Author Archives: mike@groundedsystems.com

Wicked problems and category mistakes

Wicked problems and category mistakes

This is a brief introduction to the notion of a wicked problem. It is based on the highly-cited paper by Rittel and Webber (1973). The following characterise wicked problems:

  1. There is no definitive formulation. In a sense, formulating a wicked problem is the problem
  2. There are no stopping rules. The process of intervening is also the same as understanding the nature of the problem – the intervention is “good enough” or the best that can be achieved within other limitations (e.g. of time, budget…)
  3. Interventions are not right or wrong, they can only be viewed as making things better or worse for certain interests i.e. the intervention has made things both better and worse depending on who you ask
  4. There is no immediate or ultimate test of an intervention. Interventions will generate “waves of consequences” over a period of time
  5. Interventions are “one-shot operations”, experiments are difficult to conduct, every intervention counts significantly, they are essentially unique in nature
  6. No enumerable, exhaustively describable, set of possible interventions
  7. Every wicked problem is essentially unique. “Essentially” implies that aspects may be common, but to think in terms of categories or “classes” of wicked problems with common “solutions” is misleading
  8. Wicked problems can be considered as symptoms of other problems i.e. there is inherent systemicity in the world
  9. Can be contested at the level of explanation, there is likely to be conflicting evidence or data

The corollary of this definition is that certain statements about problems are likely to be rendered false or meaningless if it can be shown that the problem is actually wicked, in effect the statement is demonstrating that a category mistake is being made. The following is not an exhaustive list:

  1. ‘Solving’ or ‘curing’ a wicked problem is a contradiction; there are no ‘solutions’, ‘cures’…
  2. Words that suggest an objective point of view used in the context of the problem at the very least need to be debated e.g. words like optimal, best, right, smart, correct, … all suggest the question – for whom? Alternatively, no decision taken should ever be considered wrong.
  3. Any statement of measurable quantity that supports an argument for the problem getting better or worse without acknowledging the dynamic complexity that systemicity implies i.e. “…worse then better…” is a more believable statement given dynamic complexity
  4. Statements that appear to deny the systemic nature of the problem e.g. ignoring requisite variety
  5. Containing irrefutable assertions of fact e.g. “…this proves conclusively that…”
  6. Use of binary choices, any mention of “silver bullets”
  7. Misrepresenting or ignoring plurality e.g. “The public…”
  8. Emphasis on producing plans rather planning as a process

If any of these corollaries are contested e.g. if someone claims to have a solution to a wicked problem, then they are likely to be making a claim about only an aspect of the problem, or only from a certain viewpoint; or their formulation is not that of a wicked problem i.e. they are talking about something ‘tame’. Statements that contain phrases like “…optimal solution…” or “…this proves conclusively that if we do this we will have the best outcome…” in the context of a wicked problem definitely signal a likely category mistake.

Category mistakes are a warning sign – be sceptical of claims being made. They suggest either misunderstanding or partiality.

It’s worth reading the Rittel and Webber paper. Despite its age, it still does an exceptionally good job of reminding us of the characteristics of wicked problems that’s just as relevant today.

The first steps towards a coherent approach to problem formulation can be found in Rosenhead’s (1996) introduction to Problem Structuring Methods.

Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155-169. doi:10.1007/BF01405730
Rosenhead, J. (1996). What’s the problem? An introduction to problem structuring methods. Interfaces, 26(6), 117-131. doi:10.1287/inte.26.6.117

A short guide to System Dynamics

A short guide to System Dynamics

This guide was produced to help explain System Dynamics modelling to a group of interested stakeholders for a modelling workshop. However, if you have the time I would really recommend reading John Sterman’s textbook for a definitive account:

  • Sterman, J.D. (2000). Business dynamics : systems thinking and modeling for a complex world. Boston: Irwin McGraw-Hill.

Otherwise this short paper summarises the key points

  • Sterman, J.D. (2001). System dynamics modeling: Tools for learning in a complex world. California Management Review, 43(4), pp. 8-25. doi: 10.2307/41166098

And if neither are available, or time is really short, then try this SD-Introduction-MY-20200527.pdf from me.

Hard Systems and Soft Systems

Hard Systems and Soft Systems

A frequent problem I come across when discussing hard and soft systems views with engineers is that the terms ‘hard’ and ‘soft’ are rarely defined clearly. Based on conversations I’ve had over the years at the University of Bristol a common position can be characterised by the statement “all hard systems are embedded in soft systems.” I used this myself in a CSER conference paper in 2011 when talking about the EngD in Systems programme where I teach. However, since then I have arrived at the position that the epistemic shift that Peter Checkland and Susan Holwell describe is a more useful way of characterising hard and soft systems views [1]. Instead of the rather vague association of soft with the social world, people, and human intentionality, the soft systems view moves away from this ontological commitment and treats the definition as a question of epistemology, i.e. what can we know or find out about the world? The following quote from [1] spells out this epistemological position in a way that I find compelling. It is:
“phenomenologist, social constructivist, avoiding ontological commitment – sees the perceived (social) world as: culturally extremely complex; capable of being described in many different ways; and sees the “system” as one useful concept in ensuring good-quality debate about intentional action. The two observers both agree that the notion “system” can be useful, O seeing it simply as a name for (parts of) the real world, E seeing it as a useful intellectual device to help structure discussion, debate and argument about the real world.”
Where observer O corresponds to the ontological position and observer E to the epistemological. This is all usefully summarised in a table that I use with my students adapted from the original in [1]:
Hard and Soft Systems Viewpoints

Checkland and Holwell’s paper appears in a volume edited by Michael Pidd [3], which brings together the ideas developed in the Interdisciplinary Research Network on Complementarity in Systems Modelling (INCISM) Network that was funded by the Engineering and Physical Sciences Research Council (EPSRC).

John Morecroft was part of the network too and in his work on System Dynamics modelling [2] reflects on how it should be used in this soft systems sense. He paraphrases Checkland to state “… system dynamics modellers do not spy systems. Rather they spy dynamics in the real world and they organise modelling as a learning process, with the project team, to discover the feedback structure that lies behind the dynamics“.

Reflections on this hard/soft complementarity and the work of the INCISM network at the System Dynamics conference in 2004 are captured in the notes from the record of the plenary session Working Ideas, Insights for Systems Modelling: The Broader Community of Systems Thinkers.

All of this is neatly summarised by Peter Checkland himself in a colloquium delivered at Lancaster University in 2012. In this short video, Checkland outlines the development of Soft Systems Methodology emphasising its role as methodology, not method, and the origin of this particular definition soft systems as the systemic learning system designed to help us deal with the complexity of the world.

[1] Checkland, P., & Holwell, S. (2004). “Classic” OR and “soft” OR – an asymmetric complementarity. In M. Pidd (Ed.), Systems Modelling: Theory and Practice. Chichester: John Wiley & Sons, Ltd.
[2] Morecroft, J.D.W. (2007). Strategic modelling and business dynamics : a feedback systems approach. Chichester : John Wiley & Sons, Ltd.
[3] Pidd, M. (2004). Systems modelling : theory and practice. Chichester: John Wiley & Sons, Ltd.

Systems modelling in engineering

Systems modelling in engineering

The wider and more pervasive use of appropriate systems modelling techniques would have a beneficial impact on the way in which engineers deal with messy socio-technical problems. This class of problems is commonly defined by the following characteristics; i) difficulty on agreeing the problem, project objectives, or what constitutes success, ii) situations involving many interested parties with different worldviews, iii) many uncertainties and lack of reliable (or any) data, and iv) working across the boundary between human activity systems and engineered artefacts. All systems models attempt to conceptualise, via appropriate abstraction and specialised semantics, the behaviour of complex systems through the notion of interdependent system elements combining and interacting to account for the emergent behavioural phenomena we observe in the world.

Engineers have developed a multitude of approaches to systems modelling such as Causal Loop Diagrams (CLDs) and System Dynamics (SD), Discrete Event Modelling (DEM), Agent Based Modelling and simulation (ABM), and Interpretive Structural Modelling (ISM) and these are all included in my programme of research.   However, despite their extensive use, there still exists a number of research challenges that must be addressed for these systems modelling approaches to be more widely adopted in engineering practice as essential tools for dealing with messy problems. These systems modelling approaches as used in current engineering practice provide little or no account of how the process of modelling relates to the process of intervention (if any). This is in part due to the wider challenge to address the poor awareness and uptake of Problem Structuring Methods (PSMs) in engineering, the current inadequate way of integrating these more engineering-focussed systems modelling approaches into PSMs, and lack of understanding in how to deploy them appropriately in addressing messy problems in specific contexts. There is also the need to interpret the current state of the social-theoretic underpinning to systems modelling into a form that is appropriate for use in engineering. This need arises from the endemic atheoretical pragmatism that exists in engineering practice. The lack of methodology supported by suitable theory to counter this i) hinders the development of understanding why methods work or not, and also what it means for them to work, ii) acts as a barrier to communication between practitioners and disciplines, and iii) has ethical consequences, as pragmatic use of methods raises the problem of instrumentalism.

Addressing this methodological challenge is currently a central core of my work. I believe this research is transformational in that it integrates academically disparate areas of expertise in engineering, management, and social science, into a coherent articulation of systems modelling for engineers.