3.1 Adding to the differences between difficulties and messes
Distinguishing between these two sorts of complexity further clarifies the difference between difficulties and messes.
- Difficulties, being well-defined and more limited situations, mainly involve hard complexity. Given a particular view of the matter, what is the best that can be done?
- Messes on the other hand are ill-defined; they include large measures of both hard and soft complexity. Of course this may not be obvious at first and some or all of those involved may fail to recognise the soft complexity: they may initially resent alternative viewpoints, perhaps seeing them as misguided or even wilful attempts to confuse the ‘real’ issue.
But ambiguities and different interpretations that can be overlooked or ignored when working on one’s own or with close colleagues are harder to avoid when more people are involved. Other people’s input will often help one see that the problem is messier than first thought (although not every difficulty is a mess in disguise). Indeed, only the most trivial difficulties involve no soft complexity at all. But the more soft complexity there is in a situation, the messier it is likely to be. Working out what to do with a mess is no longer a matter of thinking the situation through, but of rethinking or reframing it as well. Too often general principles and techniques (e.g. for project planning, work study, etc.) assume that the elements of soft complexity either don’t exist or can easily be resolved. That is, they assume you already know what sort of situation you are dealing with. If techniques help in recognising some tractable elements in a messy problem or a promising approach to aspects of it, then they are of considerable value. But equally a personal commitment to particular techniques can tie a person’s thinking to a narrow conception of the issues. In any event, by the time one is sure what principles or techniques to apply, the mess is already resolving itself into a set of related difficulties.
Activity 4 Hard and soft complexity
In the light of the discussion of hard and soft complexity, review your notes on the messy situations you have faced and answer these questions.
- What are the elements of both hard and soft complexity in the situations?
- In what ways does the discussion of soft complexity help in pinning down what for you distinguished the messes from the difficulties?
- If you have been thinking about your difficulties and messes only in terms of hard complexity, how do you account for this in terms of your particular work or your particular way of thinking?
Comment
In summary, complexity, as understood in this course, has many different facets based on both rational and emotional factors. The rational factors tend to involve technical or computational complexity, otherwise known as ‘hard’ complexity. The emotional factors or ‘soft’ complexity includes the way people view and interact with the situation. These ideas also relate to those of difficulties and messes whereby difficulties involve more hard complexity and messes more soft complexity but most situations will probably involve both. Perceived complexity arises because of our cognitive limitations as well as characteristics of the situation. Our embodied ways of knowing – individuals and the explanations they accept have different traditions and histories – lead to only seeing aspects of a situation never the whole.
There is no viewpoint or perspective that can appreciate the full variety of a situation (you will return to this issue in Week 5). It is from the recognition of these limitations that a range of systems approaches has been developed (which we deal with in Week 7). The notion of perceived complexity addresses one of the ways I experience the word complex. But are there other ways complexity is currently used? The short answer to this is: yes, lots.
The principal term under which complexity is addressed is complexity science which is broadly the scientific study of complex systems. This course does not cover these understandings of complexity other than to note the distinctions between complex situations (as has been done so far) and complex systems.