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Robert N. Phillips
CEO, Lasotell Pty Ltd.
www.lasotell.com.au
In this article, I continue the series on Soft Systems Methodology or
"How to tackle messy situations in the real world in an organised way."
Read
Part One
Read
Part Two
In general terms, the engineer is the person who provides the how
once the what has been defined. Such engineers, given the task of
bridging a river, for example, almost always build at least one model and
use it to derive the next phase of construction. They draw on their
real-world experiences to create a model and then test construction
activities against it (physically or conceptually). The result of each test
is an action(s) that leads either to the next iteration of the model or to
the development(s) for the physical bridge. Soft Systems Methodology (SSM)
uses a similar paradigm.
Trying to improve a human-based system involves coming to grips with
various aspects of the perceived problem situation, which leads to building
models of sets of useful activities. The models are subsequently used to
identify desirable and feasible changes that could be applied to the problem
situation. Implementing the agreed changes and monitoring the effectiveness
of the system are the actions at the end of the first cycle and the
beginning of the next cycle in a never-ending learning/modifying process.
(The process of building and testing the models involves examining a variety
of possible what and how options.)
The first natural assumption we make when we find a problem situation
is that we need a system to fix it. However, that assumption
presupposes that we have a clear understanding of what is meant by system
in the context of messy human situations. Peter Checkland (Wiley 2000) shows
that human beings typically call everything a system—the legal system,
the education system, the billing system—including all the sub-parts,
such as the cancer management system within the health care system or the
accounts receivable system within the billing system. A root cause of this
habit is that we seldom take into account the difference between systematic
and systemic approaches. Checkland's definition of systemic (of or
concerning a system as a whole) is broader than the usual medical-based
definition; we will explore systemic approaches to systems in this article.
Imagine we have a fish tank that contains a paramecium, a sea anemone,
and a squid. By mere observation of each whole organism, we can see
increasing sophistication between these creatures and a corresponding
increase in capabilities and functions. If we prod each creature, we can see
a reaction called irritability that is characteristic of all living things.
This reaction is a simple example of what is called an emergent property
because it is found in whole living cells only and not in a beaker full of
the chemicals that make up the cells. Similarly, the ability of the
paramecium to replicate is another emergent property (leaving pedant/purist
views aside!). Both of these properties appear only in association with the
whole organisation and structure of a living cell. They are systemic
properties. The ability of the squid to forage for food, as opposed to the
anemone waiting for food to drift into its tentacles, is a systemic, emergent
property of an organism that has mobility.
Overall, these observed differences in emergent properties between these
creatures are directly related to the underlying hierarchical arrangement of
cells, tissues, organs, and body systems as expressed in the whole organism.
(Even though the paramecium is a single-celled organism, it still shows
hierarchical organisation because it contains a nucleus, mitochondria, and
other such organelles.)
The relevance of this example to SSM is that increasing degrees of human
organisation also show emergent properties. For example, a crowd of people
in a shopping centre, in a queue at a ticket office, or working on a car
production line show quite different characteristics from each other. The
crowd in the shopping centre moves hither and thither in seemingly random
motion, but actually, their motion is the consequence of the independent
actions of each individual. The crowd in a queue forms the size and shape of
the queue according to local, generally unspoken but commonly accepted
rules. For example, people behave in accordance with some conventions
about places in the queue. The people on the production line work
co-operatively in accordance with declared processes and procedures and
achieve things that are not possible in the other two crowds. So, we can see
that when people are arranged in hierarchical structures (groups, teams,
departments, divisions, and companies), there are emergent properties at
each level. But the most important characteristic is that the people in each
of the hierarchical entities (as opposed to the shopping centre crowd) are
participating in activities that have a common purpose. In other words, they
are involved in purposeful human activities.
Going back to the fish tank example... in addition to having emergent
properties, for the sea anemone and the squid to cope with day-to-day life,
they also require communication and control systems. While at first glance
this concept may seem a bit complex for simple creatures, such as a sea
anemone and a squid, each does, in fact, have to react to what is happening
around it. In the squid's case, it requires avoidance and hunting
behaviours if it is to eat and avoid being eaten. But more interesting, if
we go further up the animal hierarchy, we see examples of communication and
control systems in groups of animals, such as in an elephant herd when a
calf is threatened and in a hunting wolf pack. We can also see an example of
communication, but presumably defective control, in the beaching behaviour
of whales.
So, it follows that in addition to having appropriate layers of
hierarchical organisation and attendant emergent properties, human-based
systems also require communication and control systems if they are to
survive. Perhaps the best human example of these features is a well-trained
military force. The military structure is clearly layered/hierarchical and
clearly has a number of emergent properties in comparison with a crowd of
individuals. It also has a communication system and a control system that
is fully understood across the whole structure. In fact, the communication
and control systems are so intrinsic that no one seriously questions them.
It is the appropriate combination of these four basic characteristics that
allows a military force to cope successfully with the unexpected during
battle.
In the civilian world, we see a very different picture. We all know too
well that communication and control are often the most woeful
characteristics. The ability of many businesses to cope with the unexpected
(or shocks in SSM terms) is poor to non-existent and that inability shows
in numerous dismal profit figures and bankruptcies during the course of the
year. We can also point to systems that have been dramatically enhanced by
simply improving either or both of these two fundamentals, without trying to
change any other work practices.
Checkland's definition of a proper system is: a whole with a layered
structure, emergent properties, and processes (communication and control)
that enable it to adapt in response to environmental pressures. To make it
easier to focus on things that fit the definition properly, a number of
words have been coined to use instead of system. Holon, coined by Arthur
Koestler (Hutchinson 1967, 1978) is the word that seems to have the widest
usage. Using holon in the appropriate way leaves the current usage of system
unchanged, which is particularly useful given that a properly constructed
set of purposeful human activities fits the definition of a holon. All of
which makes the next step very interesting: in the same way that engineers
build prototypes of bridges, so holons (which are systemic by definition)
can be built as intellectual devices for systematically investigating the
perceived messy situation in the real world. The primary means of
investigation is by comparing the holons with the real world. As a simple
analogy—it is easy to pick the imperfections in a pair of sunglasses
if we have a perfect lens on hand for comparison.
One of the fundamental features of SSM is distinguishing between treating
a system as if it is a holon versus creating a holon (a whole with a
layered structure, emergent properties, and processes that enable it to
adapt in response to environmental pressures) and using it to learn about
the problem system. The purpose of which is to identify the changes that are
desirable and feasible. (Be warned that a common mistake is to come to think
of the holon as the model for a new, to be implemented system—the
holon is merely a device for having a meaningful discussion about, and hence
learning about, the perceived messy situation.) Given this background, we
will look briefly at the actual SSM in the next article.
References
Soft
Systems Methodology in Action
Peter Checkland and Jim Scholes
2000, New York, NY
John Wiley & Sons
ISBN: 0471986054
The
Ghost in the Machine
Arthur Koestler
1967, London, England
Hutchinson
Janus:
A Summing Up
Arthur Koestler
1978, London, England
Hutchinson
ISBN: 009132100X
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