While the word tree can not realistically be used to describe a pig or a house, but we do have a problem when words start to take on specialised meaning. You see a lot of that with the words complex and complicated. In common day speech they are often used as synonyms, but with a growing understanding of complex adaptive systems, the distinction between the two words is becoming more and more important. Complicated carries an engineering flavor of knowability, while complex holds a (sic) complex set of associated ecological meanings – co-evolution, retrospective coherence etc. etc. The richness of the English language allows the emergence and loss of some distinctions over time.
We also get some words which are hijacked, and ontology is one. Derived from the Greek word for Being, it is that branch of metaphysics which deals with existence and the nature of being. Kant sees unaided reason as determining what must and therefore does exist. For Aristotle it is the apex of philosophy, for Heidegger it is all about our consciousness of our place in the world, our Dasein. The Cynefin framework is an ontological model, with epistemological consequences, although in its earlier manifestations the ordered domains were defined in epistemological terms (known and knowable).
The uniqueness of Cynefin as a model is that it actively encourages a recognition that there are different ontological states that coexist within an organisations decision space, and that a recognition of those differences leads to different and co-evolutionary epistemological strategies; I am using the two “co” words with some prevision here. The ability of humans to create order both consciously through process control and at a deeper ideation level with ritual means that we have learnt to live in multiple ontologies, while animals in general are mostly complex.
The downside of this is that we have started to create a sub-class of people who can only cope with order, and find complexity confusing at best and evil at worst. The belted high priests of the sick stigma cult are one example, but the other group are taxonomists seeking to avoid the label of taxidermy (which sounds the same and often means the same). Ontology for many now means a classification system, a set of categories from which one can assembly a a set of processes which allow you to pretend the the messy and confusing coherence of reality are somehow other and to be avoided.
I found a good and well meaning example of this recently – here is the text.
If you take a well defined and effective framework such as the ITIL, you will find some care and attention applied to identifying the objects the framework takes and ensuring that the rest of the framework provides a ‘grammar’ that consistently applies those definitions. So for example key concepts such as ’service’ ‘change’ ‘incident’ ‘problem’ are explicitly defined. Problems do creep in and especially with similar terms that may be used synonymously in common speech such as ‘incident’ and ‘problem’. But in the end it is possible to point to an event in the organisation and say with some certainty ‘that was an incident’ or another event and say ‘that is a change’.
Confusing frameworks, such as Cynefin, pile ambiguity on ambiguity and we should not be surprised that they are at once comforting to management and causes of confusion and disagreement. The “Cynefin problem” is hypostasis. It assumes a subject matter (system, problem domain, etc) that is ill defined and vague in the first place and applies a classification system for which there can be no agreed characteristics or measurements. There are no agreed definitions of a system, and just what does ‘problem domain’ signify. Worse, there are no agreed definitions for ‘complexity’ in maths or physics and certainly no unit of measure.
As a set of practices Cynefin may embody some common sense, but it cannot really be a model because the underlying ontology is vague. Application of a vague model to any real-world situation will generate confusion.
Now the definition of hypostasis (if I assume a medical meaning is not intended) is an underlying reality or substance, as opposed to attributes or that which lacks substance. So I am not sure what is meant there. The author is correct that there is no fully agreed definition of complexity in maths or physics, that is the nature of an emergent field. Its also why I always define the words (in terms of constraints) but on the basis of the argument above we would make no progress until we had things organised into little boxes with neat labels such as incident and problem. And the ontology isn’t vague, if you use the ontology word to reflect its Greek and Philosophical origins. If by ontology you mean a classification system then you have its wrong; this was one of my issues with Tom in the post of two days ago, he keeps seeing things in terms of classes or coherences. Classification is a technique associated with order.
Cynefin doesn’t pile on ambiguity, it forces a recognition that many systems and aspects of systems are inherently ambiguous, and to attempt to constrain those ambiguities into neat and tidy categories represents a potentially catastrophic mistake. The way you handle conflict is not to reduce ambiguity but to recognise it. That means if the situation is complex you allow any coherent idea the space and investment to run a safe-fail experiment. The system can only be understood by interacting with it, not by coming along with your butterfly net, a killing charge and a classification system only available to the IT elite.
The power of the Cynefin framework is that is passes the back of a napkin test, it can be drawn from memory without the need to reference a manual (which only gives power to the writer and owner of the manual). The reason it gives comfort to managers is that it reflects their day to day reality and the attitudes revealed in the above quote may explain why so many IT and Enterprise Architecture forums abound with how do we sell this wonderful vision of order to senior manager discussions. The reason you can’t sell it guys is that it bears no relation to reality. Life is ambiguous, messy and at times incoherent learn to life with it. Complexity ideas such as modularization and object orientation (an IT generated idea that really needs a underlying appreciate of CAS) are ways that we manage such situation – not classification.
If you want to read the full text you can find it here. Following it is an even more revealing comment from Stephen Bounds (who really should know better), he says “The whole field of complex adaptive systems is about predicting behavior in non-deterministic but non-random systems — which is exactly what an organisation is.” This is a common error in people who come to CAS from a systems dynamics background. They see everything in terms of a model, and the success of a model is defined by its predictive capability. We really need to move on from this restrictive thinking, and while we are at it, use words properly.
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