This article is part of the Systems Science Knowledge Area (KA). It presents issues in the comparison and analysis of systems approaches by the systems science community. Some of these ideas contribute to basic theory and methods that are used in systems thinking discussed in the Systems Thinking KA.
What is a Systems Approach?
In Bertalanffy's introduction to his 1968 general system theory (GST) book, he characterizes a systems approach as:
“A certain objective is given; to find ways and means for its realization requires the system specialist (or team of specialists) to consider alternative solutions and to choose those promising optimization at maximum efficiency and minimum cost in a tremendously complex network of interactions”. (Bertalanffy, 1968, page 4)
He goes on to list as possible elements of a systems approach: “classical” systems theory (differential equations), computerization and simulation, compartment theory, set theory, graph theory, net theory, cybernetics, information theory, theory of automata, game theory, decision theory, queuing theory, and models in ordinary language.
This description is similar to what Warren Weaver identified as the methods used successfully by “mixed teams” during World War II (WWII) on “problems of organized complexity”. However, some conditions that had contributed to success during wartime did not hold after the war, such as a clear focus on well-defined common goals that motivated participants to work across disciplinary boundaries.
By the early 1970’s, there was growing disillusionment with the promise that a systems approach would provide easy solutions for all complex problems. There was particular criticism from some, including pioneers of Operations Research and Management Science (ORMS) like Ackoff and Churchman, that reliance on rote mathematical methods to identify optimal solutions among fixed alternatives had become just as inflexible and unimaginative an approach to complex problems as whatever it had replaced. Interest grew in examining and comparing methods and methodologies to better understand what could help ensure the best thinking and learning in terms of systems in systems approaches to practice.
Issues in Systems Approaches
A systems approach is strongly associated with systems thinking and how it helps to guides systems practice. In What is Systems Thinking? the key ideas of considering a system holistically, setting a boundary for a problem/ solution of interest, and considering the resulting system-of-interest from outside its boundary are identified (Senge, 2006), (Churchman 1979), Meadows (2010).
A systems approach can view a system as a “holon” – an entity that is itself a “whole system” that interacts with a mosaic of other holons in its wider environment (Hybertson, 2009), while also being made up of interacting parts. We can use this model recursively – each part of the system may be a system in its own right, and can itself be viewed both as an entity as seen from outside, and as a set of interacting parts. This model also applies in upwards recursion, so the original “system-of-interest” is an interacting part of one or more wider systems.
This means that an important skill in a systems approach is to identify the “natural holons” in the problem situation and solution systems and to make the partitioning of responsibilities match the “natural holons”, so as to minimize the coupling between parallel activities when applying a solution. This is the “cohesive/loose coupling” heuristic that has been around for a long time in many design disciplines.
Another consequence of the holistic nature of a systems approach is that it considers not only a problem situation and a solution system but also the system created and deployed to apply one to the other. A systems approach must consider both the boundary of the system of concern as well as the boundary of the system inquiry (or model). Real systems are always open, i.e., they interact with their environment or supersystem(s). On the other hand, real models are always “closed” due to resource constraints — a fixed boundary of consideration must be set. So there is an ongoing negotiation to relate the two in systems practice and the judgment to do so is greatly helped by an appreciation of the difference between them.
Thus, a systems approach can be characterized by how it considers problems, solutions and the problem resolution process itself:
- Consider problems holistically, setting problem boundaries though understanding of natural system relationships and trying to avoid unwanted consequences.
- Create solutions based on sound system principles, in particular creating system structures which reduce organized complexity and unwanted emergent properties.
- Use understanding, judgment and models in both problem understanding and solution creation, while understanding the limitations of such views and models.
One topic that has received significant attention in the systems science community is the analysis and comparison of methodologies which implement a systems approach. A methodology is a body of tools, procedures, and methods applied to a problem situation, ideally derived from a theoretical framework. These describe structured approaches to problem understanding and/or resolution making use of some of the concepts of systems thinking. These methodologies are generally associated with a particular system paradigm or way of thinking, which has a strong influence on the three aspects of a systems approach described above.
The most widely used groups of methodologies are as follows, see also History of Systems Science:
- hard system methodologies (Checkland 1978) set out to select an efficient means to achieve a predefined and agreed end.
- soft system methodologies (Checkland 1999) are interactive and participatory approaches to assist groups of diverse participants to alleviate a complex, problematic situation of common interest.
- critical systems thinking methodologies (Jackson 1985) attempts to provide a framework in which appropriate hard and soft methods can be applied as appropriate to the situation under investigation.
Systems dynamics (SD) uses some of the ideas of cybernetics to consider the behavior of systems as a whole in their environment. SD was developed by Jay Forrester in the 1960’s He was interested in modeling the dynamic behavior of systems such as populations in cities, or industrial supply chains.
System dynamics, (Forrester 1961), is an approach to understanding the behavior of complex systems over time. It deals with internal feedback loops and time delays that affect the behavior of the entire system. The main elements of SD are:
- The understanding of the dynamic interactions in a problem or solution as a system of feedback loops, modeled using a Causal Loop Diagram.
- Quantitative modeling of system performance as an accumulation of stocks (any entity or property which varies over time) and flows (representations of the rate of change of a stock).
- The creation of dynamic simulations, exploring how the value of key parameters change over time. A wide range of software tools are available to support this.
These elements help describe how even seemingly simple systems display baffling non-linearity.
Hard Systems Methodologies
Checkland (Checkland 1975) classifies hard system methodologies, which set out to select an efficient means to achieve a predefined end, under the following headings:
- system analysis - the systematic appraisal of the costs and other implications of meeting a defined requirement in various ways.
- systems engineering (SE) - the set of activities that together lead to the creation of a complex man-made entity and/or the procedures and information flows associated with its operation.
Operational Research is also considered a hard system approach, closely related to the systems analysis approach developed by the Rand Corporation, in which solutions are known but the best combinations of these solutions must be found. There is some debate as to whether system dynamics is a hard approach, which is used to assess the objective behavior of real situations. Many application of SD have focused on the system, however it can and has also be used as part of a soft approach including the modeling of subjective perceptions (Lane 2000).
SE allows for the creation of new solution systems, based upon available technologies. This hard view of SE as a solution focused approach applied to large, complex and technology focused solutions, is exemplified by (Jenkins 1969; Hall 1962) and early defense and aerospace standards.
It should be noted that historically the SE discipline was primarily aimed at developing, modifying or supporting hard systems. More recent developments in SE have incorporated problem focused thinking and agile solution approaches. It is this view of SE that is described in this Guide to the Systems Engineering Body of Knowledge (SEBoK).
All of these hard approaches can use systems thinking to ensure complete and viable solutions are created and/or as part of the solution optimization process. These approaches are appropriate to unitary problems, but not when the problem situation or solution technologies are unclear.
Soft Systems and Problem Structured Methods
Problem Structuring Methods (PSM) are interactive and participatory approaches to assist groups of diverse participants to alleviate a complex, problematic situation of common interest. Typically the hardest element of the situation is framing the issues which constitute the problem (Minger and Resenhead 2004).
PSM use systems and systems thinking as an abstract framework for investigation, rather than a structure for creating solutions. Systems descriptions are used to understand the current situation and describe an idealized future. Interventions directly in the current organization to move towards the idea recognize that the assumptions and mental models of the participants are an important obstruction to change and that these differing views cannot be dismissed, but instead must form part of the intervention approach.
Peter Checkland’s action research program, see Systems Science, in the 1980‘s forms the basis of work by Checkland, Wilson and others in the development of soft systems methodology (SSM) (Checkland 1999; Wilson 2001). SSM formalizes the idea of a soft approach using systemic thinking to expose the issues in a problem situation and guide interventions to reduce them. SSM provides a framework of ideas and models to help guide participants through this systemic thinking.
Other PSM approaches include interactive planning approach (Ackoff 1981), social systems design (Churchman 1968), and strategic assumptions surfacing and testing (Mason and Mitroff 1981).
SSM and other soft approaches use systems thinking to ensure problem situations are fully explored and resolved. These approaches are appropriate to pluralist problems. Critics of SSM suggest that it does not consider the process of intervention, and in particular how differences in power between individuals and social groups impact the effectiveness of interventions.
Critical Systems Thinking and Multi-Methodology
The development of a range of hard and soft methods naturally leads to the question of which method to apply in what set of circumstances (Jackson 1989). critical systems thinking (CST) or Critical Management Science Jackson (Jackson 1985) attempts to deal with this question.
The word critical is used in two ways. Firstly, critical thinking considers the limits of knowledge and investigates the limits and assumptions of hard and soft systems, as discussed in the above sections. From this comes frameworks and meta-methodology that establish when to apply different methods such as Total Systems Intervention (TSI) (Flood and Jackson 1991). Critical or “pluralist” or “pragmatic” , multi-methodology approaches take this aspect of critical thinking one stage further to recognize the value of combining techniques from several hard, soft , or custom methods as needed (Mingers and Gill 1997). Many in the systems science community believe that the multi-methodology approach has been accepted as the de facto systems approach and that the challenges now are in refining tools and methods to support it.
Churchman (Churchman, 1979) and others have also considered broader ethics political and social questions related to management science, with regards to the relative power and responsibility of the participants in system interventions. The second aspect of critical thinking considers the ethical, political, and coercive dimension in Jackson's System of Systems Methodologies (SOSM) framework (Jackson 2003) and the role of system thinking in society.
Selecting Systems Methodologies
Jackson proposes a frame for considering which approach should be applied, please see Jackson's Framework. In Jackson's framework the following definitions apply to the participants involved in solving the problem:
- unitary - A problem situation in which participants "have similar values, beliefs and interests. They share common purposes and are all involved, in one way or another, in decision-making about how to realize their agreed objectives." (Jackson 2003, p. 19)
- pluralist - A problem situation involving participants in which "although their basic interests are compatible, they do not share the same values and beliefs. Space needs to be made available within which debate, disagreement, even conflict, can take place. If this is done, and all feel they have been involved in decision-making, then accommodations and compromises can be found. Participants will come to agree, at least temporarily, on productive ways forward and will act accordingly." (Jackson 2003, p. 19)
- coercive - A problem situation in which the participants "have few interests in common and, if free to express them, would hold conflicting values and beliefs. Compromise is not possible and so no agreed objectives direct action. Decisions are taken on the basis of who has most power and various forms of coercion employed to ensure adherence to commands." (Jackson 2003, p. 19)
Jackson's framework suggests that for simple and complex systems with unitary participants, hard and dynamic systems thinking applies, respectively. For simple and complex systems with pluralist participants, soft systems thinking applies. For simple and complex systems with coercive participants, emancipatory and postmodernist system thinking applies, respectively. These thinking approaches consider all attempts to look for system solutions to be temporary and ineffective in situations where the power of individuals and groups of people dominate any system structures we create. They advocate an approach which encourages diversity, free-thinking and creativity of individuals and in the organization's structures. Thus, modern system thinking has the breadth needed to deal with a broad range of complex problems and solutions.
These ideas sit at the extreme of system thinking as a tool for challenging assumptions in and stimulating innovative solutions in problem solving. Jackson (Jackson 2003) identifies the work of some authors who have included these ideas into their systems approach.
Bertalanffy, L. 1968. General Systems Theory. New York, Ny, USA: George Braziller, Inc.
Ackoff, R.L. 1981. Creating the Corporate Future. New York, NY, USA: Wiley and Sons.
Checkland, P. 1975. "The Origins and Nature of “Hard” Systems Thinking." Journal of Applied Systems Analysis, 5(2): 99-110.
Checkland, P. 1999. Systems Thinking, Systems Practice, New York, NY, USA: John Wiley & Sons.
Churchman, C.W. 1968. The Systems Approach. New York, NY, USA: Dell Publishing.
Churchman, C. West. 1979. "The Systems Approach and Its Enemies". New York: Basic Books.
Flood, R. and M. Jackson. 1991. Creative Problem Solving: Total Systems Intervention. London, UK: Wiley.
Forrester, J. 1961. Industrial Dynamics. Cambridge, MA, USA: MIT Press.
Hall, A.D. 1962. A Methodology for Systems Engineering. New York, NY, USA: Van Nostrand Reinhold.
Hybertson, D, 2009. Model-oriented Systems Engineering Science: A Unifying Framework for Traditional and Complex Systems (CRC Complex and Enterprise Systems Engineering)
Jackson, M. 1985. "Social Systems Theory and Practice: the Need for a Critical Approach." International Journal of General Systems. 10: 135-151.
Jackson, M. 1989. "Which Systems Methodology When? Initial Results from a Research Program." In: R Flood, M Jackson and P Keys (eds). Systems Prospects: the Next Ten Years of Systems Research. New York, NY, USA: Plenum.
Jackson, M. 2003. Systems Thinking: Creating Holisms for Managers. Chichester, UK: Wiley.
Jenkins, G.M. 1969. The Systems Approach. In Beishon, J. and G. Peters (eds.), Systems Behavior, 2nd ed. New York, NY, USA: Harper and Row.
Kuhn, T.S. The Structure of Scientific Revolutions. Chicago: University of Chicago Press, 1962
Lane, D. 2000 “Should System Dynamics be Described as a `Hard' or `Deterministic' Systems Approach?” Systems Research and Behavioral Science. 17, 3–22 (2000) John Wiley & Sons, Ltd.
Mason, R.O. and I.I. Mitroff. 1981. Challenging Strategic Planning Assumptions: Theory, Case and Techniques. New York, NY, USA: Wiley and Sons.
Mingers, J. and A. Gill. 1997. Multimethodology: Theory and Practice of Combining Management Science Methodologies. Chichester, UK: Wiley.
Mingers, J. and J. Rosenhead. 2004. "Problem Structuring Methods in Action." European Journal of Operations Research. 152(3) (Feb. 2004): 530-554.
Senge, P. M. 1990, 2006. The Fifth Discipline: The Art and Practice of the Learning Organization. New York, Doubleday/Currency.
Wilson, B. 2001. Soft Systems Methodology—Conceptual Model Building and Its Contribution. New York, NY, USA: J.H.Wiley.
Checkland, P. 1999. Systems Thinking, Systems Practice, New York, NY, USA: John Wiley & Sons.
Forrester, J. 1961. Industrial Dynamics. Cambridge, MA, USA: MIT Press.
Jackson, M. 1985. Social Systems Theory and Practice: the Need for a Critical Approach. International Journal of General Systems. 10: 135-151.
Jackson, M.C. and Keys, P. 1984. "Towards a System of Systems Methodologies." The Journal of the Operational Research Society. 35(6) (Jun. 1984): 473-486.
Sterman, John D. (2001). "System dynamics modeling: Tools for learning in a complex world". California Management Review. 43(4): 8–25.
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