3 Core Paradigms
In A Brief History of Systems Thinking, we explored the evolution of this multifaceted discipline, tracing its roots back to efforts to model and predict relationships between variables in hard systems, such as government and defence operations. These early approaches relied heavily on mathematical tools and computational models. However, as theorists began to grapple with social or ‘soft’ systems, those shaped by human behaviour, culture, and values, systems thinking became messier, less predictable, and less amenable to purely quantitative modelling. Over time, the field has expanded to encompass both hard and soft systems, but significant tensions remain. A long-standing divide persists between the two approaches, with many theorists accepting that they are fundamentally incommensurable.
In this chapter, we will explore the contrasting theories of Systems Dynamics (SD) and Critical Systems Thinking (CDT) to illuminate these paradigmatic differences. Using the complex challenge of the U.S. healthcare system as a case study, we’ll examine how each paradigm approaches the problem and why understanding their distinctions is essential for anyone studying systems thinking.
US Healthcare through the CST and SD Lens
The death of the United Care CEO amid the turmoil of the U.S. healthcare system offers a sobering entry point to explore the differences in epistemology and utility between critical systems thinking and systems dynamics. These approaches, though related under the systems thinking umbrella, offer distinct ways of understanding and addressing complex problems. By unpacking their respective methodologies and applications, we can better appreciate the roles they might play in solving entrenched issues like those plaguing healthcare.
Systems Dynamics: A Focus on Feedback Loops and Behaviour Over Time
Systems dynamics, pioneered by Jay Forrester (1961), is primarily a modelling approach. It examines how elements in a system interact over time, focusing on feedback loops—both reinforcing and balancing—and stock-and-flow structures. The goal is often to simulate system behaviour to predict outcomes and test potential interventions.
In the U.S. healthcare context, systems dynamics might be used to model the interrelationships among insurance premiums, hospital admissions, administrative costs, and patient outcomes. For example, rising premiums might lead to fewer insured individuals, increasing reliance on emergency care, which raises overall costs and feeds back into higher premiums. By quantifying these elements and simulating scenarios, SD can reveal leverage points for reducing costs or improving care.
While valuable, SD’s reliance on quantifiable variables can limit its epistemological scope. It assumes that key system dynamics can be represented mathematically, potentially overlooking non-linear and emergent phenomena like shifting public attitudes or the role of institutional power. Moreover, SD models often presuppose an objective observer, which can obscure the modeler’s biases and the power dynamics inherent in system boundaries.
Check out this video for a quick introduction to Systems Dynamics:
Critical Systems Thinking: Questioning Boundaries and Power
Critical systems thinking, influenced by scholars like Michael Jackson (2019)and Werner Ulrich (1983), is less about building predictive models and more about interrogating the assumptions underpinning those models. CST asks: Who defines the system? Whose interests are served? What voices are excluded? It emphasises the plurality of perspectives and the importance of reflexivity in understanding complex systems.
Applied to the U.S. healthcare crisis, CST might begin with the framing of the problem. Why, for example, is the system’s dysfunction often reduced to questions of efficiency or cost-effectiveness? What about equity, accessibility, and social determinants of health? CST would challenge the structural biases privileging insurance companies and healthcare conglomerates while sidelining underrepresented groups such as uninsured individuals or marginalised communities.
Through participatory methods like boundary critique, CST could engage stakeholders, from patients and nurses to policymakers and insurers, to identify whose voices are missing and how problem definitions might shift with their inclusion. Unlike SD, which seeks to optimise within a given system, CST might question whether the current system should exist in its present form at all.
Complementary or Contradictory?
The death of the United Care CEO, a tragic emblem of the U.S. healthcare system’s failings, highlights the need for both approaches. Systems dynamics offers tools for understanding interdependencies and testing interventions, but critical systems thinking ensures these tools are applied ethically and inclusively. Together, they encourage a dual focus on technical solutions and transformative change.
In practice, leveraging both approaches might involve using SD to identify short-term fixes, such as reducing administrative inefficiencies, while applying CST to explore long-term structural reforms, for instance, moving toward a more equitable model of insurance. This synthesis would acknowledge that no single methodology can fully address the complexities of systems as deeply human as healthcare.
Ultimately, the U.S. healthcare crisis underscores a critical lesson: systems thinking is not a monolith. Whether through feedback loops or reflexive inquiry, the choice of approach profoundly shapes the solutions we imagine and the futures we create.
Comparison of Critical Systems Thinking and System Dynamics
The points of difference between the two paradigms of systems thinking are summarised below.
| Criteria | Systems Dynamics (SD) | Critical Systems Theory (CST) |
|---|---|---|
| Focus | Quantifiable models and feedback loops | Power, ethics, and stakeholder inclusion |
| View of Knowledge | Positivist, objective modelling | Socially constructed and interpretive |
| Power Dynamics | Often overlooked | Central to analysis |
| Methodology | Single-method optimisation | Multimethodology and pluralism |
| Intervention Style | Top-down, efficiency-focused | Reflexive, participatory, emancipatory |
Table 1: Core paradigms compared
References
- Forrester, J. W. (1961). Industrial dynamics. MIT Press.
- Jackson, M. C. (2003). Systems thinking: Creative holism for managers. Wiley.
- Jackson, M. C. (2019). Critical systems thinking and the management of complexity. Wiley.
- Ulrich, W. (1983). Critical heuristics of social planning: A new approach to practical philosophy. Haupt.
- Ulrich, W. (2000). Reflective practice in the civil society: The contribution of critically systemic thinking. Reflective Practice, 1(2), 247–268. https://doi.org/10.1080/713693151
Unable to be compared or measured by the same standard due to fundamental differences in nature, approach, or perspective.
The branch of philosophy that studies the nature, sources, and limits of knowledge, focusing on how we know what we know and the validity of different ways of understanding
A feedback loop within a system where an action produces a result that influences more of the same action, amplifying the effect over time. This process can lead to exponential growth or decline, depending on whether the feedback is positive or negative
A feedback loop in a system that works to maintain stability by counteracting change. When a system strays from a desired state, the loop generates responses to bring it back into balance, promoting equilibrium over time
A method used in systems thinking to represent and analyse how quantities (stocks) accumulate or deplete over time due to inflows (inputs) and outflows (outputs). It helps visualise dynamic behaviours within a system
Relates to the study of knowledge—its nature, sources, limits, and validity
Behaviours or outcomes in a system where the relationship between cause and effect is not proportional or predictable. Small changes in inputs can result in disproportionately large or small effects, and feedback loops often play a critical role. Examples of non-linear phenomena include tipping points, emergent behaviours, and oscillations, where interactions within the system produce complex and dynamic outcomes.
Complex behaviours or patterns that arise from the interactions of simpler elements within a system, which cannot be predicted solely by understanding the individual components. These phenomena are a hallmark of complex systems.
The existence of multiple perspectives, ideas, or elements within a system or group
The ability to critically examine one’s own beliefs, assumptions, and actions, and how they influence and are influenced by the surrounding system or context.
A process in systems thinking that involves examining and questioning the boundaries of a system to determine what is included or excluded, whose perspectives are considered, and how these decisions affect problem framing and solutions. It ensures a more inclusive and reflective approach to analysing systems.
