When I read something like..
Self-organization is the process where a structure or pattern appears in a system without a central authority or external element imposing it through planning.
I get a smile on my face. The populist (like that above) definition of a CAS is clearly designed to inform the general public and establish a basis of discussion around the notion that organizations and the people who populate them are subject to forces outside of their control and management must act accordingly.
Good advice. But it's one of those good pieces of advice based on a naïve understanding of the underlying principles. In this case the Lagrangian of the individual elements that interact with each through a combined set of ground rules. In the mechanical systems domain, gravitational, electromagnetic, the strong, and weak forces - your choice.
But First Some Background
A vision shared by most researchers in complex systems is that certain intrinsic, perhaps even universal features capture fundamental aspects of complexity in a manner which transcends specific domains. It is in identifying these features that sharp differences arise. In disciplines such as biology, engineering, sociology, economics, and ecology, individual complex systems are necessarily the objects of study, but there often appears to be little common ground between their models, abstractions, and methods.
From Complexity and Robustness, J. M. Carlson, Department of Physics, University of California, Santa Barbara, CA 93106 and John Doyley, Control and Dynamical Systems, California Institute of Technology, Pasadena, CA 91125.
It's for this very reason that statements found in the first quote - in the absence of a domain and context - have little use outside of popularizing the notion of Complex Adaptive Systems. They best serve those seeking words without the underlying tools for analysis.
It is this little common ground where the popularizations have difficulty. They want to state ideas without out all the wrangling about the details, the semantics, the gory mathematical complexities. They are popular and therefore readable in the absence of the details.
Failing to acknowledge that popularizations are just that, popular for a reason, creates issues when it comes to making calculations or decisions using other peoples money.
Back to the Populist Approach
Who cares if the statement above is based on naive principles, if it works? Well clearly those reading and writing general management books are not concerned with the underlying details. Their job is to inform the populace not provide tools to calculate solutions.I'm reminded of the advice to Stephen Hawking when he was writing A Brief History in Time. He was told sales of the book go down by ½ for every equation he used. Compared to The Large Scale Structure of Space-Time, (a graduate text I still have on my shelf), where every page of the 381 pages is as dense like the clip to the left of this paragraph. (Click for full size)
Motivation for the Underlying Principles
Let's look beyond the simple definition for some understanding of CAS. But first let's look for some motivation...
As a physician, I learned to think from a biological perspective. When I went into management, traditional organizational theory seemed artificial, foreign to my experience. So when I started studying complexity, I was stunned. Here was a way of thinking about organizations that compared them to living things. That makes sense to me, intuitively." Richard Weinberg, MD, Vice President, Network Development, Atlantic Health System, Passaic, New Jersey
This intuitive understanding is critical for many reasons, not the least of which is to convey a broader understanding of the problem space to the general public to gain their interest in further discussion.
So here's a succinct definition from the Santa Fe Institute focused on the social aspects of CAS.
Definition: A Complex Adaptive System (CAS) is a system of individual agents, who have the freedom to act in ways that are not always totally predictable, and whose actions are interconnected such that one agent's actions changes the context for other agents. Examples of complex adaptive systems include: the stock market, a colony of termites, the human body immune system; and just about any collection of humans such as an industry, a business organization, a department within an organization, a team, a church group, a family, or the Rotary Club.
In this definition of CAS these agents act according to their own rules. These rules are defined for specific classes of agents in the system. Either one rule for all or a single rule for each of agents, or any combination.
The behavior of the resulting system emerges from the interaction among the agents executing their rules of interaction. In this case the Central Authority is the collection (one or many) Ground Rules for how these interactions take place. This is subtle but critical to the next step, when CAS is applied to business.
There are always Ground Rules. To not have ground rules defies the laws of physics. But these ground rules may be flawed. When they are, the outside observer would say the system is broken. That is the system behaves in undesirable ways. But those ground rules that central authority is still in place. It is always in place.
In order to return the system to its desired behavior, those ground rules of interaction must change.
The CAS exhibits novel behaviors resulting from the interactions. The interactions defined by the ground rules covering all objects in the system, or "N" Ground Rules one for each element, result in fundamentally unpredictable behavior. It is not a question of better understandings of the agents, better models, or faster computing; as we have come to believe erroneously, based on the machine metaphor. We simply cannot reliably predict the detailed behavior of a CAS through analysis.
But this does not mean there is no control system in place. This control system is distributed among the elements of the system. When the phrase...
where a structure or pattern appears in a system without a central authority
...is used it begs the question - what is the definition of Central? Most populist approaches fail to make this subtle and important distinction. This is why they are populist. To make these distinctions requires deep analysis and the introduction of more complex mathematics. The analogy used in the original quote suffices for the discussion at the populist level. It works, so let's move on.
But of course, we'll want to calculate something one of these days. Say the forecast close of the Stock Market tomorrow, given any non-disruptive events. While we cannot predict the precise closing value of the Dow Jones Industrial Average tomorrow, we can estimate (with a confidence interval) the market trend as bullish or bearish and take appropriate action on this estimate with a known confidence.
Note the qualifier of any non-disruptive event. This approach provides some confidence in understanding human based systems. But care is needed to not over-estimate the ability to predict what will happen outside the error bounds of our forecast.
It is popular to say ...
In a CAS, control is dispersed throughout the interactions among agents; a central controller is not needed.
Notice the difference between control and controller. The controller is distributed among the agents. But there is control, just not in a single entity.
In the end the business writers are right, but for the wrong reason.
Trying to apply external control, or a single internal controller leads to disappointment. But there is control and that control must be in place for any system to work and not turn into a dispersed set of agents flying off into the universe. This is the definition of Chaos.
The Take Away
The ground rules of the independent controllers that make up the control algorithm of the system must act in ways that produce beneficial outcomes. It is the correction of the actions of the individual (or collective) controllers that make up the control algorithm that must be the target of management processes.
Not the naive belief that there is no control needed and the control will emerge from the group of agents. There is always control at some level, be it microscopic or macroscopic. But it is always there. If it is microscopic we may not be able to see it or have any influence on its outcomes. If it is at too high a macroscopic level we are likely not going the like the outcome either.
In the end it is the semantics that are important, especially when we want to calculate something - say the probability that it will rain tomorrow on the Front Range of the Rocky Mountains. Since the weather on the Front Range is a CAS - all weather is a CAS - doesn't not remove our ability to make forecasts of it's behavior in the very short term and the long term - Global Circulation Model scales. And especially when we want to make MANAGEMENT decisions in the presence of CAS, these populist descriptions fail to provide much guidance.
