“Invention, it must be humbly admitted, does not consist in creating out of void but out of chaos.”
―Mary Wollstonecraft Shelley
All reductive explanations are pyramid schemes that always boil down to the perpetual stability of something, but nothing is perpetual. In management as in physics, if you keep asking “why?” you will quite quickly run out of answers. In any field, the last answer that makes any sense is, “because it’s always been that way.”
What do you think lies at the foundation of any instruction, explanation, or argument? What’s the fundamental “thing” that holds everything up? It isn’t logic, reason, or human nature; it’s measure. Measure precedes discernment, judgment, and distinction. It’s what enables you to perceive. Measurement enables you to form the boundaries that allow for discrimination by which you understand everything you encounter.
When things are normal, we are able to make out what’s around us. What we can’t make out, we ignore. We walk right past what we can’t make sense of. In those cases where our attention is drawn to what we don’t understand, we perceive chaos—we can’t “make sense” of it. Our instinctive reaction to chaos is fear, and that is reasonable, based on the assumption that structures will do something to us when we come into contact with them.
How you think determines what you see. The prejudice most people carry—believing they are separate—causes them to be exclusive. For those of us who believe we’re separate, everything lies on a spectrum that runs from positive to negative. Our “why” questions always boil down to explaining something’s position on this spectrum. Our “how” questions focus on gaining advantage. This is the egoistic point of view.
The opposite is also true: what you see determines how you think. This is learning from experience, and building on existing prejudice. This is the basis of the dictum, “What fires together, wires together,” which is a flowery way of saying repetition creates habits.
“Chaos is what we’ve lost touch with. This is why it is given a bad name. It is feared by the dominant archetype of our world, which is Ego, which clenches because its existence is defined in terms of control.”
A chaotic network.
This begets the question—that no one asks— “What causes us to repeat ourselves?” The egoic answer is, because the outside world forces us to; but that’s not really true. There are always alternative ways to do things that we don’t try because we don’t think of them. We repeat ourselves and develop habits because we’re not bright enough to do otherwise. And that is because we keep making the same measurements, and consistently interpret what we see.
You might say we’re built that way, but that’s not exactly true. We’re built in a very plastic manner and we’re able to do far more than we usually attempt. The answer is that we try to do as little as possible, expend as little energy as possible, think as little as possible, and look for patterns we can repeat so as to maximize our free time.
Patterns of behavior are our first structures. Given a highly complex world, not to mention a dangerous one, having free time to consider the next obstacle is probably a good idea. Certainly, our awareness develops within certain physical constraints; but even so, most of our patterns of thought and perception are in our software.
We measure many things, and we always translate these measurements back to a scale of their proximity and value to us. This egoistic thinking makes it impossible to see the bigger picture necessary to understand the whole system. You might draw the analogy with the Special Theory of Relativity, which says that your measurement system is distorted by movement. In the case of thought, your judgment is distorted by your engagement.
It’s a poor analogy because, whereas space-time can stretch, it does not change its character, while your judgment can be distorted completely out of character. In fact, to move from the egoistic perspective to a holistic perspective, we need to dramatically change the nature of judgment.
From the point of view of ego, the goodness and badness of things do not change by going faster or slower. Bad things may become worse, and good things better, but they do not transform into each other.
In terms of the whole, the same event can have both positive and negative impacts over different time scales, in different contexts, and even in subsequent encounters. Individual judgments of positive and negative lose their meaning when seen from a larger perspective.
The question is, how can you perceive things so that things appear egoistic when viewed up close, but holistic when viewed from afar? We want one way of thinking that works in both situations because, without that, the structures that we build—like corporations—become entrenched in seeing, acting, and behaving. And while maximizing revenue is a sustainable strategy for the small ecosystem of a corner store, it is not sustainable for a global industry based on a wasting asset.
Go back to how we measure things. Measurement is based on a stable, repetitive situation. Whether you’re measuring time, distance, profit, or widgets, that measure must not change. Well, actually, it does change some. The cost of money, the value of widgets, and the mechanisms that underlie the process do change, but they change in a flexible manner. These changes deform our expectations but don’t break them, or so we hope. When some massive change does break everything, we’re usually at a total loss and many of our structures collapse. When measurement breaks, catastrophe happens.
A measurement system is fundamentally this: a series of points with distances between them. Such a system can have regular properties, such as being uniform and the same in all directions. It can allow for the infinitely small but, for the purposes of practical measurement, it doesn’t need to. A grid is a measurement system, as is graph paper, a tape measure, a clock, or a thermometer.
A regular network.
“Chaos furnishes the building blocks for order, and order breaks down to replenish chaos.”
We want a dynamic form of measurement, a way to see things that itself changes as the object that’s being looked at changes. This is where networks come in. A network is a fabric, and understanding the network as a substrate, something that exists before structure, provides this tool if we know how to use it.
A network is a relationship of things. It has a basic structure, and it can vary over space and time, but it does not have separate structures in it. It can support separate structures, but those are thought of as existing on top of the network, and not fundamental to it.
The ocean is made up of a network of water molecules. A city is a composite of many networks, one of which is people. An ecosystem is made up of a network of energy consumers and producers. In a network, we don’t give separate identity to the parts. There may be classes of parts and classes of processes, but we focus on the types and relationships.
A painting is a network of molecules of pigment that exist on a canvas. We need the canvas to maintain the network, but we are not concerned with the relationship of any particular pigment to the next. The picture that will emerge is of no concern, because at the level of a network we have no way of describing a picture.
A network is the first step above chaos. It is the most fundamental regularity we can have. It provides our first notion of measure. The simplest network has only one kind of thing, a node, and one kind of relationship, a link. Nodes and links are at the root of it. Certainly, there are more complicated networks, like pigments of a painting, but we can consider the simplest: one kind of node and one kind of link.
Types of Networks
From an egoistic point of view, all networks are the same. But when we talk about the network we’re talking about the whole thing. We’re starting off from a holistic point of view. And from this point of view, we can distinguish three different kinds of networks, even when they have nothing in them: the chaotic, the regular, and the organic.
In a chaotic network there appear to be no rules of order. There may be rules, but we can’t find them. As far as we’re concerned, there are just nodes and links with no limits on the number of links or the location of the nodes. Even a hairball has more structure than this, so that a chaotic network is really just an abstraction. Any network we draw has some limitations, so we can’t really draw an accurate chaotic network; but we draw something that gets the point across.
A regular network is one in which the rules of order are fixed and are not related to the structure. This doesn’t mean a regular network is simple, uniform, or highly ordered. A diamond is a regular network and so is the Mandelbrot fractal, but so is a hairball! A regular network is also an abstraction, because nothing is perfect in reality; but things can be close enough to form a useful structure for taking measurements.
The fabric of space-time is a network, but it’s purely an abstraction. But even though it can’t be constructed or directly observed, it is still believed to underlie everything, and its rules are believed to apply everywhere and always. Personally, I don’t believe it, as no abstraction is perfect, but we pretend it is.
There are organic networks where the rules of network change as the network changes. The rules of an organic network must involve relationships that exist outside the network. They must embody something more than just the nodes and links and rules built on them alone. There must be something else.
A mold is an organic network, as it grows in such a way as to maximally explore and consume the nutrients in its neighborhood. A tree is an organic network, as it grows to maximize the light received by its nodes while minimizing the stress on those nodes caused by the weight of its links which, in this case, are branches.
A mushroom is an organic network. At first, it develops a tree-like structure that spreads out through the soil. At some point, determined by instructions held within the intelligence of its nodes, it undergoes a transition and develops fruiting bodies which then erupt as mushrooms and produce spores. Once complete, it returns to its tree-like structure.
Human networks, like all real networks, are a combination of all three of these network types. That is, some of the structure is prescribed, some is random, and some is organic. While we might like to think of a network in the abstract as something independent, like a chessboard, real networks always interact with the structures that develop on them. Even a diamond has its flaws.
A corporation is an example of an organic network. It has a hierarchy built according to preexisting rules, yet this hierarchy suffers random failures and develops organically according to changing internal and external situations. Real networks like this must be described by an interconnecting combination of networks.
An organic network.
Emergence of Structure
“The battlefield is a scene of constant chaos. The winner will be the one who controls that chaos, both his own and the enemy’s.”
Systems drained of energy decay to their least energetic state. The least energetic state is the network devoid of structure. This is the law of increasing entropy. It’s actually not a law, it’s an observation. There is not a single reason anywhere why cold things can’t get hotter and dead things can’t come alive; and, in fact, they do that all the time, but only when there is energy flowing through them.
We know that structure emerges from chaos when energy is available. That’s because building structures takes energy, and structures store energy and, for some mysterious reason, systems universally prefer to develop structures rather than shake off energy. That is the real mystery—not why entropy increases, but why it does not.
Why, for example, should lifeless stellar dust in the coldest, darkest environment conceivable form into suns, planets, and life? Perhaps you’re of the group that would answer, “God”; but that’s cheating, so you’re out of the game.
Why, for example, when you give most people a lot of money, do they choose to build something rather than just fritter it away? There is something fundamental in us, as in the inanimate things in the universe, that likes to create structure.
Retouching Jackson Pollock’s “Number 1.”
Emergence of Measure
“The things we fear most in organizations—fluctuations, disturbances, imbalances—are the primary sources of creativity.”
― Margaret J. Wheatley
At a more fundamental level, measurement emerges from any network that gets past the chaotic stage. In a chaotic network there is no measure, as there is no regularity to support it. Every other network, however, does have a measure or what’s more formally called a metric.
Regular networks support linear metrics. That is, there is some general rule related to the nodes and the links that allows you to establish some regular unit of measure. That doesn’t mean that every node is always equidistant from every other node. Rather, it means that if you can reproduce a certain contained (or local) condition of the nodes and the links, then you’ll get a repeatable arrangement. This is why you can measure time with atoms, because if you prepare them the same way, then they’ll vibrate with the same regularity every time.
Organic networks don’t support linear metrics, and this is why they are the solution to our problem. Remember, the problem was how to measure things dynamically so that what you see can change as conditions change. An organic network will do this.
In an organic network, the network’s character changes along with the structures that develop on it, or in it. For example, in a corporation, a manager’s relationship to other people will change as the organization grows and changes. If the organization responds to its changing environment, then the change will impact its internal structure. If the internal structure recognizes the necessity of this change and distinguishes it as positive, then the organization can respond organically.
For example, if a person’s role is determined not by their rank but by their task, and their task changes, then their role should change also. If a person is aware of their limitations and their task exceeds their limitations, then they will know to expand their resources rather than to limit their tasks. This is the essential nature of growth and especially entrepreneurial growth.
In this example, the metric, or the measure, of how people relate is determined by the flow of “energy” through the links of the network. This energy is recognized as the source of new structure, and the question is not how to manage it but how to absorb it.
From the network point of view, the Blue Ocean Strategy, according to the book of the same name, is not a strategy at all. It is the description of a dynamic system that moves toward sources of energy and creates new structures from them. It is an organic network that is constantly evolving by minimizing the energy it discards and maximizing the new structures it creates.
An organization can only respond in this manner if its network is organic from the start. In addition, the notion of dynamic metric needs to be in the nodes of the network, the people themselves, and not be in the regular structure that exists outside them.
“Chaos does not mean total disorder. Chaos means a multiplicity of possibilities. Chaos is from the ancient Greek word that means a thing that is birthed from the void. And it was about that which is possible, not about disorder.”
The Mandelbrot fractal, a regular network. All its structure is internal to it.
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Nice post Lincoln,
I’ve been reading about object oriented analysis and design lately (expanding my resources) and this concept of dynamic networks is quite relevant: when we’re programming we’re trying to build networks out of known structures and the trick is to make those networks organic so that we can maintain them as circumstances change.
I like these two statements in your post:
— That is the real mystery—not why entropy increases, but why it does not.
— Perhaps you’re of the group that would answer, “God”; but that’s cheating, so you’re out of the game.
I had not thought of networks in the context of OOP, nor OOP (which I’ve done a lot of work) in the context of organic networks. But why not? There’s a lot more structure provided when defining object classes than in evolutionary networks, which undergo seismic shifts.