The Origins of SSM

SSM provides a philosophy and a set of techniques (a method) for investigating a “real-world” problem situation that is viewed as a governed by business logic – rather than the engineering logic normally attached to IT system requirements. Its intention is to improve real world situations by orchestrating changes of appreciation through a cyclic learning process” based on Vickers’ concept of Appreciative Systems (Vickers, 1968; Checkland, 2000b). Geoffrey Vickers observed the diversity of norms, relationships, and experiential perspectives among those involved in, or affected by, a system of human-activity such as that found in business work-organizations. He argued that organizational change analysts needed methods for analysis that explored how to reconcile these perspectives, developing the concept of an “appreciative system,” the set of iterative interactions by which we explore, interpret, and mutually construct our shared organizational reality (Vickers, 1968), shown in Figure 1.

Vickers conceptualized organizational work as a stream, or flux, or events and ideas that were interpreted by participants in the organization by means of local “standards,” reflecting shared interpretation schema and sociocultural values (Checkland and Casar, 1986). Interpretations of new events and ideas are subject to the experiential learning that resulted from prior encounters with similar phenomena; these will vary across stakeholders, depending on how they interpret the purpose of the system of work-activity. To achieve substantive change, we need to understand and reconcile these multiple purposes, integrating requirements for change across the multiple system perspectives espoused by various stakeholders. These are separated out into distinct perspectives, which model subsets of activity that are related to a specific purpose or group of participants in the problem situation (Checkland, 1979, 2000b), as shown in Figure 2.

SSM As an Iterative Inquiring/Learning Cycle of Change

SSM is therefore based upon a single concept: that we separate and analyze systems of purposeful human activity (what people do), rather than data-processing or IT systems (how IT components should function to support what people do). SSM is helpful for analysis approaches that wish to understand the connections, conflicts, and discrepancies between elements of a situation rather than attempting to subsume all elements into a single perspective. It is systemic, rather than systems-focused, exploring relationships between participants and between perspectives (Checkland, 2000a). SSM provides a way of engaging in joint learning with stakeholders and participants about the problem-situation. It allows all parties involved to understand the implications of achieving various purposes and involves participants in defining relevant work-activities and exploring what needs to change, as shown in Figure 2.

Initially, the process of inquiry focuses on the real-world problem-situation, exploring how this works using representations such as Rich Pictures, which impose as little structure on what exists as possible. In this way, we get to appreciate how this world “works” rather than viewing it through the filter of the models we construct. Whatever insights a model may give us, it does not represent the real world. Instead, it represents systems thinking about the real world. Checkland (1979) distinguishes between “above-the-line thinking” (about entities, relationships, and activities performed in the real-world situation) and “below-the-line thinking” (which models the potential/ideal-world sub-systems of human-activity required to achieve each separate purpose of the real-world system). Below-the-line thinking produces the “Relevant models of purposeful activity” shown in Figure 2, above. These are separated out, as shown in Figure 3, so we can model and analyze the activities required to achieve each purpose separately.

Separating Out Purposeful System Perspectives

SSM relies on the explicit declaration of worldviews which make each purposeful system model meaningful to participants. In defining purposeful models, the Soft Systems Method (SSM) avoids what Russell Ackoff (1974) called “messes”: the typical situation where none of the requirements for change are understood or implemented fully, because the relationship between requirements is systemic (each requirement has “knock-on” implications for other requirements). Unraveling systemic messes needs a divide-and-conquer approach that separates out the requirements for each separate purpose that the system-of-work exists to achieve, as shown in Figure 4. We delay this stage until we have a reasonable understanding of the problem situation: what various actors do, why they do it, and how they interact to achieve their purposes.

Generating one perspective on the work-system at a time allows us to analyze what work-activities need to be done to achieve a single purpose — and how actors’ work-outcomes are evaluated — in isolation from all the other purposes, before merging perspectives back into a (better understood) integrated system-of-human-activity so we may determine priorities for change. This divide-and-conquer strategy employs the CATWOE framework to define each perspective (or purposeful system):

Client	Who is the victim or beneficiary of these changes?
Actors	Who performs the work for this transformation?
Transformation	How is an entity, the input to the transforming process, changed into a different state or form to become the output of the process?
Weltanschauung	What is the perspective that makes the transformation significant to participants (the purpose)?
Owner	Who has the power to say whether the system will be implemented or not?
Environment	What needs to be known about the environmental conditions that the system operates under?

Complex transformations should be separated into distinct purposes, with a single set of actors. It is usually an indication that you have conflated two purposes if you have two different sets of actors involved – you will tie yourself in knots attempting to model both points of view at the same time. You can happily repeat the exercise using another perspective, to see if you can balance the needs of two purposes with the same system, but conflating perspectives often leads to change requirements being overlooked. Sometimes it may not be possible to balance two perspectives – for example, how do you integrate the needs of drivers to park easily with the needs of pedestrians to be kept safe in congested areas? If you cannot integrate competing perspectives, you must take a decision about whose perspective will have priority – this is where your client’s objectives come into play. In every change, there are winners and losers; your job is to make it explicit who loses and who wins, rather than to make this decision for the client (!).

Defining and Prioritizing Requirements For Change

Once each transformation is defined, it can be explored in terms of the potential sequences of activity needed to achieve that purpose. Participants and other stakeholders are involved in developing conceptual models that reflect “ideal world” sub-systems of activity. Not all of these activities may be implemented – or they may not be implemented in the way originally envisaged. Subsequent changes to the real-world system of work are evaluated by managers and the client of the change initiative, to determine the order and priorities for change. But it is important to understand what work needs to be done, so you can consider constraints on achieving the desired outcomes should your client not choose to implement some process-changes. Actions to improve the problem-situation are based on finding accommodations that balance the interests of competing perspectives. This involves defining versions of the situation which stakeholders with competing interests can live with (Checkland, 2000b).

In much of his later work, Checkland addresses the difficulty of converting a model that represents a system of human activity into a set of requirements for an IT-based information system by distinguishing between the supporting system (IT) and the supported system (human activity).  The supported system represents the problem domain, the amalgam of purposeful systems of human activity that underpins the problem situation. The supporting system represents the solution domain, that combination of people, processes, and technology that provides a solution to problems identified by participants in the problem situation.

 

Fig 4. The supporting system of IT vs. the supported system of human activity

Reconciliation between the two system views depends on the translation of requirements for change to the human-activity system to IT system requirements. If these changes are undertaken incrementally, with a focus on a single purposeful system perspective at a time, this is generally fairly simple to accomplish – it aligns well with the business-process (re)design approach used by most organizations in driving IT change.

The Contribution of SSM

Soft Systems Methodology (SSM) was devised by Peter Checkland and elaborated in collaboration with others at Lancaster University in the UK: (Winter, Brown, & Checkland, 1995; Checkland & Scholes, 1999; Checkland & Holwell, 2007; Checkland & Poulter, 2006). Its contribution is to separate the analysis of the “soft system” of human-activity from the “hard system” of IT and engineering logic that serves the needs of the human-activity system.

Checkland distinguishes between the hard, engineering school of thought and soft systems thinking. The development of systems concepts and system thinking methods to solve ill-structured, “soft” problems is Checkland’s (1979) contribution to the field of systems theory. Soft Systems Methodology (SSM) provides a method for participatory design centered on human-centered information systems. It also provides an excellent approach to surfacing multiple perspectives in decision-making, complex problem-analysis, and socially-situated research. The analysis tools suggested by the method — which is really a family of methods, rather than a single method in the sense of modeling techniques — permit change-analysts, consultants and researchers to exercise reflexivity and to explore alternatives. In his valedictory lecture at Lancaster University, Peter Checkland listed four “big thoughts” that underlie soft systems thinking (Checkland, 2000a):

Systems thinking attempts to understand problems systemically. Problems are ultimately subjective: we select things to include and things to exclude from our problem analysis (the “system boundary”). But real-world problems are wicked problems, consisting of interrelated sub-problems that cannot be disentangled — and therefore cannot be defined objectively (Rittel, 1972; Rittel & Webber, 1973). The best we can do is to define problems that are related to the various purposes that participants pursue, in performing their work. By solving one problem, we often make another problem worse, or complicate matters in some way. Systemic thinking attempts to understand the interrelatedness of problems and goals by separating them out.

In understanding different sets of activities and the problems pertaining to those activities as conceptually-separated models, we understand also the complexity of the whole “system” of work and the interrelatedness of things – at least, to some extent. It is important to understand that, given the evolving nature of organizational work, a great deal of the value of this approach lies in the collective learning achieved by involving actors in the situation in analyzing changes, and that this approach in inquiry is, in principle, never ending. It is best conducted with and by problem-situation participants (Checkland, 2000b).

SSM is an approach to the investigation of organizational problems that may – or may not – require computer-based system support for their solution. In this sense, SSM could be described as an approach to generating early requirements for change analysis, rather than as a systems design approach. The original, seven-step method of SSM (Checkland, 1979) has been replaced by more nuanced approaches to soft systems analysis (note the loss of the word “method”). Checkland now considers the approach more of a mindset, or way of thinking than a strict set of steps that should be followed (Checkland & Holwell, 1997). However, without the roadmap provided by the seven stages of analysis, it can be difficult to understand where to start. For this reason, the discussion on this site employs the terminology and approach of the seven-stage method originally proposed, while attempting to iron out some of the complexities and confusions in the original (Checkland, 1979).

This website attempts to explain some of the elements of SSM for educational purposes. It is not intended as a comprehensive source of information about SSM, but as a reflection of my own tussles with the approach. As a result, it may well subvert some of Checkland’s original intentions, in an attempt to make the subject accessible to students and other inquiring minds … .

Note [1]: Weltanschauung is a German word, used in philosophical works to represent a particular philosophy or view of life, especially when analyzing the worldview of an individual or group. Checkland (1979) adopted the term in its philosophical sense when he was making the argument that the purposes for which a system of human-activity (or work) exist are situated within a specific sociocultural framework of rules and expectations that govern who-does-what and how. The idea is similar to Anselm Strauss’ concept of social worlds, where participants draw on experience-based interpretations, culturally-situated, relational identities, and shared interpretations of organizational structures that allow them to respond automatically to new phenomena and events (Strauss, 1978). The term “worldview” may be substituted, with the understanding that this reflects the broader use of the term to indicate socioculturally-situated interpretations, not simply an individual’s point of view.

References

Ackoff, R. L. (1974). Redesigning The Future: Wiley.

Checkland, P. (1979)  Systems Thinking, Systems Practice. John Wiley and Sons Ltd. Chichester UK. Latest edition includes a 30-year retrospective. ISBN: 0-471-98606-2.

Checkland P., Casar A. (1986) Vickers’ concept of an appreciative system: A systemic account. Journal of Applied Systems Analysis 13: 3-17

Checkland, P., Holwell, S.E. (1998) Information, Systems and Information Systems. John Wiley and Sons Ltd. Chichester UK. ISBN: 0-471-95820-4.

Checkland, P. & Scholes, J. (1999) Soft Systems Methodology in Action. John Wiley and Sons Ltd. Chichester UK. ISBN: 0-471-98605-4.

Checkland, P. (2000a) New maps of knowledge. Some animadversions (friendly) on: science (reductionist), social science (hermeneutic), research (unmanageable) and universities (unmanaged). Systems Research and Behavioural Science, 17(S1), pages S59-S75. http://www3.interscience.wiley.com/journal/75502924/abstract

Checkland, P. (2000b). Soft systems methodology: a thirty year retrospective. Systems Research and Behavioral Science, 17: S11-S58.

Checkland, P., Poulter, J. (2006) Learning for Action: A Short Definitive Account of Soft Systems Methodology and its Use, for Practitioners, Teachers and Students. John Wiley and Sons Ltd. Chichester UK. ISBN: 0-470-02554-9.

Churchman, C.W. (1971) The Design of Inquiring Systems, Basic Concepts of Systems and Organizations, Basic Books, New York.

Rittel, H. W. J. (1972). Second Generation Design Methods. Design Methods Group 5th Anniversary Report: 5-10. DMG Occasional Paper 1. Reprinted in N. Cross (Ed.) 1984. Developments in Design Methodology, J. Wiley & Sons, Chichester: 317-327.: Reprinted in N. Cross (ed.), Developments in Design Methodology, J. Wiley & Sons, Chichester, 1984, pp. 317-327.

Rittel, H. W. J. and M. M. Webber (1973). “Dilemmas in a General Theory of Planning.” Policy Sciences 4, pp. 155-169.

Vickers G. (1968) Value Systems and Social Process. Tavistock, London UK.

Winter, M., Brown, D. H., & Checkland, P. B. (1995). A role for soft systems methodology in information systems development. European Journal of Information Systems, 4(3), 130-142.

von Bertanlaffy, L. (1968) General System theory: Foundations, Development, Applications, New York: George Braziller, revised edition 1976.