Complexity in Unprecedented Times

Cameron Norman
6 min readApr 3, 2020

‘Unprecedented’ is a term that is changing how we understand complexity and foresight and what we need to do to act wisely in the world.

One thing that often makes complex situations live up to their name is that there is so much going on at once in different directions, velocities, and timing; it’s hard to connect causes with consequences.

We hear the term ‘unprecedented’ being used to speak of our current times. For those trying to understand what is going on, how we got here, and what it means that term takes on a meaning that is also unprecedented.

Let’s consider what this means through the lens of complexity.

Expert Failures

Nearly everything that we are seeing from the current pandemic has been seen before and much of it has been anticipated by experts in public health, economics, political science, journalists, and artists, in part.

In September 2019 — more than two months before the first sign of what would become known as COVID-19 — the journal Foreign Policy featured an article by science journalist and public health historian Laurie Garrett titled The World Knows an Apocalyptic Pandemic is Coming: But nobody is interested in doing anything about it. In that article, Garrett references the many calls and warnings from experts raised since the early 1990’s — a period that covers SARS (2003), H1N1 (“swine flu”, 2009) and MERS (2012) outbreaks along with multiple waves Ebola virus outbreaks during that period.

Even in Garrett’s prescient piece the scale and scope of what we are seeing at present with the COVID-19 outbreak aren’t foreseen.

The failure here is not of the journalists, scientists, policymakers, and others making predictions, it’s of the nature of the problem we face and the complexity of our situation. The more we grasp that the better we can wisely deal with the situation we have, not the one that we expected.

We have anticipated many parts of this pandemic, but the interconnections of people, transportation networks, cultural beliefs and practices, supply chains, financial policies, and historical trends have overwhelmed our ability to appreciate the myriad interconnections between them all.

What we are thinking are ‘wholes’ are actually parts of a bigger system. Our recognition of that is also unprecedented in shaping how we think about systems and live with complexity.

Believing and Seeing Complexity

Futures work has a complicated track record. At its best, it can support an adaptive approach to strategy, visionary evaluation, and enable us to anticipate possible issues before they arrive. At its worst, futures can lead us into realms of ‘fantasy’ that distract us from the situation at hand. It’s a fine line between the two as good foresight requires imagination, but it also requires data and explicit assumptions, which is something we are short of when it comes to the interconnections but not the things themselves. We are not lacking in data, only certain types of data and that matters when making statements about what is happening and prognostications about what is to come.

It’s in the latter part — data and assumptions — that we see the problems of complexity influence the former (imagination). While seeing is believing, sometimes we need to believe something before we can see it. This is particularly true in complexity. It is one of the reasons why, when it comes to complexity, good theories can be as practical as anything.

As the systems adage goes: the whole is different (and greater) than a sum of its parts.

Unlike previous outbreaks, economic downturns, or moments of social and political upheaval, we’ve got more data about more things that once was unimaginable. We literally have moment-by-moment updates of the number of COVID-19 cases by region and the globe at our fingertips. Where we once had quarterly or annual reports from our government on the state of things we are now receiving updates multiple times daily.

Add in the torrent of reports within the news, social media, and independent sources (like this) and we are drowning in information from the data fire hose.

What are we seeing and what are we believing?

Complexity Done Local: SVS

Drawing on the Cynefin Framework for sensemaking, we can see a lot of situations shuffling us between the various quadrants quickly. What was once chaotic where it was near impossible to discern order, we are now seeing situations that are quickly becoming complicated, even simple (consider navigation of shopping for household goods as the range of options winnows).

It is in this spirit that I provide a recommendation that is also unprecedented for systems change: to manage the complexity of our world focus on the smallest visible (or viable) system (SVS). In our efforts to shape the world we might do better focusing on our individual worlds first.

What we cannot appreciate now is the whole of our situation. It is too big, too dynamic, and just too complex; we don’t know where the boundaries are, the interactions are changing, and even who is involved with those interactions. Just consider the role of the grocery store clerk or delivery driver as true heroes and vital links in the public health chain.

This matters because as things change our assumptions and their effects on our models of reality might get carried with those changes and embedded into our future models, which will no longer work. The closer we keep our models to what we can influence, perceive, and integrate, the more reliable our models will be. The more reliable our models of reality, the greater coherence and meaning we can make of what’s going on and that’s when and where we can design and influence real change in a complex system.

Creating Coherence

Complexity requires we create coherence in order to act wisely. What we cannot do is create coherence without a means to appreciate the interactions that take place within certain boundaries. By seeking to deeply understand where we are, what we are doing, how we are having immediate effects on the system as we’ve drawn it, and what is immediately affecting us, we can better develop a ‘model’ that we can use to leverage a greater understanding of the whole.

This is similar to what the makers of the Sensemaker® software platform are seeking to do by looking at the aggregation of micro-narratives for systems understanding. The risk in this approach is that we seek to find — and thus codify — some ‘model’ of the situation that is static. I’ve seen this firsthand looking at complex networks of people where, when presented with a statistical model of a network to those people, the inquiry ends because of a belief that ‘we’ve now figured it out’ because we have a model.

What’s happening now is that we aren’t going to figure it out anytime soon. The dynamism is too much, the landscape too vast, and the stakes are too high. However, by exploring our own SVS landscape — whether that’s at a person, household, neighbourhood, or even community — we can build our sensory capacity for seeing systems and the complexity within them, interacting with complexity meaningfully, and enhancing our learning as a result.

It’s as if we are all citizen systems scientists.

Seeing through Valleys

The image above is a representation of our situation. We are in a valley looking around us with the prospect of seeing something beyond. The more we learn about our valley, the more we can see the hills and valleys beyond us.

By building some common frames of understanding and shared intelligence — used in both meanings of that term — we can better communicate with each other and learn together. By building coherence and understanding of our own SVS we can better see and share what’s happening with others’ systems. By learning from each other we can better start to make sense of what’s happening more broadly and then we might be able to take more informed actions to shape the world to come.

Note: It’s important to recognize that we don’t have the luxury of time to do this with certain aspects of the situation, nor do we need to. Infectious disease epidemiology and the public health measures recommended from science are largely complicated to understand, even if their consequences are complex. That means we can make sound recommendations based on the science for what to do and how to manage COVID-19 and where expert advice works best. We also know that things, like providing money or waiving fees, can keep people in their homes and businesses paying rent. That’s actually a very simple problem (if difficult to manage and administer). It is the larger social and economic issues tied to that that are complex. Let’s be careful about recognizing the nature of the problems we’re facing; not all of this is complex.

Lastly, if you’re struggling with how to think, act, and manage in times of complexity, I can help you. This is what I do for a living. Thanks for reading. Be safe and well.

This story is based on an earlier post on Censemaking.

Photo by Jamie Hagan on Unsplash

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Cameron Norman

Designer, evaluator, educator, & psychologist supporting people in making positive change, by design. Principal @censeltd @censeacademy