Creating the Self Organizing System

When creating a model for any system – a representation of how you expect events and participants to behave – we must first reconcile that as advanced as our knowledge of the world has become, the gaps in knowledge still outweigh the known. This variance is due in large part to an impossibility of considering every variable that can affect any system at every point in time. Every system has the potential to fall into chaos, but part of the difficulty in studying chaos arises because complex systems are difficult to study in pieces. Efforts to separate pieces of dynamical systems often fall apart. The system depends on each minute part of that system and the way it interacts with all other components. 

In light of a system’s lean towards chaos, it is critical we take our eye of short-term events and take a longer view of behavior and structure. When most of us attempt to illustrate a process, it is typically depicted in a linear fashion, with a start (input), events, and a finish (output). However, we must also consider that not all events are weighted equally within a continuum. The relationship between cause and effect can only be drawn with curves or wiggles, not with a straight line. Some things matter more than others in the dynamic behavior of a system. 

We often draw the wrong conclusions from accurate analysis because we are focused on the event outputs, which are snapshots of a particular moment in time, rather than dynamic patterns of behavior. Chaos creates growth, stagnation, decline, oscillation, randomness, or evolution in a system, but taking a longer view of history better reveals the overall structure of the system. We saw the event-by-event rise and fall of candidates during the 2016 Presidential Election, as short-term analyses are postulated based on a debate performance or new found “skeleton in the closet.” Instead of looking at the overall structure of how a candidate was likely to perform over time, we instead focused on catchy headlines and sensationalism. This creates a feedback loop for the candidates in the election as they realize if a little bit of outrageous rhetoric did some good, than a lot more will do a lot more good. 

In general, human beings are really bad at drawing correct conclusions from events. Daniel Kahneman, a Nobel Prize Winner in Economics, says we are slaves to our psychological, emotional, social, and situational influences whenever we are confronted with drawing a conclusion. Kahneman terms this state “cognitive bias” (bounded rationality) and it causes us to make decisions based on limited information or self-interest. This state is difficult to overcome due to cognitive dissonance. Leon Festinger proposed the theory in 1957, and showed that most people want to maintain consistency in their thoughts and beliefs, and if those worldviews are challenged, it can lead to irrational behavior. When two cognitions are at odds with each other, we will tend to hold on to our belief systems even when opposing facts are present. For example, thinking smoking causes lung cancer will cause dissonance if a person smokes. However, new information such as “research has not proved definitely that smoking causes lung cancer" may reduce the dissonance. In a disorderly, chaotic world, dissonance increases the strength of the feedback loop as we seek evidence that corroborates what we already believe and ignore any evidence counter to it. 

When dealing with chaos, and realizing that everything physical comes from somewhere, goes somewhere, and keeps moving, we have to invent boundaries for clarity and sanity. Deciding where to draw boundaries depends on who wants to know, for what purpose, over how long. Boundaries are necessary when we are analyzing for desired outputs. For example, if we are seeking to find the best possible method for educating our children, we would look at the school as the system. Elements of the system would include the inflows (the physical building, location, teachers, learning tools), stocks (the students) and the outflows (highly-learned students). By setting these boundaries we can measure each elements relative contribution to the system within the boundaries we have set, and adjust flows as desired. However, outside the boundaries of the school model can be limiting factors such as unsupportive parents, hungry children, or a fiscal shortfall. In considering boundaries to a system we know that infinite growth is not possible – we cannot exponentially add unlimited learning tools into a school – so we must decide what limits to live within.  

In April, 2014 I received my Permaculture Design Certificate (PDC), and Donella Meadows is a well-known figure in that circle. The term Permaculture was coined in 1978 by Bill Mollison and David Holmgren, and it postulated that people could design synergistic assemblies of plants, animals, and structures that served human needs but adhered to nature’s logic. Ecology looks at the living communities of many species of plants, animals, microbes, and the landscapes they inhabit (stocks) to assess the quantity and quality of information and resources that flow within the system. It identifies system boundaries and can see where the information is missing and when it is critically threatened. At its core, ecology is the study of feedback loops and their consequences – if a key species goes extinct and an important function of the whole system fails. It requires that we think about wholes and their relationship to the other wholes, and while self-regulating, each is influenced by system feedback. When using Google Earth to survey the landscape it becomes clear that there is barely a foot of land that humans have not formed, shaped, or impacted. In this way, human activity is the limiting factor in ecological survival. 

There are 12 core principles in Permaculture which consist of: 1) observe and interact, 2) catch and store energy, 3) get a yield, 4) self-regulate and accept feedback, 5) use and value nature’s gifts, 6) waste not, 7) design from pattern to details, 8) integrate, 9) choose small and slow, 10) work diversity, 11) push the edge, and 12) respond to change. It should be apparent that the first principle is the most important for system design. If we are tasked with restoring a wetland or designing a homestead, the initial task is to recognize patterns so we can see trends and influences that are recurring. What microclimates exist within the property during different seasons? How does water flow on the slope of the land? Where does the wind blow in the winter? Is there fire risk at any section of the plot? Nearby pollution? What kind of soil exists? Has anything changed on the property recently? Instead of protracted and thoughtless labor, the regenerative process starts with protracted and thoughtful observation over time. The patterns that are revealed allow us to interact, and possibly change the system for the better. 

We also know that systems cannot grow forever as they are always bounded by resource and energy limits. Recognizing these are crucial to health and balance. We cannot navigate well in an interconnected, feedback-dominated world unless we look for long-term behavior and structure, become aware of boundaries, and take into account limiting factors, non-linearities and delays. Permaculture is a system within the larger system that provides necessary checks and balances by accounting for the chaos of ecological balance. It takes into account people, nature, and structures and realizes that each cycle of design begins with an event – a tree falling, the act of moving into a new house, a street widening, a school closure – and from that its sequence of principles follows the model dynamically as well as logically.

Peter Senge's, The Fifth Discipline, extends this line of thinking into the business world. When analyzing any organization it is helpful to comprehend the whole and examine the interrelationship between the parts - departments, people, internal systems - to begin to connect what was initially seen as unrelated variables (culture, skill, politics). This forces a long-term view of strategy, as what you ignore in the short run can come back to haunt you in the long run (cuts in marketing, layoffs). It is critical to identify all the inputs, reinforcing feedback loops, and balancing mechanisms so the real system can be mapped for desired outcomes. 

It begins with "Personal Mastery", a process by which those in an organization focus their energies, develop patience, and see reality objectively. A learning organization exists perpetually in an information gathering mode and is self aware of its ignorance, incompetence, and where they need to grow. Do the employee's visions match that of the company's? Are internal behaviors aligned with the success of the team? Are people aware of the organization's mission relates to its financials? Building "Mental Models" begins with turning the mirror inward. This discipline allows people to expose their own thinking while simultaneously being open to the thinking of others. The generalizations we hold about reality has to match the data. At its core, this step seeks to distribute business responsibility while retaining coordination and control of the mission. When teams learn together, not only are there good results for the organization, but its members grow more rapidly than would have occurred otherwise. 

When "Team Learning" exists there is a flow of information, feedback, generative thinking, and innovative problem solving. People begin to learn to ask questions that further knowledge rather than offering expert points. When a genuine vision emerges, people naturally excel and learn - not because they have to, but because they want to. This "Shared Vision" aligns a company's purpose with the efforts of its people, thereby fostering a culture of commitment rather than compliance. As in nature, the most powerful system in existence is one that self organizes.