Why You Need Systemic Reasoning

This instinct to subdivide complex systems dominated scientific inquiry, and it advanced a framework that attempted to reorganize nature into deceptively simple components. This was the logic of reductionism, a way of thinking that can be traced at least as far back as Aristotle. Reductionism analyzed complicated things (bicycles, cities, humans) by breaking them down into distinct parts (wheels and gears, streets and people, organs and cells). In theory, everything is the sum of its parts. So if you understand those parts, you understand the whole.

Mark Bittman // Journalist and Author

We are conditioned to think linearly. Linear thinking is so ubiquitous that most of us don’t recognize it as a type of thinking. We think of it as, simply, thinking. Examples are everywhere: the scientific method, manufacturing processes, agricultural monocultures, business and other college courses, corporate hierarchies, and public education curriculum.

Being good at linear thinking is highly rewarded. In some cases, rightly so. Valuable things have emerged from linear thinking – like pandemic vaccines. The challenge is that linear thinking is also, assuredly, our biggest blocker. We might be able to change a thing or two but if we hope to transform anything, including digital ecosystems, linear approaches won’t get us there.

Linear thinking is binary

Linear thinking is also binary thinking. We imagine that everything can be defined by its opposite – black and white, right and wrong. Our de facto social constructs make a binary worldview seem normal. Product vs tech, Democrat vs Republican. People are black or white, gay or straight, a boy wearing blue or a girl wearing pink. We reinforce binary thinking by ignoring (or sometimes deriding) whatever doesn’t fit. For example, imagine a boy playing with dolls, how do people generally react to that?

Very few people, or real world circumstances, fit into our de facto social constructs. A binary label (like female) might help us understand something about a person but it doesn’t help us understand the person as a whole. Same with all types of systems, including technology systems. Understanding the parts does not necessarily help us understand the whole.

… black-and-white logic can sometimes work even for complex systems. But it ignores the ways in which parts interact with one another. Reductionism may serve to explain how a bird flies, but not how a flock of birds move in unison. It may describe internal combustion, but not traffic patterns. It may describe electric patterns in the brain, but not consciousness, and it’s unlikely that anyone or anything – not even the world’s most powerful computers – will ever fully analyze the interactions that make for healthy soil

Mark Bittman // Journalist and Author

When we define “success”, we usually mean the rewards for linear thinking. We like success; success is awesome. Alas, this definition of success often ignores the impact of the “success”. McDonald’s, for example, is a profoundly linearized model. If profit equals success, McyDs is mindbendingly successful.

If we add impact to the equation … on our physical wellbeing, children’s nutritional health, an economy of government-subsidized corn masquerading as chicken nuggets and milkshakes, poorer people, the rainforest shrinking from grazing cattle, the trash created by every single-use order … “success” is less clear.

Success, from a nonlinear point of view, is improvement of the system as a whole. Success means leaving things, overall, better than you found them … for everyone involved, not only the successful.

Linear thinking is limiting

Linear relationships are easy to think about: the more the merrier. Linear equations are solvable, which makes them suitable for textbooks. Linear systems have an important modular virtue: you can take them apart and put them together again— the pieces add up.

Nonlinear systems generally cannot be solved and cannot be added together. . . . Nonlinearity means that the act of playing the game has a way of changing the rules. . . . That twisted changeability makes nonlinearity hard to calculate, but it also creates rich kinds of behavior that never occur in linear systems.

James Gleick // Author and Historian of Science

Linear thinking can’t solve systemic challenges, like climate change, or design interrelated systems of components (like event-driven microservices). Our lives are interwoven with technology systems. To build and design those systems well, we need to think in systems.

We need to think in systems together. What we build will reflect our thinking … and shape it.

We have very little experience with nonlinear thinking. Especially when we are thinking as groups – which was aptly demonstrated by the year 2020. We don’t realize that the thinking we agree with – or disagree with – is often linear, binary and socially constructed. For example: “A woman’s most important work is mothering.” Perhaps we agree. Perhaps we disagree. Either way, this assertion is linear and binary. Our response is likely to also be linear and binary.

We work against systemic thinking

…Although people deeply involved in a system often know intuitively where to find leverage points, more often than not, they push the change in the wrong direction

Donella Meadows // Environmental Scientist, Educator, and Author

Systems are challenging, complex and counterintuitive. To improve them, we can improve our capacity for tackling hard challenges (together). Instead, we usually try to simplify too soon. We attempt to break challenges down into easy-to-linearize steps. We believe that this break down is actually possible and always preferable.

Complexity is “water logic” … what is “best” in one circumstance, or at one time, may not be “best” in a different circumstance, or at a different time. Mental fluidity and flexibility is required. Complexity is uncertainty, changes can, and often do, have unintended consequences. Some good, some not. Rather than a servant, complexity is a teacher, if we are in a learning mindset.

Yet, we imagine that current circumstances won’t change unless we allow them to change. We prefer “rock logic” — concrete and permanent answers to complex problems.

Counterintuitiveness is thinking that is contrary to intuition or to common-sense expectation but often nevertheless true. Grappling with it is inherent in systems thinking. Counterintuitiveness makes us feel confused and off kilter. When faced with that discomfort, we try to straighten. To try to reinforce what “feels right” or familiar, reassert what works even when we suspect it isn’t working.

And we know from bitter experience that, because of counterintuitiveness, when we do discover the system’s leverage points, hardly anybody will believe us.

Donella Meadows // Environmental Scientist, Educator, and Author

When faced with challenges, complexity and counterintuitiveness, rather than clarify the context (why are we doing whatever we are doing?), we often reinforce linear values instead. For example, when faced with uncertainty, we create a role that has power and control over others. We act on the idea that adults need to be monitored and supervised in order to get work done. They need to be told exactly what to do. Is that so? Is that so in this circumstance? We think linearly about time management, diet and exercise. Does this enable us to become, overall, more productive and healthier? Or simply busier?

(Likely, some of both.)

We are each a system amongst systems. Our bodies; our families and communities; the organizations we are part of; the ecosystems we live in; the nations, planet and universe(s) we inhabit are systems. Almost nothing in a system can be linearized.

Nevertheless, we persist.

We are moving from software to systems

Content management software defined the boundaries of a website. Individual people and large organizations installed a single piece of software to create a lovely digital space. They encouraged users to visit there and interact.

Now, many people and organizations want to COPE: create (content) once and publish (it) everywhere. A website is only one of many digital tools used for sharing, displaying and consuming information. Users are everywhere, interacting. Information from one piece of software is purposefully intermixed with information from others (though they are often incompatible) and then shared with still more.

The impact of this change is profound. Developing emerging digital systems requires expertise in 10Xs as many technology tools as the software alone did. And often, a very different mindset for everyone involved.

Yet, we transfer our linear thinking models and processes to our systems building. We might, for example, maintain feature-driven development, outlining “requirements” and model a conveyor belt of delivery. We concretize workflows rather than make them more fluid and flexible. We focus on designing linearly-governable parts while ignoring the relationships between the parts. We continue to stratify strategic decision making and structure people into silo’d teams to deliver it. We add more people to control the people doing the work. We attempt to mitigate all risk before taking any action. We accept “technical debt”, the impact of our successes, as a fact of life.

But what happens as complexity increases – when our software becomes one part of a larger system? When the relationships between software become complex? We invest a tremendous amount of energy into creating interrelated software systems using linear approaches. A feat that simply can not be accomplished.

We adopt new “modern” tools to move from software to systems … then build the exact same software.

For big, successful companies—now or in the past—it’s very difficult to get agile. Those companies have a legacy. They have grown, and most of them have been successful by actually using what we call a managerial hierarchy—a classical way of managing from the top down, with jobs, with boxes and lines and structures and process descriptions, running and controlling the company from the top. And now, when they try and put some experiments in place to be more agile, to give more space to people, to allow them to be more flexible, what happens? Well, when you are a leader and for 20 years you have been in a managerial hierarchy, what do you do when you really get fearful and uncertain? You go back to what’s worked in the past. You exert control, add things, add rules, add processes, add structure.

What you should do is actually a real act of leadership: you have to take things away. You have to reduce the structure, the processes. But that’s really difficult. It’s much easier and more comfortable to add things because that gives you a, maybe false, sense of control.

Wouter Aghina // Partner – Global Leader of Agile Organization and Transformation · McKinsey & Company

We need to cultivate systemic reasoning

The world is full of nonlinearities.

So the world often surprises our linear-thinking minds. If we’ve learned that a small push produces a small response, we think that twice as big a push will produce twice as big a response. But in a nonlinear system, twice the push could produce one-sixth the response, or the response squared, or no response at all.

Donella Meadows // Environmental Scientist, Educator, and Author

Linear thinking can not resolve systemic issues. Systems behave nonlinearly. No matter how well-meaning linear approaches are, they simultaneously reinforce existing structures in a system, structures that likely need to be deconstructed. Relationships in systems are emergent and changing – the human relationships need to change with it. When we don’t address systemic causes, and instead continue to tack on fixes, we simply encourage the problem to flow elsewhere. Linear approaches can not explicitly design healthier systems.

Linear approaches do, however, implicitly design our systems, if we don’t change them. We will always get a system that mirrors our thinking. To create healthier systems, we embrace healthier, nonlinear systems thinking approaches. Iteratively, we:

Discover the best possible solution or theory, under the circumstances, when conditions are uncertain.

We do this by focusing on the reasons that support our conclusions. Rather than debate “should we or shouldn’t we”, we work to strengthen our reasons for acting and make them as cohesive as we can. We improve our thinking and communication, in specific ways, ways that build trust and hel us navigate circumstances. We encourage leadership through:

Synthesizing knowledge, experience and good judgement into decisions based on valid reasons.

Systems thinking processes are grounded in collective, systemic reasoning skills. Systemic reasoning is the art and science of integrating our reasoning with our conclusions. While we simultaneously understand the context in which the conclusion is “best”. We look at challenges from high and low, left and right, as holistic a view as we can muster. Which allows us to take action, even in the midst of uncertainty, and learn from it.

This may sound like “overthinking” or “big up front design” … it is neither. Unfortunately, doing this work is an experience that words fail to accurately convey. Like mindfulness, if you’ve experienced it, you know what it means. If you haven’t, you’re probably not imagining it correctly. Likewise, if you’ve worked on a team that is good at systemic reasoning, you know it.

Teams good at systemic reasoning seek to gain necessary knowledge and experience, rather than strictly deliver on linear expectations. Which, counterintuitively, makes them more trustworthy. When figuring out “what to do”, they simultaneously develop a more mature understanding of why they are doing it. They communicate and test the reasons why an action is recommended. They proactively interweave multiple points of view to arrive there (they integrate other people’s expertise). They improve each other’s thinking and their ability to decide together by strengthening the mental models underlying their decisions. As the strength of their thinking and observing improves, they increase the likelyhood that they come to the best possible solutions, under the circumstances, even when conditions are uncertain.

Conditions are always uncertain.

They create success. A strongly agile, well-constructed systems approach often generates more trustworthy positive growth for teams than a linear one. Counterintuitively, perhaps, teams good at systemic reasoning are often the most productive teams. Rather than trying to force situations to bend to their will, these team arrive at the best possible conclusion they can. Which is all anyone can ever do.

When synthesizing knowledge, experience and sound judgement, we often overfocus on the knowledge part. Knowledge is an ingredient, not a meal. Relevant knowledge changes as systems change. The technology tools we are expert in today might be irrelevant five years from now. (They likely will be.) Rather than rely on whiteboard tests to demonstrate knowledge, we could ask people to demonstrate the positive impact they’ve had when applying their knowledge. Knowledge interwoven with experience and judgement helps us to become pattern thinkers … grokking how a system is working (or not) by the patterns it presents. Pattern thinkers can use current tools or adopt new tools and still deliver value.

Groups with specific expertise (in one programming language, for example) sometimes work against systemic changes (that would benefit them) because they’ve made knowledge King. Individual expertise trumps cultivating collective expertise. Despite the fact that, surrounded by the emerging complexity of everything, the ability to learn the next new thing is more important.

Nowadays, one person rarely has sufficient relevant knowledge or experience. Which is why we need to synthesize other people’s knowledge and experience.We are constantly combining information from different sources, expertise and experiences in order to construct an understanding of our circumstances. The ability to integrate other people’s knowledge and expertise into sound solutions is essential for systems.

Change is the one thing we can be certain about. Linear approaches attempt to dominate uncertainty, control change. Yet, circumstances are always uncertain. When we embrace uncertainty, we begin to see opportunities for structuring stability. We don’t need to make everything concrete to create stability. When we add water logic, we get more able to flow towards well-discerned choices and act in satisfying ways … even in the midst of nearly-infinite possibilities.

If you are interested in improving systemic reasoning, we are here to help. We give talks and workshops. We coach individuals leading systemic changes. And we design and deliver systems transformations to enterprise organizations.

Remember, always, that everything you know, and everything everyone knows, is only a model. Get your model out there where it can be viewed. Invite others to challenge your assumptions and add their own.

Donella Meadows // Environmental Scientist, Educator, and Author


Bittman, MarkAnimal, Vegetable, Junk: A History of Food from Sustainable to Suicidal. Boston, Houghton Mifflin Harcourt, 2021. ISBN: 9781328974624

Aghina, Wouter, and Aaron De Smet. “The Keys to Organizational Agility.” Edited by Monica Murarka and Luke Collins, McKinsey & Company, McKinsey & Company, 16 Feb. 2018, The keys to organizational agility .

Meadows, Donella HThinking in systems: a primer. White River Junction VT, Chelsea Green Publishing, 2008. ISBN: 9781603580557

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