FAQ
Systems thinking

A system is a set of interconnected parts that, together, produce an effect different from the sum of the effects of each individual part. Systems are found everywhere, from biological organisms like animals and trees to human-made structures like schools, cities, factories, and economies. They are characterised by identifiable parts that influence each other and collectively produce a unique result. Unlike a simple collection of elements without particular connections or functions (like sand on a road), changing the parts of a system can fundamentally change or even destroy the system itself. Intangible elements like pride in belonging to an organisation or academic excellence can also be important components of a system. Systems can also be nested within larger systems, forming hierarchies.

The systems thinking mode is a framework for understanding the world that recognises the interconnection of its different parts and how they influence each other over time. The goal of this approach is to promote this holistic view and encourage constructive dialogue about complex social systems by providing the tools and language needed to do so. Systems thinking encourages probing questions, bold assertions, and free revision, valuing learners and thinkers over experts and followers.

Systems surprise us for several reasons related to their inherent complexity and our limited perspectives. One reason is that we often draw inadequate boundaries around the systems we study, ignoring important stocks and flows that are external to our defined boundary but nonetheless influence the system’s behaviour. Another factor is the presence of time delays within systems (perception delays, response delays, delivery delays), which can cause unexpected oscillations or slow responses to interventions. Nonlinear relationships, where cause and effect are not proportional, also contribute to surprising behaviour; small changes can sometimes have disproportionately large effects, and vice versa. Furthermore, we tend to focus on individual events rather than the underlying behavioural patterns generated by the system’s structures. Finally, bounded rationality means that individual actors within a system make decisions based on limited information and local interests, which may not correspond to the welfare of the system as a whole, leading to unintended consequences.

Bounded rationality describes the logic that drives individuals or entities within a system to make decisions or actions that appear rational and beneficial from their limited perspective, but may not be reasonable or optimal for the system as a whole. Actors in a system are not omniscient; they operate with incomplete information, focus on immediate concerns, and often do not fully anticipate the broader impacts of their actions on the entire system. This means that individual decisions, even if rational from the actor’s perspective, can collectively lead to suboptimal or even harmful behaviour for the system. For example, a fisherman trying to maximise their catch to support their family might overfish due to limited knowledge about the state of the fish population and the incentives they face, contributing to the collapse of the fishery. Bounded rationality can create systemic traps, where well-intentioned individual actions lead to undesirable systemic outcomes.

Systemic traps are recurring patterns of behaviour in systems that lead to undesirable or suboptimal outcomes. Common examples include the “tragedy of the commons” (where individual self-interest leads to the depletion of a shared resource), “policy resistance” (where interventions aimed at solving a problem are thwarted by system feedback loops), “drift toward low performance” (where performance standards are progressively lowered), and “escalation” (where competing actors continually increase their actions in response to each other’s).

These traps are difficult to avoid because they are often fueled by the underlying structure of the system and the bounded rationality of the actors involved. Addressing them requires understanding the feedback loops and incentives that perpetuate problematic behaviour, and this often requires system redesign.

Leverage points are places within a system where a small change can lead to significant changes in its behaviour. However, not all leverage points are equally effective, and the most impactful are often the least obvious and most fought for.

Low leverage points include parameters (such as subsidies or taxes) and buffers (the size of stabilizing stocks). Intermediate leverage points involve stock and flow structures, time lags, and balancing feedback loops.

High leverage points relate to reinforcing feedback loops, information flows, system rules (incentives and sanctions), self-organising power, and ultimately, the system’s goals and the underlying paradigms or mindsets that shape it. Changing paradigms is considered the highest leverage point because it can fundamentally alter the system’s goals, rules, and information flows.

Paradigms, or mindsets, are the deepest leverage points in a system. They are the shared social agreements about the nature of reality from which everything else in a system flows—its goals, information flows, feedback loops, stocks, and flows. Paradigms are the wellsprings of systems. When the underlying beliefs and assumptions (the paradigm) that shape a system change, it can lead to radical and fundamental transformations in how the system operates. For example, moving from a paradigm of endless growth to one of sustainability can significantly alter economic and environmental systems. While paradigms are often deeply ingrained and highly resistant to change, contemplating the idea that current worldviews are not absolute truths can be incredibly empowering. Challenging and changing the dominant paradigm can open the door to new possibilities, different system structures, and previously unthinkable outcomes. This is where profound and lasting change can occur.

Stocks and flows are fundamental components of systems that help us understand their behaviour over time. A stock is an accumulation of matter or information at a given point in time, similar to a reserve or quantity. Examples include water in a bathtub, a population, or money in a bank. Stocks change over time as a result of flows, which are the rates of change into or out of the stock (e.g., filling and emptying, births and deaths, deposits and withdrawals). Understanding the dynamics of how stocks change in response to flows is crucial for understanding the behaviour of complex systems. Stocks typically change slowly, even when flows change suddenly, acting as lags, delays, buffers, or sources of momentum within a system. This buffering capacity allows inputs and outputs to be temporarily independent, allowing systems to absorb shocks and maintain a degree of stability.

What are feedback loops and what are the two main types?

Feedback loops are the control mechanisms within a system that allow a change in a stock to affect the inflows or outflows of that same stock, creating a closed chain of causal connections. They are the key to understanding why systems exhibit consistent patterns of behavior over time. There are two main types:

• Balancing (or regulating) feedback loops: These loops aim for a goal or stability. They work to maintain a stock at a given value or within a desired range. If a stock is pushed too high, a balancing loop will act to lower it, and if it is pushed too low, it will try to raise it. They oppose the direction of change imposed on the system. A common example is a thermostat regulating the temperature of a room, where the goal is the desired temperature and the feedback loop activates heating or cooling to reduce the deviation.
• Reinforcing (or amplifying) feedback loops: These loops amplify change. They cause a stock to grow or shrink exponentially. They are found wherever an element of the system can reproduce itself or grow at a constant fraction of itself. An example is interest on a bank account: the more money in the account, the more interest is generated, which is added to the principal, leading to even more interest, thus amplifying the growth of the stock of money.

• Feel the rhythm of the system.
• Expose your mental models to the light of day.
• Honor, respect and share information.
• Use language carefully and enrich it with systemic concepts.
• Pay attention to what’s important, not just what’s quantifiable.
• Design policies based on feedback.
• Take care of the good of the whole.
• Listen to the wisdom of the system.
• Place responsibility within the system.
• Stay humble, keep learning.
• Celebrate complexity.
• Expand your time horizons.
• Challenge the disciplines.
• Expand the boundaries of kindness.
• Don’t let the goal of kindness erode.