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Transition

Definition

"Classical analytical problem solving works fine for isolated problems with pre-stated goals. Systemic methods, on the other hand, are especially helpful when many different stakeholders interact in a dynamic complex setting, where there is no initial consensus on the problem definition, the expected future, or a shared vision of what to reach.". Hieronymi (2013)

3rd-order approaches are therefore characterised by drawing widely from eclectic theoretical orientations of "systems theory" as defined and discussed in the diverse literature spanning biology, physics and mathematics through to social sciences.

Defining the qualitative boundaries between 1st- and 2nd-order approaches is difficult because 3rd-order approaches often use or borrow theory (e.g. concepts such as feedback and regulation, adapatation or learning, system instability and complex dynamics) and sometimes methods (e.g. mathematical and computational techniques) common to all three orders. However, 3rd-order approaches often use the concepts from 1st and 2nd-order approaches qualitatively rather than quantitatively or literally; for example, while a 3rd-order model might articulate the existence of negative feedback between two or more system components, we are unlikely to be able to produce a useful quantitative model that describes and makes quantitative predictions about the feedback processes using differential equations or state-space models. This mirrors what Checkland (2000) calls the "hard" and "soft" systems distinction (see also, Costa, 2019) where 1st and 2nd order approaches would be considered the former, and the methods used in SysteMatic's design process are "soft".

Approaches we have called 3rd-order are those that don't seek to optimise (1st order) or necessarily innovate (2nd order, systems engineering) on an existing model of a system (for example, improving patient throughput given a set of existing services and constraints to be satisfied) but rather, may help transition from an existing model of healthcare to something very different and re-imagined. This open-endedness implies that some of the resulting models or tentative proposals for a healthcare system are incompatible with how healthcare is currently understood or delivered; i.e. they may be unrealistic given the immediate and medium-term funding for acute and secondary care in hospitals. Indeed, Checkland's Soft Systems Methodology (reviewed in Checkland, 2000) emphasises that any formal model of a system is epistemological rather than ontological -- this means it is one perceived model of a system (components, relationships and abstractions) and there may be many candidate models that each depend on the author/stakeholder articulating them.

Hieronymi (2013) then provides an overview of systems principles, theories and their philosophical connections and outlines "systems approaches" that help ground these principles in practice -- notably, in the familiar iterative four-stage process of "Design, Plan, Intervene, Analyse" -- for comparison, see our MLTC-focused design process and the "double diamond" design process.

The overarching tenets of 3rd-order approaches are:

  • Inter- and transdisciplinary expertise
  • Theories of systems drawing from formal sciences, biology, social- and cognitive sciences
  • Taking a systems approach, inheriting from the above
  • A system is inherently open (rather than closed) with porous boundaries
  • The system exhibits non-linear or unpredictable behaviours (that are difficult to model using methods common to 1st- and 2nd-order approaches) and are context-dependent (Preiser 2019)
  • Systems are epistemological (rather than ontological) entities (Reynolds et al. 2016) consistent with soft-systems methodology (Checkland 2000). 3rd-Order approaches view any ‘system’ as one possible model of components and their relationships/dependencies that inextricably depend on the perspective of the agent articulating that model.
  • A system model will therefore vary with the level of abstraction adopted, the individual modeller and the appropriate methodologies and tools will vary accordingly.

Methods and Approach

Consequently, a 3rd-order approach naturally invites methodology/frameworks such as participatory design, patient-public co-design, soft-systems methdology (SSM) (Augustsson, Churruca, and Braithwaite 2019) and action research (Checkland 2012; Koshy, Koshy, and Waterman 2010; Meyer 2000) but importantly, does not exclude formal methods (Schwaninger and Grösser 2008) e.g. agent-based modelling and system dynamics (Liu et al. 2018). The emphasis on complexity as a function of unpredictable actors (people/professionals) and uncertainty that is difficult to capture using more familiar formal methods (as in 1st- and 2nd-order systems) but invite methods that include:

  • Sensemaking & visualising complexity: Design synthesis attempts to interpret and make meaning out of multiple interconnected/conflicting sources of qualitative and quantitative data, and to make it explicit through various forms of externalisation, modelling and visualisation.
  • Generate & test alternative futures: Transitioning systems requires envisioning futures that are not simply extrapolations of the present (Dunne & Raby, 2013). Methods such as critical design, speculative design, and transition design (Irwin, 2015) facilitate engagement with radical alternatives.
  • Non-linear, iterative/adaptive, co-evolutionary processes : Given the inherent unpredictability of complex systems, design-based approaches emphasise iterative processes including prototyping, adaptive learning, embedding feedback mechanisms Systems Shifting Design Report from Design Council
  • Distinguishes 'system-conscious design' i.e. design as practiced with an awareness of the wider system context and perception of interdependence, and ‘system-shifting design’ i.e. design with the specific objective of changing a system - a practice that is expansive and transcends rather than simply merges design with systems thinking
  • Being aware that no static 'solution' is possible to a living evolving web of interconnected problems - multiple points of intervention that collectively steer the system in the desired direction

Examples

A helpful summary of the field of general systems theory can be found in (Checkland, 2000) -- this paper articulates important historical connections between different scientific approaches to systems. We located three papers that survey the sometimes perplexing array of methods, theories and approaches in the field of systems science and thinking -- both of which help provide context and history relevant to undertanding the field (Cabrera, 2015; Checkland, 2012; Preiser, 2019). Checkland (2000) surveys a large body of work on SSM using social and health care as examples.

References and Further Reading

  • Augustsson, Hanna, Kate Churruca, and Jeffrey Braithwaite. (2019) Re-Energising the Way We Manage Change in Healthcare: The Case for Soft Systems Methodology and Its Application to Evidence-Based Practice. BMC Health Services Research 19 (1): 1–11. https://doi.org/10.1186/s12913-019-4508-0
  • Cabrera, D., et al (2015). A Unifying Theory of Systems Thinking with Psychosocial Applications. Systems Research and Behavioral Science, 32(5), 534–545. https://doi.org/10.1002/sres.2351
  • Checkland, P. (2012). Four Conditions for Serious Systems Thinking and Action. Systems Research and Behavioral Science, 29(5), 465–469. https://doi.org/10.1002/sres.2158
  • Checkland, P. (2000). Soft systems methodology: A thirty year retrospective: Soft Systems Methodology. Systems Research and Behavioral Science, 17(S1), S11–S58. https://doi.org/10.1002/1099-1743(200011)17:1+<::AID-SRES374>3.0.CO;2-O
  • Costa Junior, Jairo da, Jan Carel Diehl, and Dirk Snelders. (2019) A Framework for a Systems Design Approach to Complex Societal Problems. Design Science, 5. https://doi.org/10.1017/dsj.2018.16
  • Dunne, A., & Raby, F. (2013). Speculative Everything: Design, Fiction, and Social Dreaming. MIT Press.
  • Hieronymi, A. (2013). Understanding Systems Science: A Visual and Integrative Approach. Systems Research and Behavioral Science, 30(5), 580–595. https://doi.org/10.1002/sres.2215
  • Irwin, T. (2015). Transition Design: A Proposal for Advancing Design as a Transformational Discipline. Design Philosophy Papers, 13(1), 57-66. https://doi.org/10.1080/17547075.2015.1051829
  • Liu, S., Xue, H., Li, Y., Xu, J., & Wang, Y. (2018). Investigating the Diffusion of Agent‐based Modelling and System Dynamics Modelling in Population Health and Healthcare Research. Systems Research and Behavioral Science, 35(2), 203–215. https://doi.org/10.1002/sres.2460
  • Preiser, R. (2019). Identifying general trends and patterns in complex systems research: An overview of theoretical and practical implications. Systems Research and Behavioral Science, 36(5), 706–714. https://doi.org/10.1002/sres.2619
  • Reynolds, Martin, Emily Gates, Richard Hummelbrunner, Mita Marra, and Bob Williams. (2016) Towards Systemic Evaluation. Systems Research and Behavioral Science 33 (5): 662–73. https://onlinelibrary.wiley.com/doi/10.1002/sres.2423
  • Schwaninger, M., & Grösser, S. (2008). System dynamics as model‐based theory building. Systems Research and Behavioral Science, 25(4), 447–465. https://doi.org/10.1002/sres.914