Three ways to visualise a complex system

Designing in complex systems is hard, but there are ways to help you understand

Published in

UX Planet

6 min readJun 29, 2020

The toughest challenges our societies are facing are complex by nature (i.e. they demonstrate the properties of a complex system). Think of the biggest issues facing us — climate change, ageing populations, poverty, healthcare crises, and inequality. These are complex challenges — there is no straightforward answer, otherwise they would have been solved by now. In order for us as designers to tackle these challenges, we need to understand the complex systems which these issues emerge out of.

As designers, our goal is to create better futures. But how can we do so if we don’t understand the complex systems in which we are designing and implementing our ideas?

Everyone designs who devises a course of action aimed at changing an existing situation into a preferred one.
- Herbert Simon

Because complex systems are unpredictable, any solution is not guaranteed to work and can backfire. This means that we need to sufficiently understand the complex system in which we need to intervene. The challenge for us is to understand these complex systems to design better interventions that make use of this understanding. Without this understanding, we risk designing change that results in worse futures, not better.

This post is based on my experience designing in complex systems around the world, in areas like Africa, Asia, the Pacific Islands, and Oceania — tackling issues like domestic violence, malnutrition, unemployment and inequality.

In this post, we will cover:

The distinguishing features of a complex system
Why visualising a complex system is a helpful tool for designing interventions, and
Three practical ways to visualise a complex system to create an intervention

What is a complex system?

A complex system has a few distinguishing features. Here, we will talk about three elements. A complex system:

Has many moving parts, which are interconnected and interdependent. This means that a change in one component can cause a significant change in another.
Is non-deterministic — that is, its behaviour cannot be predicted. The challenge then is to design and experiment with fail-safe interventions.
Displays the butterfly effect — and is sensitive to initial conditions. That is, different initial conditions significantly change the outcome. This means that you cannot just copy/paste design interventions into different contexts.[1]

Take the healthcare system as an example, it has lots of moving parts:

People (babies, children, parents, adults, older people, and carers) with varying needs and priorities.
Professionals (doctors, nurses, paramedics, government officials, receptionists, cleaners, interns)
Equipment (ventilators, needles, curtains, bed)
Infrastructure (hospitals, emergency wards, healthcare centres, doctor offices), and
Institutions (healthcare insurance funds, medical professional associations).

What do we mean by visualising a complex system and why is it important?

Visualisation is about drawing rich pictures — representing a real-world situation in a way that highlights its most important aspects. For example, think of the London subway map — it’s helpful in as much as it helps travellers use it to get from point to another.

When we’re visualising a complex system, the aim is to develop a more sophisticated understanding of the system by creating a shared mental model and language that we can use. The process needs to be collaborative and iterative, and as the complex system changes, so does its representation. [2] The desired outcome is to use our shared understanding to design and test interventions that produce the desired change.

Visualising a complex system helps us in a few ways:

Before we can solve a problem in a complex, we need to understand the areas where we can intervene. Visualising a complex system is essential because it helps us identify leverage points that we can target with interventions to achieve the desired outcome.
Complex systems are involved — and it’s difficult for us to fully grasp this complexity just by thinking about it. Visualising it helps us tangibly talk about the system, and have a standard frame of reference for the people working together to design an intervention.
Our goal of visualising a complex system is to make sense of people’s experiences in the context of the whole. The challenge is that everyone’s experience is different. If you talk to a doctor, their experience will be different — they might talk about the lack of resources and training. If you speak to a patient or carer, they might talk about the paperwork they needed to sign, cleanliness and attitude of doctors and nurses towards them. If you speak to the health-fund, they might refer to their numbers. Visualising the system helps you make sense of these experiences by seeing the whole picture.

What are the three ways to visualise a complex system?

Metaphors

A metaphor is when we understand one thing in terms of another. [3] This is helpful because it allows us to understand something we don’t know (a complex system) by using something we do know (the metaphor).

For example, in 2018, we were asked to visualise the Australian innovation system. [4] The trouble was, this project had been done quite a few times, using different ways of visualising a system. Through conducting our research, we found out that people’s experience of the system varied. One collective experience was that even when an innovator had a clear goal for their innovation, they needed access to a network of people, skills and expertise to achieve it. However, a lack of access results in setbacks and dead-ends.

We started generating ideas for how we could visualise the innovation system. One idea was to imagine it as an unlabelled shopping centre. You know the item you’re shopping for, but you have to go to lots of different places to find the right shop that sells that item.

After prototyping a few different ideas, we landed on another metaphor — a city. There were dead-ends for all the avenues people went to that weren’t helpful, graves for all the ideas that died, and an airport for the innovators that took their concept overseas.

Causal loop diagrams

Causal loop diagrams originate from the field of systems thinking — a discipline that focuses on understanding the behaviour complex systems.

Causal loop diagrams have two core elements — nodes and edges. Nodes represent the variables, while edges represent a connection or link between two variables.

Let’s illustrate this with a simple example. The variables (nodes) we have are food, energy and exercise.

The more food I eat, the more energy I have, hence the plus symbol. But, the more energy I have, the less food I eat (- symbol).
The more energy I have, the more I exercise. The more I exercise, the less energy I have.

Now you know that if you want energy, you should eat, and if you’re going to exercise, you should eat as well. This might seem like a basic example, and it is, but causal loop diagrams can represent a lot of complexity. For example, check out this causal loop diagram for healthcare!

A causal loop diagram for healthcare [5]

Physical representations

Some of us like to get our hands dirty, so this way is for you. You can use physical objects to represent a complex system. This helps people use their hands and work together to create a physical representation of the system.

You can use Lego blocks, or like in the photo, ice cream sticks, fluffy things, cardboard cards, paper cut-outs, ping-pong balls and blocks.