In the last post I wrote about systemic change as the conditions or structures that hold a situation in place. I introduced the six conditions for systems change by Kania, Kramer and Senge and showed the little inverted triangle that puts the conditions in neat boxes and a clear hierarchy – the deeper ‘down’ the condition, the more influential over the system. I also introduced again the systems iceberg, which has a similar hierarchy and logic.

These two things – the neat boxes and the implied hierarchy – kept bugging me. I know that in complex systems things are never that neat and never linear causal – there is not one thing in one box that leads to another thing in another box or to an observed behaviour. Reality is messier. I also missed the dynamics in these diagrams – how are these structure created, how do they persist, how do they change? So I want to follow up on this in this post.

Stable structures are better seen as wobbly patterns

When thinking what would be a better way to look at systems change that would not rely on neat boxes and hierarchies – and somehow triggered by discussions in a podcast on a totally different topic – I remembered that some complexity thinking make a point that in complexity, you need to be able to see things both as structures but also dynamic and constantly renewed patterns at the same time. A bit like in quantum mechanics, you need to see particles as both particles and waves at the same time. Only when you have a specific question and you look closer (or measure), then they are forced to become either one, depending on you, the observer and how you observe.

I remembered that Jean Boulton, Peter Allen and Cliff Bowman in their 2015 book Embracing Complexity described this phenomenon in a very accessible way. I adapted the title of this blogpost from one in their book: the future is a dance between patterns and events.

For Boulton, Allen and Bowman, patterns include institutions, routines, norms, and system maps. Hence, the use of the concept of patterns and not structures or conditions makes the idea more generally applicable, but essentially, the structures and conditions humans build to bring order into their lives are nothing but patterns.

Now here is the important point:

If patterns sustain, then we feel they provide the information we need to predict the future. We think they can be studied ‘scientifically’. In many cases our response to identifying these patterns sharpens them and locks them in, as we refine our behaviour to respond to their predictions and try to ‘game’ the systems; investment bubbles would be an example here. These patterns, however, are always in practice ‘wobbling’ or fluctuating because they are, in reality, made up of a collection of individual and varied actions and behaviours.

Boulton, Allen and Bowman (2015: 29-30)

This idea of patterns being ‘wobbling’ somehow stuck with me. The structures around which we organise our lives – policies, practices, relationships, power dynamics – are a bit like a negative space built by us staying out of it , reinforced by written rules and stories (‘you don’t go there, child’). Only in very few cases they are physical; more often they are continuously reconstructed by our behaviour: continuously not doing something creates a constraint (‘don’t speak to strangers’) while if everybody does something in a specific way this creates an attractor (‘we tidy up after playing as we prefer living in a tidy place’). And as our behaviours fluctuate, these structures wobble. Yet when we observe or measure them, we put them in boxes and give them a more fixed form than they may actually have.

How patterns change – and why maps only work when things are stable

According to Boulton, Allen and Bowman, patterns change through events. Events can be external shocks, larger-than average fluctuations or the coming together of several diverse factors. Events can invade patterns and may cause them to shift, to ‘tip’ into something new, either very quickly or in a slow process.

The future is a complex combination of (a) the effect of current patterns, which can be studied – at least to some degree – scientifically and analytically, and (b) the effect of particular events or variations at particular times and places. These two factors – enduring patterns and specific events – through interacting together, shape what happens. … Current patterns form the context in which events may or may not gain impact and so may or may not stabilise them. Thus the future unfolds through the patterns that have been established in the past interacting with current events or variations. The future state of the system is, in this way, path-dependent.

Boulton, Allen and Bowman (2015: 31) – emphases in original

In systems thinking, people are mapping the structures of a system and create large maps to analyse the determinants of certain problems or issues and change them (fining the ‘root causes’ and ‘leverage points’ is the language often used here). According to Boulton, Allen and Bowman this works well in stable times when the patterns are not changing that much and are relatively simple to describe. Often when things are stable, the causality between elements of a system can be described and they are often fairly linear.

Where things are very stable over a long time, the macro-characteristics of complex systems tend towards behaviour that looks machine-like and predictable: i.e. the patterns can be readily identified, modelled, and understood. This is why we can find that separable causal relationships are adequate descriptions of stable situations.

The nub of the matter, though, is that, whilst such simple systemic analyses are helpful in describing stability, they tell us little about change – what may cause it and what may emerge as a result.

Boulton, Allen and Bowman (2015:32)

Implications for living in unstable times

These days, with COVID-19, we are not at all in a stable situation. Many of the structures that we took for granted – that we quite literally thought are stable and will never change – are now up in the air. And knowing and mapping the structures does not help us to predict where they will fall once things stabilise again. Many discussions are currently happening on whether things will go back to ‘normal’ (i.e. to how they were before) or whether there is no going back to normal after the pandemic and the events have already shook the structures so they will change for good. But also if you buy into this second view – and I do –, we can still not predict what trajectory these newly arranged patterns will put us on. Many hope, for example, that we can take this chance to reorganise our economy so we can slow down environmental degradation and climate change while at the same time build a more just and equal world. Others think that capitalism and extractive thinking will still dominate the patterns and lead to more destruction and inequality – only setting us up for the next crisis. The only way to predict the future at the moment, as Steve Jobs would say, is to create it.

This is certainly an extreme situation. Yet we often face uncertainties and shifting structures also in situations that are more harmless in nature and smaller in scope. What helps us in such situations is not solely to create a detailed map of the stabilities in a system – even though understanding these stabilities is relevant to understand the history and current context. But in addition, we need to be able to continuously take in and observe the events and changes that happen and build our situation awareness. We need to make sense of these inputs and act in appropriate ways. In order to do that, we need to sense what types of challenges we are facing – whether they are stable and ordered and thus manageable by using leverage points or established practice or if they are complex and emergent and require us to experiment and explore in order to allow new practices to emerge. The Cynefin framework is a useful framework to approach such questions.

Decision-making horizons are much shorter and we need to be able to live with questions we cannot answer. Last week the UK government decided that the lockdown in the UK was to continue for at least another three weeks but what will happen afterwards they could not say. The data to make that decision is simply not available at the moment or not clear enough. We need to hold that uncertainty until we have new and better data. Many people struggle with this.

My job has always been to help people in situations of change and uncertainty to make sense of what is happening around them and so they are able to take meaningful action. This ability proves particularly valuable during crises of the scale of the COVID-19 pandemic. If you find yourself in need of support to make better decisions in times uncertainty, don’t hesitate to reach out.

Resources

Boulton, J., Allen, P. and Bowman, C. 2015.  Embracing Complexity: Strategic Perspectives for an Age of Turbulence. Oxford, UK: Oxford University Press.

Feature image by Photo by Ahmad Odeh on Unsplash