Systems Thinking Part 2: Methodology
Once you understand the philosophy of systems theory then it is time to move on to find a methodology for using that philosophy. There are so many methods in systems theory. It can be used for businesses, engineering, social problems, education… etc etc etc. The applications of systems theory are endless. I will explain a few areas of methodology but will focus main on Soft Systems Methodology because this is my area of study… it is not, however, the most interesting application. I think chaos theory is probably the most interesting but I think my knowledge of it wouldn’t do it justice! I am however stoked about most methods in systems theory…
Peter Checkland (the guy I love most in systems theory) succinctly states that “Progress in the systems movement seems more likely to come from the use of systems ideas within specific problem areas than from the development of overarching theory.” (Checkland, 1999, pg 94) With this idea in mind it is important to know the philosophy but also to move forward from the philosophy to method (and ultimately intervention).
Chaos and complexity theorists began their methodology using math to show that much of what happens on earth is unpredictable (Gleick, 1987). A large system with a very small disruption or variance can have an extremely high number of outcomes which renders long-term predictions essentially impossible. This is interesting because the conditions within the system are largely predictable as they are determined by the parameters within the system. Gleik states, “The universe is randomness and dissipation, yes. But randomness with direction can produce surprising complexity”, and thus the goal now is to discover what the rules are that determine that direction (1987, pg 341)! Gleik’s book Chaos: Making a New Science shows a variety of complex and chaotic yet systemic examples of chaos such as Julia sets, chaotic mixing by Julio M Ottino, the Beluzov-Zhabotinsky reaction and even chaotic harmonies in music, which all demonstrate the wide variation of examples within chaos. There is now a philosophical argument among chaos theorists about whether or not this inability to predict is intrinsically a characteristic of the world or if it simply comes from human limitations of understanding the systems.
Gegory Bateson in Steps to an Ecology of Mine (specifically parts III and V) deals with cybernetics, introducing ideas such as the world existing as a series of systems comprised of individuals, societies and ecosystems (1972). In each of these different systems he found competition, dependency and adaptive changes that are dependent on feedback loops that controlled balance. These became termed “self-correcting systems” as they would, independent of any outside intervention, change variables to try and remain stable. Feedback, as described by Midgley is “…causal ‘loops’ where a system makes a change in its behaviour and receives information back from its environment about the effects of this behaviour, which is then used to determine future actions” (2000, pg 48). Bateson argued that all these systems are part of a supreme cybernetic system that controls everything and each is a self-regulating system within one large self-regulating system (Bateson, 1972).
System dynamics was developed by Jay Forrester in the 1950’s and was originally used in electrical engineering (1961). It uses computer modelling to show the organization and structure of a system. It can plot out these feedback loops in systems while simultaneously being able to see the connections to other variables.
Soft systems methodology is a subject that is concerned with “organized complexity” (Checkland, 1999, pg 6) and will be the of the rest of this post….because it’s my area of specialty.
Soft Systems Theory
In seven statements Checkland and Scholes describe why soft systems methodology is so useful (1999). They start by explaining that humans attribute meaning to their perceived world, and are interpretations of the world that can be experience-based forms of knowing. These interpretations can be used to improve situations and change the world. These steps become a cycle from which an epistemology of systems thinking is formed. Soft systems methodology, they argue, does this in a coherent process that becomes a learning system. It then provides the basis for using the learning cycle through meanings, intentions and purposeful action without hampering the individual approach of a person as the technique can be used fluidly. The tool of action research in soft systems methodology is contrary to subject/object research. In action research the researcher actively becomes involved with the object. They participate in the action and become part of the research, which is directly useful with the systems epistemology.
What is the technique?
Checkland’s initial soft system methodology was based on seven steps: 1. Find out a problem; 2. Express the problem; 3. Create a root definition of relevant purposeful activity systems; 4. Build conceptual models of systems in the root definition; 5. Compare the models with the real world; 6. Come up with systemically feasible and culturally desirable change; and 7. Action to improve the situation. Checkland suggests using the mnemonic CATWOE to define an adequate root definition where C is customers, A is actors, T is transformation, W is Welanshauung, O is ownership and E is environmental constraints (Checkland, 1999). While no human activity system or root definition is inherently relevant, this will help define an adequate definition for the system at hand and for the researcher’s purposes. It is also important to point out that human activity systems are not “real” things. They are systems that are compared to the real world. Thinking of them as real things misses the “essence of soft systems thinking, namely that it provides a coherent intellectual framework…an epistemology which can be used to try to understand and intervene usefully in the rich and surprising flux of everyday situations” (Checkland and Scholes, 1999, pg 24). Going back to the root definition, the core of CATWOE is the transformations, input and outputs and Welanshauung, the worldview (Checkland and Scholes, 1999). Transformations are descriptions of the desired outcomes of variables in the system. For example, an input could be the local population and the outcome is to have a better informed population. The Weltanschauung defines the worldview and values of those involved with the system, thus admitting one’s own biases, values and morals.
Checkland also describes five kinds of systems studies: 1. Systems design and implementation; 2. Sharp problem definitions; 3. Systems analysis of past events; 4. Aim is to survey; and 5. Purely theoretical (Checkland, 1999), allowing for various uses of systems that don’t necessarily use all the steps in the 7 step method. Another technique of the methodology is rich picture building. Pictures can be used to show human affairs as it reveals relationships much more effectively than words. The pictures, which can be built with various actors in the system, can express relationships and value judgements while creating a product that transcends language and cultural and professional barriers (Checkland and Scholes, 1999). Cultural issues and barriers are not only important in the development of a root definition or rich picture, and the stream of cultural enquiry should continue through the entire process (Checkland and Scholes, 1999).
The idea that soft systems methodology can be used in a more fluid way developed later. Originally soft systems methodology was thought to be primarily for problem solving, but this is now called thinking in “mode 1”. Experience in using the methodology quickly demonstrated that the language of “problems” and “solutions” was too simplistic and didn’t cope sufficiently with actions, norms, standards and judgements and with the changes of everyday experiences. Thus the language and methodology evolved to where there are no “problems” but instead “problem situations” and the methodology is used in a much more flexible manner instead of directly from step 1 – 7. It would also seem that now soft systems methodologies are based on systems ideas and a very particular epistemology. Thus anyone who claims to use the methodology should understand and express the systemic epistemology.
There are also methods for analysing the system in soft systems methodology to understand the problem situation, of which one is Analysis 1, 2, 3 (Checkland and Scholes, 1999). Analysis 1 is the analysis of intervention. This involves three roles: the client, would be problem solver and the problem owner. Analysis 2 is social systems analysis which looks at the continually changing interactions between roles, norms and values. Roles are social positions in the system; the expected behaviour of those in the roles is the norm; and the actual performance that is judged based on the standards within the system is value. Analysis 3 is an analysis of the political system. In this analysis it is understood that human situations have political dimensions associated with them. It is made practical by examining power relationships within the system (Checkland and Scholes, 1999).
Once the problem is defined or analysed and defined (pictorially or however appropriate those within the system), the researcher and system participants will make “desirable and feasible changes” (Checkland and Scholes, 1999). This change should be “systemically desirable and culturally feasible”; they need to make sense within the system and match the values and morals of those who have to live within it in the future. This way of employing soft systems methodology is much more mature and fluid than the original seven step methodology.
This is a pretty basic rundown of what SSM is. For a great application of SSM take a look at this pdf on a case study done in India (by my advisor). In the next and final part of this mini series I will look at intervention, explain my own use of SSM and put the philosophy and methodology together.
Works Cited In The Series (and all great books on systems theory):
Ackoff, Russell L. (1973). Science in the Systems Age: Beyond IE, OR, and MS. Operations Research 21(3): 661-671.
Bateson, Gregory. (1972). Steps to an Ecology of Mind. Chandler Publishing Company: Philadelphia, PA.
Bertalanffy, Ludwig von. (1950). An Outline of General System Theory. The British Journal for the Philosophy of Science 1(2): 134-165.
Bertalanffy, Ludwig von. (1956). General Systems Theory. General Systems Year Book 1: 1-10.
Capra, Fritjof. (1997). The Web of Life: A new scientific understanding of living systems. Random House of Canada: Mississauga, ON.
Checkland, Peter (1981) Systems Thinking, Systems Practice. John Wiley and Sons, Ltd: West Sussex.
Checkland, P. and Scholes, J. (1999). Soft Systems Methodology in Action. John Wiley and Sons, Ltd: West Sussex.
Churchman, C. West. (1968). The Systems Approach. Dell Publishing: New York, NY.
Churchman, C. West. (1970). Operations Research as a Profession. Management Science 17: b37-53.
Fitzgerald, L.A. (1999). Why there’s nothing wrong with systems thinking a little chaos won’t fix? A critique of modern systems theory and the practice of organizational change it informs. Systemic Practice and Action Research 12: 229-235.
Forrester, J. W. (1961). Industrial Dynamics. MIT Press: Cambridge, MA.
Gleick, James. (1987). Chao: Making a New Science. Penguin: London, UK.
Jackson, M.C. (1991). Systems Methodology for the Management Sciences. Plenum: New York, NY.
Kuhn, Thomas S. (1962). The Structure of Scientific Revolutions. The University of Chicago Press: Chicago, IL.
Midgley, Gerald. (2000). Systemic Intervention: Philosophy, Methodology and Practice. Kluwet Academic/Plenum Publishers: New York, NY.
Resnik, David B. (1998). The Ethics of Science: An Introduction. Routledge: London, UK.
Resnik, David B. (2009). Playing Politics with Science: balancing scientific independence and government oversight. Oxford University Press: New York, NY.