HALF CENTURY OF PETER CHECKLAND SOFT SYSTEMS METHODOLOGY

It is more than 50 years since Peter Checkland first published his initial papers outlining the use of systems thinking as an approach to management. (Checkland, 1972). In the following decade, Checkland and his colleagues (as he always pointed out) at Lancaster University questioned the use of hard systems thinking to real-world situations. Based on real world action research, they crafted a new methodology that shifted the systemicity from the real world to the process of enquiry itself.

Checkland locates the emergence and development of what he called the optimisation paradigm in management sciences/ operational research (MS/OR) in the late 50s and 60s. This was mainly an extension into management of what was the functionalist paradigm from the social sciences (Burrell and Morgan, 1979). The belief that organisations can be seen as objective worlds was certainly underpinning the early developments of classical MS/OR methods and techniques. Furthermore, these approaches relied on the assumption that the decision maker acts in full possession of rationality or ‘bounded rationality’, Simon (1947, 1960) and the ability to choose between different alternatives, generated in full knowledge of what the problem is and where s/he wants to be. Broadly, the Optimisation Paradigm and the development of ‘solving methods’ are generally associated with classic Operational Research techniques and the so called ‘hard’ approaches.

The Emergence of SSM and the Learning Paradigm in MS/OR

During the 1970s, Checkland and Lancaster colleagues challenged the effectiveness of the MS/OR hard approaches. The ‘failure’ of Management Science and Operational Research was also strongly debated by Churchman (1971) and Ackoff (1979). The core of the argument was that in situations where the problem is not well defined, Systems Engineering and the rest of the Hard Approaches did not offer a suitable methodology. The Hard Approach worked successfully when the problem and objectives to achieve were well defined. However, in scenarios where the ‘problem’ itself is not clear, these ‘hard’ approaches fail to give useful insights. Checkland (1981, 1999) argues that this is mainly because these approaches see the situation as an engineering problem; looking at ‘how to do things’ when ‘what to do’ is already specified.

In contrast, Soft Systems Thinking proposes to abandon this goalseeking model. It argues that not only the ‘hows’ of the ‘problematic situation’ (not of the ‘problem’) should be studied but, more importantly, the ‘whats’ of the situation must be debated. Furthermore, this approach proposes the use of ‘systems’ (or more appropriately ‘holons’) as mental constructs for perceiving the problematic situation, with the view of improving (not ‘solving’ it) and learning from it.

Overall, Systems Thinking in the UK, has been associated with Soft Systems Methodologies. According to this paradigm, organisations and humans are believed to be fundamentally different to the physical world; and in order to gain knowledge of their actions, we need to attempt to interpret their meaning and perceptions. This is the main claim of the interpretative paradigm- ‘soft’ issues relating to the different ways that people perceive and feel the problematical situation, are really the areas that need to be investigated and explored.

The learning (Checkland, 1981), interpretivist (Jackson, 1982; Mingers, 1980, 1984) paradigm is the one that underpins systemic methodologies that, abandoning the search for a ‘solution’ to the problems, instead seek to learn from the process of any intervention. Ackoff (1993) calls this the ‘design approach’ comprising methods that attempt to dissolve systems of problems or messes. Ackoff calls this the ‘design approach’ comprising methods that attempt to dissolve systems of problems or messes. He argues that these methodologies differ substantially to those of the ‘optimisation’ or ‘research approach’ in that they aim to tackle the context or environment where the mess takes place and, focus on alleviating or dissolving the systems of problems rather than solving it. Jackson (2003) groups the methodologies of this paradigm under Systems approaches that ‘Explore Purposes’; here he includes Soft Systems methodology (SSM); ‘Strategic Assumption Surfacing and Testing’ developed by Mason and Mitroff (1981) and ‘Interactive Planning’ proposed by Ackoff (1981). From these methodologies, SSM is widely the most used and more widely accepted systemic approach in the ‘soft’ end of the OR/MS methodological spectrum.

Soft Systems Methodology: an epistemology for a learning process and making sense through the flux of life.

Aware of the importance of the British systems thinker Geoffrey Vickers’ appreciative systems theory (Vickers, 1965), for Checkland, the real world is an ever-changing flux of events and ideas. ‘Managing’ this means reacting to this fluidity. We perceive and evaluate, take action(s) which itself becomes part of the flux- leading to next perceptions and evaluations, doing more actions, and so on. It follows that SSM assumes that different actors of the situation will evaluate and perceive this flux differently. Hence, this creates scenarios in which the manager must be able to adjust and to cope. Here, SSM offers systems ideas to managers as a helpful tool to tackle problematic situations arising from the issues.

Essentially, at the core of its nature, SSM articulates an appreciative, learning process which takes the form of an enquiry process in a situation that people are concerned. This process leads to action in a never-ending learning cycle: once the action is taken, a new situation with new characteristics arise and the learning process starts again.

Moreover, for Checkland, the very essence of Vickers’s most important legacy is the of ‘appreciation’ which underlies all his work. Based on this notion, SSM develops a knowing device which helps to make sense of the process by which ‘. . .we create the webs of significance that define and constitute for us the perceived world we inhabit.’ (Checkland, 2005:287).

The basic structure of SSM rests on the idea that in order to tackle real-world situations, we need to make sure that the ‘real-world’ is separated from the ‘systems thinking world’. This distinction is crucial for SSM because it guarantees that we will not see systems ‘out there’, (that is in the real or physical world). SSM urges us to consider ‘systems’ as abstract concepts Eventually, their use can help us to bring some improvements to the situation concerned. SSM takes reality to be problematical level and ceases to worry about modelling it systemically.

Overall, SSM seeks to work with different perceptions of reality, facilitating a systemic process of learning in which different viewpoints are examined and discussed. This happens in a way that can lead to purposeful action, in pursuit of improvement. SSM provides a systemic methodology by which participants learn what changes are feasible and desirable, given the peculiarities of their problem situation. SSM’s best known general mode starts when a problem situation is perceived and somehow structured. From this perception, the stakeholders, will select relevant systems and express them in basic root definitions. A model building construction follows as means for predication of conceptual models. All activities of a purposeful action are carried out by individuals in the form of Human Activity Systems (HAS). These then will be compared with the perceived situation before taking action. Figure 1 shows the basic four phases (Perceive/Select; Predicate; Compare; and Take action) disaggregated in the well-known SSM 7-stages to be followed, when applying SSM to a real-world situation.

In 1990 in SSM in action, Checkland adjusted the seven steps of SSM into two modes, ‘Mode 1’ and ‘Mode 2’ of the methodology. But essentially, SSM still consists of these four main elements: ‘find out about the situation’, ‘design of purposeful activity models’, ‘ideas for change’, and ‘take action to improve’.

Figure 1: The SSM cycle: Four phases (Perceive/Select; Predicate; Compare; and Take Action) and SSM 7 steps/stages. from: Jerardino- Wiesenborn, et al (2020), based on Checkland (1981; 1999)

Peter Checkland’s Achievements- SSM Legacy and its Future

Peter Checkland’s Soft Systems Methodology is one of the most developed Systems Methodologies in terms of its theoretical premises and philosophical underpinnings. It is also one of the most widely used in the UK and in other parts of the world. Amongst others, see Mingers and Taylor (1992); Ledington & Donaldson (1997); Macadam & Packham (1989); and; Brocklesby (1995).

In 2000, when commemorating 30 years of the development SSM, John Mingers stated that: ‘[…] SSM has reoriented an entire discipline and touched the lives of literally thousands of people.’ Adding that SSM has paved the way to Soft OR: ‘[…] soft and interpretive thinking is now completely taken for granted within the systems discipline and, to a great extent, within OR/MS and many areas of information systems.’. Mingers (2000:747)

Living in a world which faces increasing complexity and constant uncertainty, highlights the need for tools that help us to interpret and to understand the complexity of human affairs. Now, with this 50th Anniversary, I think there is plenty of real-world material where SSM can still assist us. Perhaps, Mingers’ outline of SSM’s future role (written 25 years ago) is more relevant today:

‘ […] We still have, in the United Kingdom, major problems of poverty, inequality, health, and education […] But even worse are the international problems of underdevelopment, poverty and starvation, environmental destruction, and civil and international war, which seem no better now than they ever have been. This is where the challenge for systemic thinking lies and where SSM has a major role to play.’ Mingers (2000: 750).

Over the last five decades, SSMS’ legacy to the OR and Systems community has been remarkable. I strongly believe that for Soft OR advocates and practitioners, the next decades are full of opportunities and challenges to continue developing further SSM’s applications on real-world situations.

Happy 50th Anniversary SSM! Long live SSM and, many thanks to you Peter for developing it!