Why is the definition of complexity important to anybody? From
a generalist viewpoint, complexity is something that we all deal with on a day
to day basis, whether in the form of social, economic, weather, biological or
physical systems. From a business engineering specialist perspective,
complexity impacts on the organisational system's ability to create wealth from
scare resources for its stakeholders.
The word “complexity” is mostly used in conjunction with reference to a “system” and to understand complexity, one needs to understand a system. In essence, a system can be defined as a scoped enclosure with a purpose, containing within this enclosure “things” or objects. When studying these objects in the system, an understanding needs to be gathered around the static construction of the objects (the space dimension), and how these objects move through the time (dynamics of the object).
In the world of complexity sciences, the definition of “complexity”
is complex itself – little agreement to what it really means. However, in the
classification of complex systems one will find agreement; business systems are
classified as complex adaptive systems. I like to expand this to (C)omplex (H)uman
(A)daptive (O)rganisational (S)ystems. Michel Baranger from MIT calls this
science, the “science of everything”, but even in this science, complexity is
linked to “understanding”. This means that in order to understand a system
under study, allows the observer to use, modify, control and appreciate the
system. Yaneer Bar-Yam from the New England Complex Systems Institute expands this by explaining
that system understanding entails the classification, description and ultimate
predication of behaviour of the dynamics of the system as it changes in space and
time.
For this to be possible, requires a means to measure and
describe complexity in a quantitative manner. To do this, complexity scientists
have borrowed the concept of entropy from the field of thermodynamics, where
entropy indicates the amount of order and disorder of heat transfer in physical
systems. Applying Shannon’s entropy from an Information Sciences perspective to
the thermodynamics application defines entropy as representing the amount of “missing
information” about the system from an observer’s perspective (Michel Baranger).
This also implies our inherently difficulty to understand the system.
A sensible definition for complexity can then be defined as “ Complexity is the level of uncertainty that exists in the spatial dynamics of a system".
The minimum information required to understand a system can
be found in common building blocks that most complex systems share; objects,
relationships and scale (or hierarchy). In a system, many objects will interact
with many other objects in the system, while some will be influenced by the
system’s external environment. These interactions create dynamic, non-linear
relationships between the objects which may vary in strength from weak to
strong. In the case of business systems, activities will be designed to fulfil
specific system objectives, and objects will cluster around them to ensure
achievement of these objectives. Ultimately, these activities form the
structure of the system which spans multiple scales.
Business engineers design and implement complicated business systems – meaning layers of activities, control procedures and moving objects of people, machines and money in a coordinated fashion. This design normally assumes rational leadership, good top-down planning, smooth implementation of policies, work specification and delegation that ensures an organisation that runs clock-like. Generally, a good design practice is followed to group seven to ten activities on every scale of the system to allow for efficient and effective operations, but due to chaos, things turn complex. Uncertainty, variability and irrational human behaviour ensure that most good organisational designs turns into complex adaptive systems over time. This leads to the system to exhibit characteristics such as emergence, social networks, economic cooptition and competition, and possible self-organising criticality in the system.
To assist in the mental understanding of a “complicated-turned-complex
system” within the context of entropy, I have created the concept of a business
fractal. In a complex human adaptive organisational system, activities and
objects can be designed and analysed according to a business pattern – the business
fractal. The business fractal is a geometric business shape which doesn’t become
simple if one analyses it in smaller and smaller parts. However as time passes,
the fractal will change in appearance as it is stretched and folded many times
due to time chaos. Using this construct in the space dimension (static design),
time dimension (dynamical equations of motions), and relational dimension
(structural) provides the context to understand the systems complexity from an
entropy approach.
In conclusion, the science of complexity is still new, and
the understanding of the discipline still growing. Whereas complexity science is
relatively advanced in physical systems such as biology, in the case of complex
human adaptive organisation systems we still need to go a long way to provide a
solid scientific, engineering and management platform to deal with it, due in
fact that it is a “science of everything”.
