System thinking, problem solving as learning (Checkland, 1981)

25 October 2010

Regarded as a whole, the soft systems methodology is a learning system which uses systems ideas to formulate basic mental acts of four kinds: perceiving (stages 1 and 2), predicating (stages 3 and 4), comparing (stage 5), and deciding on action (stage 6). The output of the methodology is thus very different from the output of hard systems engineering: it is learning which leads to a decision to take certain actions, knowing that this will lead not to “the problem” being now “solved” but to a changed situation and new learning …

Overall, the stages of the methodology for work on ill-defined problems (which do not have to be followed in fixed sequence) constitute a learning system, a system which finds things out in a situation which at last one person regards as problematic. For ill-structured problems involving a number of people the very idea of “a problem” which can be “solved” has to be replaced by the idea of dialectical debate, by the idea of problem-solvlng as a continuous, never-ending process.

(Checkland, 1981, p. 17)

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System thinking on “solutions” (Checkland, 1981)

25 October 2010

Firstly, unstructured problems though”recognizable”, cannot be “defined”. Secondly, in problems in human activity systems history always changes the agenda. The contents of such systems are so multivarious, and the influences to which they are subject so numerous that the passage of time always modifies the perception of the problem (such problems really do sometimes “go away”!). Such perceptions of problems are always subjective, and they change with time. This is something which the research had to take into account. In fact a number of studies have been completed which are successful in the sense that they are judged so by both client and systems analyst but in which “the problem” was never defined throughout the whole course of the work.

In formal terms the research proceeds on the basis of the following definition of the word “problem”.

A problem relating to real-world manifestations of human activity systems is a condition characterised by a sense of mismatch, which eludes precise definition, between what is perceived to be actuality and what is perceived might become actuality.

In the early stages of the research it was accepted that whereas the definition of structured problems implies what will be accepted as “a solution”, unstructured problems – the concern of the research – must not be pressed into a structured form but must somehow be tackled in the absence of any firm definition of them. They are conditions to be alleviated rather than problems to be solved.

(Checkland, 1981, p. 155)


Systems thinking on “solutions” = to improve the problem situation (Hicks, 2004)

25 October 2010

The first stage in an SSM (Soft System Methodology) investigation involves the careful observation of the problem situation with all its intricate details, and the recording of all that is perceived. This involves collecting qualitative data – such as attitudes and opinions concerning the problem situation, including reactions to our intervention in matters (as external consultants) – as well as quantitative data, and recording this in the form of a “picture”. In this way we try to capture as much as possible of the richness of the real situation. Following this, the essence of these observations is encapsulated in brief descriptions of human activity systems that we hope may later provide relevant insights into the problem situation. Then models of these systems that are consistent with the different viewpoints expressed within the descriptions are drawn. Finally, several comparisons are made of the models with the observations of the real-world situation, which are used in a discussion with the problem owners to suggest systemically desirable and culturally feasible changes that it is hoped will lead to improvements in the problem situation. Note that, unlike many other problem-solving processes, SSM does not explicitly attempt to identify problems, but through its iterative “learning” process it is intended to make changes to the problem situation such that whatever the problem were they no longer exist.

(Hicks, 2004, p. 259f)