at least moving us in the right direction.  The point is that many seeds are sown at the same time, i.e., we try many diverse small interventions at once.
  • Monitor what happens, so that when something starts sprouting, we can add water and fertilizer. And when a weed grows (Unintended Consequences), we can pull it out while it’s still small.

We can’t design everything. We just need to get close enough to the system that we can interact and “dance with it”.  In the dancing you will discover what works, what doesn’t work, and what’s emerging.

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