Thinking of trees, not icebergs
“Philosophers have only interpreted the world, in various ways; the point, however, is to change it” – Karl Marx
Ever since I started learning about Systems about 20 years ago, and whilst exploring how to intervene in existing Systems, I’ve struggled to find the right analogy that is capable of encapsulating all the terms and concepts related to a System.
What I wanted was something akin to what I’d read in Yate’s The Art of Memory, called ‘The Palace of the Mind’. You see, in the Mediaeval period, the key constraint on retaining information was the retention and recall capability of one’s own brain. So memory training was a big feature of Mediaeval education, particularly before writing was a common form of communication.
With this in mind, I wanted something like a mnemonic, something that provided a map of as much of the territory as possible. And withstood changes in environments and contexts – that could hold-up in most of the circumstances I needed to apply it in.
You don’t have to look far in Systems Thinking literature until you come across the Iceberg Model. The model is ubiquitous, and designed to highlight how superficial common thinking can be, and how much that influences events and situations in the status quo is imperceptible and prone to go unseen. When I discovered it, it made a lot of sense about the importance of what can be seen and what needs to be dug a little deeper. Over the years, I gradually replaced the idea of the Iceberg with another concept. It was the idea of a Tree.
Here, I’ll propose an alternative Fruit Tree model which I have found provides greater depth, utility and variety. It also allows us to model a theory of direct experience of our environment, as well as anchoring on cues already embedded in how we think about problems. Crucially, it’s already embedded in how we speak about problems. Systems are difficult things to mentally model in the first place. My proposal allows a tangible model that is easy to interact with and manipulate hypothetically.
In this article, I hope to convince you that it’s a more obvious paradigm, because the way we commonly speak about systems is clarified and amplified with it.
The Iceberg Model
Origins: Various attributions have been made, with the earliest attribution I’ve been able to trace being Senge (1990, 1999). etc. Other routinely cited attributions are Kim (1999, 4), Donella Meadows (2009, 88), Dennis Meadows & Sweeney (2010, 243), Bryan, Goodman & Schaveling (2006), Cababa (2023, 139–143).
The model contains 4 layers of concepts, of which the observable events (1) are above the surface and visible, whilst 2–4 are obscured under the surface.
2. Patterns / structure
3. Underlying structures
4. Mental model(s)
Using this diagram, Donella Meadows framed a set of 12 interventions into Systems. In descending order from easiest and most observable to hardest to change and most obscure. The two models don’t precisely line-up, but I’ll make an attempt. Here’s a summary of how Meadows described them (I’ve reversed the order from lowest to highest impact as Meadows presented it, into highest first), juxtaposed with Senge’s Iceberg:
Benefits of the model
- Communicating how systems work
- Ordering one’s own mental model
- Using the model to navigate where you are
- how to structure change?
- Depth of the real changes, and the immovable, glacial scale of change.
Issues with the model
- Teaching an abstract concept with an abstract concept. People tend not to have first-hand experience of icebergs on which to draw.
- Doesn’t extend to exposing intervention points.
- Provides inaccurate cues for how events are embedded from structures. The layers imply they are separate when they cannot be.
- Assuming all paradigm shifts create glacial change is inaccurate, and often is seen as a barrier to enacting any form of change (observable in clauses such as: ‘it’ll take too long’, ‘it’ll take more cost and effort than we can devote’, ‘we don’t have enough time’).
Icebergs tend to be, famously, things that cause ships to sink. Whilst this mental model provides a structure to understand how systemic change/interventions are likely to sink when crashing into the status-quo, it also suggests the immense and imposing scale of the challenge.
But I’d like to provide a more optimistic alternative.
The Fruit Tree Model
Taking the same elements, we can reorder and present an alternative structure. But this structure provides great insight into how the system operates, where you are in the system, and where to engage its leverage points.
So with this in mind, let me talk about Trees.
Fruit Trees begin from seeds, grow into saplings, where their roots and branches extend and split outwards to maximise the available space. Roots capture water, whilst leaves capture light. As they grow, they reinforce their own ability to succeed at the expense of others in the vicinity.
Let’s now apply this concept to build a model, whilst highlighting how these same concepts do not appear in the Iceberg Model, in 9 reasons:
Growth: From the depths of structure and mental models grows the trunk and structure of the model in which we exist. As the branches divide and separate, they expand their surface and maximise their surface area. And from those branches manifest fruit. Inversely, therefore, and to translate back into Systems terminology: an event is an outgrowth of the structure and patterns of behaviour, just as fruit is an outgrowth of the branches. The patterns and behaviours are an outgrowth of the infrastructures, as the branches are the outgrowth from the trunk of the tree. Expansion and contraction are viable modes of change.
Information transmission: as Meadows stated in her work on how to influence and change systems, the hardest but most effective type of intervention is to introduce paradigm shift. This means intervening in the roots, and how this changes the growth of the fruits. The Fruit tree analogy directly demonstrates this interrelationship.
Separation and unification: The concept of bifurcation and fractality is embedded in such a model, and also demonstrates a much closer relationship from the There’s also the flexibility to update the fruit in order to explain about favourable events as Apples, or less favourable as Lemon trees. There’s also the variety in describing events as healthy or rotten apples, or as green or red apples. This analogy allows for greater depth and anchoring for folks who are new to Systems Thinking.
Mirrored structures: the seen and unseen are directly equivalent, rather than shown as the largest hidden structures. The ancient Alchemists once theorised that the form and structure of the unseen is the same as that which can be seen, which they summarised in their statement: As above, so below. The tree model shows the basic model as derived from both upper and lower components that both are derived from each other.
Encapsulated: All self-contained systems have their own hardened boundaries to protect it from the outside environment. The tree’s bark, the insect’s carapace, the mammal’s skin. Even chemical boundaries, like the ‘skin’ on hot soup in a cold room, or the planetary tectonic plates on a liquid magma core, or the o-zone layer. All examples of how subsystems preserve their integrity and isolation, with a boundary.
Accessible: you can look out the window and point at a tree. You can describe the features of it, and look together whilst explaining to someone why a tree is like a system. Also, people tend to have better and more meaningful intuitive understanding of trees than they do of Icebergs. This intuitive understanding can be leveraged to accelerate their understanding of Systems.
Scalable: the best thing about a Tree model is that it scales from a System into a System of Systems. In common parlance, we say ‘missing the wood for the trees’, or ‘missing the bigger picture because of a focus on the smaller’. In systems thinking, this means to focus on the part and miss the whole. A wood as material, or a Wood as a collection of trees adds additional scalability. If we expand the concept of a tree into an ecosystem, and consider the connection between them as an orchard, then we also expand the viable space of the analogy. In which case, we may explore the interconnectivity and latticework of Systems. Another phrase embedded in English is the concept of ‘Reap what you sow’. In other words, if the mental model used to produce the system was not considered over the long-term of its behaviour, then it may be possible for it to have lasting and unintended consequences.
Uprooting systems: Deracination is a fancy term, meaning to uproot. Systems change is capable of uprooting existing infrastructures. Interestingly too, the concept of roots is also similarly embedded in our language. The term ‘radical’ literally means ‘to return to the root’ (from the Latin word radix, from where we still have the word Radish), or in systems terms to address the root, and return to first-principles. Entrenched mental models are those that have ‘dug in’, and are difficult to uproot.
The downfall of systems: In the Dao de Jing, there’s a reference to Positive Feedback loops, in reference to a tree. ‘It is the largest and strongest tree that is most ready to be chopped’ (Chapter 76). With this in mind, there is also an indication of the natural and logical decline of successful systems. The translation to Systems Thinking is the limits to growth archetype.
A cross-cultural embedded analogy: there is another reason why trees are a better analogy. For many cultures, there’s already an embedded and accepted understanding of trees. Demonstrably, ancient cultures also used the tree as a proxy to understand the complex world around them. Things that ‘come to fruition’, or long-term work that ‘bears fruit’, investing in positive outcomes as ‘reaping what you sow’, also work well with this mental model. In Norse Mythology, Yggdrasil was the tree that presented the universe. Splitting and creating variations. In Confucian mythology, the I Ching (Book of Changes) catalogued all the variations and combinations possible from a binary system, based upon a theory of extremes (Taiji-tu, commonly known in the West as ‘Yin-Yang’). And the list goes on Lao Tzu’s 10,000 things. Microcosm/Macrocosm, omnia ab uno, omnia ad unum. Isaac Newton’s apple tree from Summer 1666, The eating of the forbidden fruit in the Garden of Eden. These are only a few simple examples, but there are many, many more.
Sense-making and intervention: another benefit of the model is to figure out where you operate within the context of a tree, then you’re able to create effective interventions.
We can apply this mental model to various problems, by treating a given System as a Tree. Take a team, a business, a society, a country or even an economic model. We can understand the System by inspecting the components of the tree.
Take Capitalism, for example. One of my common examples, mainly because it’s easy to understand and captures a meta-concept from which all mental model decisions about business, production and other systems are made.
Let us first observe the State as it currently stands. What is present in the structure of the system overall, let us call ‘the status quo’. The status quo takes the entirety of the System as one, as derived from decisions and choices. In fact, the status quo is the outcome of the total sum of choices. These are the decisions consciously and unconsciously, intentionally and unintentionally made. The system doesn’t miraculously or spontaneously appear. It is the aggregate of all the choices made.
In our case, for example, our current form of Capitalism is the result of a Mental Model proposed by Milton Friedman in The Shareholder Primacy (‘The Friedman Doctrine’, 1970). With the profit-incentive and growth-incentive as the two seeds for decision-making over 50 years, the result is a positive feedback loop designed to amplify itself.
When a system is created on that basis, it is inherently imbalanced. The outcome is global wealth inequality, poverty, and eventual collapse. This is the pattern of all positive feedback loops without a balance mechanism. I’ve written about this in much more detail elsewhere. Further, Galabo (2023) explains this situation very well:
“The dominant paradigm of capitalism is fundamentally unfair. It nurtures inequalities and establishes power in the hands of a few people who have or who inherit control over the private or state resource systems (e.g., land, real estate, industry) that make up the wealth of nations and shape social, economic, and political processes. Whoever has or inherits the power to control these resources and to influence these processes is in an advantageous social condition to have better health, education, and access to employment. Social inequalities are driven by this unequal distribution of wealth, income, and power, which leads to inequities in people’s social conditions and differences in many aspects of life, such as housing and health. To tackle these inequalities, there is a need to provide support for alternative ways of distributing power and wealth to progress the equity agenda and increase collective control over the aspects that shape the lives of communities, particularly those that are socially disadvantaged and deprived.” (Galabo 2023, 43)
If a system ‘nurtures inequality’, and the purpose of a system is what it does (POSIWID, Stafford Beer), then the goal of this form of Capitalism can be claimed to be divisive. So a good question about a given System is ‘who does it harm?’. In order to answer this question, we may climb the tree, or dig down to understand the root causes. If the answer is that an existing system harms one group at the expense of another group, and is demonstrable as an outcome from a root assumption as shown in Table 2, then there is arguably a moral obligation to correct that System.
One basic assumption at the root of Capitalism is Darwinism (survival of the fittest, as a zero-sum game competing for resources), and the Hobbesian idea that life is naturally ‘nasty, brutish and short’. Aside from that there is also the assumption embedded in the concept of ‘Power’. We might define Power as the amount of control a single ‘node’ has in a network of nodes. Let’s personify the nodes. When a single node, let’s say ‘The Prime Minister’ or ‘President’, has an outsized ability to control the other nodes (in this example, ‘the electorate’) in the system, then that control must also be balanced with scrutiny by the collective nodes, and an inverse accountability for the outcome of implemented controls. We might say that the tail wags the dog, or the apple controls the tree. This is the design of a democratic system framed using Systems terms. In order to change any System, the ‘root’ assumptions must be challenged, and better ones proposed. There must be an alternative demonstrated, because criticism alone is impotent.
The physical and structural elements of Capitalism are individuals, and the collective productivity of those individuals referred to as a ‘Company’. Companies are incentivised to make economic gains, and to invent ‘flywheels’ (positive feedback loops) which self-boost the activity of the Company. Companies are ‘actors’ in a Capitalist System. They act in the interests of others, only in so far as they can reap a return for themselves from that activity. If a problem is not ‘lucrative’, then there is no incentive to intervene. As this process accumulates, the accretive result is a format known as ‘success to the successful’ archetype. Those that dominate quickly exclude those that do not. As Donella Meadows cited ‘According to the competitive exclusion principle, if a reinforcing feedback loop rewards the winner of a competition with the means to win further competitions, the result will be the elimination of all but a few competitors’ (2009, 3). Arguably, and observably, the viability of the economy cannot be determined by only a few players, but an environment that allows many players to play.
Using this model of fulcrum points within a given system allows us to make better predictions about the success. For example, reinforcing models of Capitalism are governments, which are reinforced by legislation and democratic systems. Attempting to change the system by not voting in a democratic election is the lowest form of change, with the lowest level of leverage. Lack of participation has no impact on the underlying infrastructure. Whether we use Bronfenbrenner’s Ecological Framework or Brand’s Pace-Layer Model, it is the elements interacting across layers that generate the events we can observe.
Only Paradigm Shift can truly change this, and that comes from a shift in perspective and mental models, across all actors within the System. With this example of leverage, and fulcrums, we can begin to talk about how to change a System from one to another, through another analogy.
Turning Lemon Trees 🍋 into Apples Trees 🍎
When we talk about systems that are favourable to the entities within it, then we might consider that system to be an apple tree. By the majority of Systems change and intervention work is designed to shift elements or even an entire system into one that supports the greatest number of entities within it.
For this reason, I use the analogy of Living in a Lemon Tree, vs Living in an Apple Tree. In which case, Systems Thinking works to change a Lemon Tree into an Apple Tree, sometimes going as far as a diseased Lemon tree. Working within the System we may use language around climbing the problem, wrapping both arms around the problem, or digging into the problem.
It’s not the object, but the configuration, that causes harm. Therefore you can’t distinguish different fruits in the analogy, only healthy and unhealthy (rotten) apples. Continuing the analogy, the gardener defines weeds as unwelcome or unwanted plants, by their own value judgement. This means there is not necessarily an objective definition of a weed. Therefore the same tree configuration creates events, but the definition of what is favourable to one group might be very different to another.
Using a standard method of the Five Why’s can help to dig down into the unseen and often unchallenged layers that make up the immediate problem. One way that this method can fail is that it can sometimes move across branches, and doesn’t descend into the realm of infrastructure or into mental models. The Fruit Tree model can help correct for that.
Planning and implementing interventions can also mean different things need to happen: Sometimes it means to pivot the structures that create the observable events. Other times, it means to change the paradigm of the tree itself. Cynefin Framework can help to model the kind of tree you’re working with, and establish which Tree you’re working in, and how deep the intervention needs to be in order to change the outcomes. In our example of Capitalism, in its dominant Friedman form, as we saw, might be claimed to be a system that perpetuates unfairness. One group must disadvantage another in order to define success (Galabo 2023, 43). A recurring theme of Systemic Design is to reduce harm and increase social fairness. A paradigm shift might be to redefine a design definition of done: A Design is complete when all potential and actual harms have been minimised. The mental model of living in a Lemon Tree rather than an Apple Tree offers a sense of the distance between social operating systems. By pivoting the tree at the root, and maximising the leverage.
Over the years, I’ve found this model useful. The more I’ve considered it, the more I find other applications within it. For example, plants grow towards the sources of their nutrients. If you orient a potted plant away from the sun, they will reorient to find the source of light. This effect is the same as any system having a goal, regardless of the circumstances the System encounters in its environment, it will always orient towards its purpose. This is a natural example of Negative Feedback and reminiscent of the more popular example of a Thermostat.
I’ve not even started with seasonal changes, and more molecular changes, the structure of the leaf or the fruit itself. For this reason, I’m certain there are many, many more useful analogies that can be made using a Fruit Tree. It encapsulates a large range of the variety found in any System.
The advantage of the model is that it complies with a contemporary worldview and therefore anchors on tangible and tacit experience. This having been said, there is also a clear limitation in using a prestructured hierarchical ontology. One challenge with using a hierarchical model is that it assumes a large distance between mental model and events, even though events are manifested because of the presence of those mental models. It therefore has a similar limitation to the Iceberg, despite going beyond it in the other ways covered here. The next step is to deconstruct the tree in a way that can allow any node to connect to any other node in a Reticulum (using a rhizome model). I shall leave this for a future article (see Post-script).
The Iceberg Model remains a great introduction to the inherent complexity of the Systems in which we exist and interact. But if you seek a model that contains all the insights of the Iceberg, but layers on many more insights then try the Fruit Tree model.
So next time you need to go beyond the Iceberg model, or you’re trying to figure out how a System works and where to intervene, try looking out the window at a Tree instead of imagining an iceberg.
A tree can be an anchor, a map, and a plan, which can and a means of collaborating better on the problem, all in one.
Give it a go, and let me know if it works for you too.
A tree is good, but its hierarchy is particularly fragile. Cut the trunk, or any other bifurcation, and the rest of the plant will be compromised. A much more ‘robust’ and ‘anti-fragile’ concept is the idea of the Rhizome, more commonly known as ‘grass’. As Delueze & Guatarri explained, “the rhizome is an acentered. nonhierarchical, non-signifying system without a General and without an organising memory or central automaton, defined solely by a circulation of states” (1975, 1). They continued:
“A rhizome has no beginning or end; it is always in the middle, between things, interbeing, intermezzo. The tree is filiation, but the rhizome is alliance, uniquely alliance. The tree imposes the verb “to be,” but the fabric of the rhizome is the conjunction, “and. . . and.. . and. ..” This conjunction carries enough force to shake and uproot the verb “to be.””
This echoes the sentiment that Meadows suggested, when she reminded us of a Rumi proverb: That the crucial part of true understanding is to understand the concept of ‘and’. This means we can effectively level-up our understanding by considering the interconnectivity of nodes, but also the interconnectivity of trees as nodes within an orchard system. Such an analogy forms a 3rd level of generality not found in the Fruit tree analogy alone.
As Professor Sweeting further questioned, “an ecology of bad ideas just as there are ecologies of weeds” – But whose weeds?”, suggesting that there are always multiple perspectives at play, whilst pointing toward the fact that “Sandra Harding described a kind of “strong objectivity” where the world is seen from those standpoints that are typically marginalised.” For this reason, “Bateson’s move is always to point to the relationships things are in, rather than the things themselves” (Prof Sweeting, Private Communication).
Level 1: Iceberg Model (Good)
Level 2: Fruit Tree (Arboreal) Model (Better)
Level 3: Orchard (Rhizome) Model (Best)
My deep and sincere gratitude must be extended to Dr Ben Sweeting (University of Brighton), for his additions and critique on the earlier drafts of this article. Thank you for helping me to think deeper.
- Bryan, Goodman & Schaveling (2006), Systeemdenken. ontdekken van onze organistiepatronen, Academic Press/ SDU.
2. Cababa (2023), Closing the Loop: Systems Thinking for Designers. Rosenfeld Media.
3. Chistopher Alexander: A City Is Not a Tree
4. Delueze, G & Guatarri, F (1975), A Thousand Plateaus: Capitalism and Schizophrenia, From Introduction: Rhizome. Translated by Brian Massumi (1987), University of Minnesota Press.
5. Donella Meadows (2009, p88), Thinking in Systems: A Primer, Earthscan.
6. Harding, S. (1995). “Strong Objectivity”: A Response to the New Objectivity Question. Synthese, 104(3), 331 – 349. http://www.jstor.org/stable/20117437
7. Harding, Sandra (1991) Whose Science? Whose Knowledge? Thinking from Women’s Lives. Ithaca, NY: Cornell University Press.
8. Kim, Daniel (1999), Introduction to Systems Thinking, available online at thesystemsthinker.org
9. Linda Booth Sweeney, Dennis Meadows (2010); The Systems Thinking Playbook: Exercises to Stretch and Build Learning and Systems Thinking Capabilities, Chelsea Green Publishing
10. Meadows, Donella (1999); Leverage Points: Places to Intervene in a System, available online at donellameadows.org
11. Senge, Peter (1990, 1999), The Fifth Discipline
12. Snow, T. (2020). Ecosystem Metabolisms and Functions: An eco-literacy framework and model for designers. FormAkademisk , 13 (4), Article 4. https://doi.org/10.7577/formakademisk.3370
13. Snow, T. (2020). Integrative Systems of Production: A framework and model for designers, based on ecosystem metabolisms and functions. FormAkademisk , 13 (4), Article 5. https://doi.org/10.7577/formakademisk.3791