A Model That Expands the Boundaries of Vision: the Cynefin Framework (Complexity Theory)
Any company can be conditionally divided into two parts. One part is called «run» and it is
characterized by a small
amount of uncertainty, here we can use those processes and models which we already have, i.e.
ready-made. The second
part is called «change» and it is characterized by a high degree of uncertainty, here we make
assumptions and
hypotheses, develop new processes, models, products, etc.
How to act in the face of uncertainty? What can help us make the most effective decision that is
relevant to the
external environment? In a complex environment, when cause and effect relationships are not clear,
when we are dealing
with high levels of uncertainty, and when the external environment is constantly changing, it is
necessary to constantly
push the boundaries of the vision of the external environment. Dave Snowden's theory of complexity can
help expand our
understanding of the world around us. This is the sense-making framework on the basis of which
decisions are made.
Complexity theory was developed by Dave Snowden in 1999, when he worked for IBM Global Services to
manage intellectual
capital.
To begin with, to get an overview of this theory, Figure 1 presents its main points.
Figure 1 - Basic Points of the Theory
of Complexity
A key point of Complexity Theory is that Systems consist of interaction agents and the causal relationships by which they interact, and, depending on what we know about them, they fall into one of five domains: Disorder, Simple, Complicated, Complex, Chaotic (see Figure 2).
In simple systems, the number of agents and the causal relationships in which they
interact are obvious and repeatable,
therefore, decision-making is based on the following model: Sense -> Categorize -> Respond.
Complex systems are characterized by the fact that the number of agents and cause-effect relationships
are not obvious,
so we resort to expertise, and the following model is used to make decisions: Sense -> Analyze ->
Respond.
In complex systems, causal relationships are obvious only in retrospect, and the results are
unpredictable, so another
model of decision-making is applied here: Probe -> Sense -> Respond.
In chaotic systems, causal relationships cannot be determined, and the decision-making model looks
like this: Act ->
Sense -> Respond.
As for the domain of disorder, it is characterized by a lack of clarity as to what other domains are
applicable.
Therefore, the situation must be divided into separate elements and each part attributed to one of the
other four
domains.
***
The theory of complexity has found its application not only at IBM, but also in public administration in the United States and Europe. This model allows for a more correct assessment of the type of tasks or problems, as well as for determining the approaches by which they will be solved.