Robert N. Phillips
CEO, Lasotell Pty Ltd.
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.”
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 asystem 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 communicationand 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 itis 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.
Soft Systems Methodology in Action
Peter Checkland and Jim Scholes
2000, New York, NY
John Wiley & Sons
The Ghost in the Machine
1967, London, England
Janus: A Summing Up
1978, London, England