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Wheatley, Margaret J. Leadership and the New Science: Learning about Organization from an Orderly Universe. San Francisco, CA: Berrett-Kohler Publishers, 1992. 100-137.

 

CHAPTER 6

The Creative Energy of the Universe—Information

 

“An organization that creates information is nothing but an organization that allows a maximum of self-organizing order or information out of chaos.”

—Ikujira Nonaka

 

Why is there such an epidemic of “poor communications” within organizations? In every one I’ve worked in, employees have ranked it right at the top of major issues. Indeed, its appearance on those lists in the past years became so predictable that I grew somewhat numb to it. Poor communication was a superficial diagnosis, I thought, that covered up other, more specific issues. Over the years, I developed a conditioned response to “communications problems” the minute they were brought up. I disregarded the category. I started pushing people to “get beyond” that catch-all phrase, to “give me more concrete examples” of communications failures. I believed I was en route to the “real” issues that would have nothing to do with communication.

Now I know I was wrong. My frustration with pat phrases didn’t arise from people’s lack of clarity about what was bothering them. They were right. They were suffering from information problems. Asking them to identify smaller, more specific problems was pushing them in exactly the wrong direction, because the real problems were big—bigger than anything I imagined. What we were all suffering from, then and now, is a fundamental misperception of information: what it is, how it works, and what we might expect from it.

The nub of the problem is that we’ve treated information as a “thing,” as an inert entity to disseminate. Things are stable; they have dimensions and volume. You can get your hands around a thing. You can move it, track it, pass it back and [102] forth. Things can be managed because they’re so concrete. This “thing” view of information arose from several decades of information theory that treated reformation as a quantity, as “bits” to be transmitted and received. Information was a commodity to transfer from one place to another. The content, meaning, and purpose of information were ignored; they were not part of the theoretical construct (Gleick 1987, 255-56). Information theorists also focused on “noise”—those interferences that prevented smooth movement of the bits. Ideally, it was felt, information moved virgin-like through the system, untouched by anything.

I believe it is information theory that has gotten us into trouble. We don’t understand information at all.

What’s curious about our misperceptions of information is that we all started out on a much higher plane of awareness. Remember playing “telephone” and being delighted and amazed at how the message got distorted with only a few layers? At a young age, we knew information for its dynamic qualities, for its constantly changing aliveness. But when we entered organizational life, we left that perspective behind. We expected information to be controllable, stable, and useful for our purposes. We expected to be able to manage it.                                                           

In the universe new science is exploring, information is a very different “thing.” It is not the limited, quantifiable, put-it-in-a-memo-and-send-it-out commodity with which we have become so frustrated. In new theories of evolution and order, information is a dynamic element, taking center stage. It is information that gives order, that prompts growth, that defines what is alive. It is the underlying structure and the dynamic process that ensure life.

How can information be a dynamic or a structure rather than just content? A [103] dramatic example of this, one that pushes our self-concept to the edge, is seen by asking: Who am I? Am I a body containing a mind, or a mind that has created a body? Am I a physical structure that processes information or non-physical information organizing itself into form?

Although we experience ourselves as a stable form, our body changes frequently. As physician Deepak Chopra likes to explain, our skin is new every month, our liver every six weeks; and even our brain, with all those valuable cells storing acquired knowledge, changes its content of carbon, nitrogen, and oxygen about every twelve months. Day after day, as we inhale and exhale, we give off what were our cells, and take in elements from other organisms to create new cells. “All of us,” observes Chopra, “are much more like a river than anything frozen in time and space” (1990).

In spite of this exchange, we remain rather constant, due to the organizing function of the information contained in our DNA.

At any point in the body-mind, two things come together—a bit of information and a bit of matter. Of the two, the information has a longer life span than the solid matter it is matched with. As the atoms of carbon, hydrogen, oxygen, and nitrogen swirl through our DNA, like birds of passage that alight only to migrate on, the bit of matter changes, yet there is always a structure waiting for the next atoms. In fact, DNA never budges so much as a thousandth of a millimeter in its precise structure, because the genomes—the bits of information in DNA—remember where everything goes, all 3 billion of them. This fact makes us realize that memory must be more permanent than matter. What is a cell, then? It is a memory that has built some matter around itself, forming a specific pattern. Your body is just the place [104] your memory calls home. (Chopra 1989, 87; italics added)

Jantsch describes the same phenomenon in dissipative structures, asking whether they should be understood as a material structure that organizes energy, or as an energy structure capable of organizing the flow of matter. “At higher levels of self-organization,” he concludes, “a description will suggest itself which views energy systems manifesting themselves in the organization of material processes and structures” (1980, 35).

Information organizes matter into form, resulting in physical structures. The function of information is revealed in the word itself: in-formation. We haven’t noticed information as structure because all around us are physical forms that we can see and touch and that beguile us into confusing the system’s structure with its physical manifestation. Yet the real system, that which endures and evolves, is energy. Matter flows through it, assuming different forms as required. When the information changes (as when disturbances increase), a new structure materializes. Even a large structure like an ecosystem has been described similarly, as “an information system which manifests itself in the organization of matter,” evolving as it accumulates information (Jantsch 1980, 141).

In a constantly evolving, dynamic universe, information is the fundamental ingredient, the key source of structuration—the process of creating structure. Something we cannot see, touch, or get our hands around is out there, organizing life. Information is managing us.

For a system to remain alive, for the universe to move onward, information must be continually generated. If there is nothing new, or if the information that exists merely confirms what is, then the result will be death. Isolated systems [105] wind down and decay, victims of the laws of entropy. The fuel of life is new information—novelty—ordered into new structures. We need to have information coursing through our systems, disturbing the peace, imbuing everything it touches with new life. We need, therefore, to develop new approaches to information—not management but encouragement, not control but genesis. How do we create more of this wonderful life source?

Information is unique as a resource because of its capacity to generate itself. It’s the solar energy of organization—inexhaustible, with new progeny emerging every time information meets up with itself. As long as there are senders and receivers linked together in a context, fertility abounds. All that is needed is freedom of circulation to guarantee new births. In fact, the greatest generator of information is chaos, where so much spawning of information goes on that researchers feel obliged to monitor every moment of the system’s activity lest they miss something (Gleick 1987, 260).

Of course, this is exactly what we fear. We have no desire to let information roam about, to let it procreate promiscuously where it will, to create chaos. Our management task is to enforce control, to keep information contained, to pass it down in such a way that no procreation occurs. Information chastity belts are a central management function. The last thing we need is information, running loose in our organizations. And there are good reasons for our stern, puritanical attitudes toward information: Misplaced information seems to have created enough horror stories to justify our frequent witch hunts.

But if information is to function as a self-generating source of organizational vitality, we must abandon our dark cloaks of control and trust in the principles of self-organization, even in our own organizations. Information is the source of [106] order, an order we do not impose, but an order nonetheless. All of nature uses information this way. Can information, therefore, be used as an ordering mechanism for humanly-created organizations?

Information can serve such an organizational function only if organizations are living entities and respond to the same dynamics as open systems. A key question, then, is, are organizations alive, are they conscious, responsive entities? A new definition of consciousness—broader and more provocative—is emerging in some fields of science that can help frame an answer to these questions.

Prigogine was stimulated to think about consciousness when he observed a process of communication in certain chemical reactions. He concluded that even in “non-living” chemical solutions, communication occurs, generating order. In the chemical clocks he studied, the random mix of molecules became coordinated at a certain point. A murky gray solution, for example, suddenly would begin pulsing, first black, then white. In chemical clocks, all molecules act in total synchronization, changing their chemical identity simultaneously. “The amazing thing,” Prigogine notes, “is that each molecule, knows in some way what the other molecules will do at the same time, over relatively macroscopic distances. These experiments provide examples of the ways in which molecules communicate .... That is a property everybody always accepted in living systems, but in nonliving systems it was quite unexpected” (1983, 90):

If the capacity to deal with information, to communicate, defines a system as conscious, then the world is rich in consciousness, extending to include even those things we have classified as inanimate. Consciousness occurs in systems that do not even have an identifiable brain.

If we understand consciousness from the viewpoint of machine imagery, this [107] makes no sense. If there is no identifiable part that handles thinking and communication, then there can be no such activity. In the past, we measured an organism’s capacity for intelligence by counting the parts of its brain (or noting the lack of one). If crayfish have only 90,000 neurons, compared to our 10 billion or so, then certainly they aren’t very smart. But then we discovered that crayfish are capable of doing far more than could have been predicted from our mechanistic models. One school of researchers working in artificial intelligence suggests that consciousness can’t be discerned from the constituent parts of an entity. Instead, consciousness is a property that emerges when a certain level of organization is reached. Anything capable of self-organizing, therefore, possesses a level of consciousness. A well-ordered system is defined not by how many brain parts it has, but by how much information it can process. The greater the ability to process information, the greater the level of consciousness.

With this definition, organizations qualify as conscious entities. They also meet Gregory Bateson’s (1980) criteria for “Mind.” They have capacities for generating and absorbing information, for feedback, for self-regulation. In fact, information is an organization’s primary source of nourishment; it is so vital to survival that its absence creates a strong vacuum. If information is not available, people make it up. Rumors proliferate, things get out of hand—all because people lack the real thing. Given the need for constant nourishing information, it is no wonder that “poor communication” inevitably appears so high on the problems list. Employees know it is the critical vital sign of organizational health. We have lived for so long in the tight confines of bureaucracies—what Max DePree, former CEO of Herman Miller, describes as “the most superficial and fatuous of all relationships”—that we need to learn how to live in a conscious [108] organization, how to facilitate its intelligence. This requires an entirely new relationship with information, one in which we embrace its living properties. Not so that we open ourselves to indiscriminate chaos, but so that we facilitate aliveness and responsiveness. If we are seeking resilient organizations, a property prized in self-organizing systems, information needs to be our key ally.

Think about how we generally have treated information in the past. We’ve known it was important, but we’ve handled it in ways that have destroyed many of its life-giving properties. For one thing, we’ve taken disturbances and fluctuations and averaged them together to give us comfortable statistics. Our training has been to look for big numbers, important trends, major variances. Yet it is the slight variations—even, whispered at first—that we need to encourage. (Some of the recent work with statistics used in quality programs does emphasize the detection of these slight variations.)

Or we’ve taken conflicting information, rich with the possibility of moving us to new levels of understanding, and, instead, felt the need to play Solomon, to decide which piece of information or which position was correct. “Let’s get to the bottom of this,” we say, pointing our efforts dead into the ground—away from the conflicts that can move us toward the light, toward new, more complex understandings. We’ve been so engaged in rounding things off, smoothing things over, keeping the lid on (the metaphors are numerous), that our organizations have been dying, literally, for information they could feed on, information that was different, disconfirming, and filled with enough instability to knock the system into new life.

We do not exist at the whim of random information; that is not the fearsome prospect which greets us in conscious organizations. Our own consciousness plays [109] a crucial role. We, alone and in groups, serve as gatekeepers, deciding which fluctuations to pay attention to, which to suppress. We already are highly skilled at this, but the gate-keeping criteria need revision. We need to open the gates to more information, in more places, and to seek out information that is ambiguous, complex, of no immediate value. I know of one organization that thinks of information as a salmon. If its organizational streams are well-stocked, the belief goes, information will find its way to where it needs to be. The organization’s job is to keep the streams clear, so that the salmon have an easy time of it. The result is a harvest of new ideas and projects.

Information is always spawned out of uncertain, even chaotic circumstances. ~, This is not reassuring prospect. How are we to welcome information into our organizations and ally ourselves with it as a partner in our search for organizational order, if the processes that give it birth are ambiguity and complexity? In a profession that has raised the practice of “no surprises” to a high art, sponsoring such processes reads like a macabre prescription for self-destruction. Few things make us more frantic than increasing complexity. And although we say we’ve come to tolerate ambiguity rather well over the past years (because we had no other choice—it wasn’t going away), it often appears that we don’t tolerate it as much as we shield ourselves from it. We have a hard time with lack of clarity, or with questions that have no readily available answers. We quickly find our way out of these discomforts, focusing on one element, coming up with a solution, and pretending not to notice the questions we’ve left hanging. We feel safer with blinders on, fearing that unimpaired vision will only add to our distress.

We fear both ambiguity and complexity in management because we still focus on the parts, rather than the whole system. We still believe that influence is a [110] localized event, where we must directly touch what we seek to affect. We still believe that what holds a system together are point to point connections that must be laboriously woven together by us. Complexity only adds to our task, requiring us to keep track of more things, handle more pieces, make more connections. As things increase in number or detail, the span of control stretches out elastically, and, suddenly, we are snapped into unmanagability.

But there is a way out of this fear of complexity, and we find it as we step back and refocus our attention on the whole. When we give up myopic attention to details and stand far enough away to observe the movement of the total system, we develop a new appreciation for what is required to manage a complex system. Peter Senge, in his work in systems theory (1990), develops complex nonlinear systems to portray the dynamics of an organization. This whole-system view requires very different management expectations and analytic processes. Rather than creating a model that forecasts the future of the system, nonlinear models encourage the modeler to play with them and observe what happens. Different variables are tried out “in order to learn about the system’s critical points and its homeostasis,” Senge reports. Controlling the model is neither a goal nor an expectation. Analysts want to increase their intuitions about how the system works so they “can interact with it more harmoniously” (in Briggs and Peat 1989, 175).

This is such a remarkably different approach to analysis, this sensing into the movement and shape of a system, this desire to be in harmony with it. The more we develop a sensitivity to systems, the more we redefine our role in managing the system. The intent is not to find the one variable or set of variables that will allow us to assert control. This has always been an illusion anyway. Rather, the intent becomes one of understanding movement based on a deep respect for the [111] web of activity and relationships that comprise the system. Physicist David Peat terms this “gentle action . . . involving extremely subtle actions that are widely distributed over the whole system.” The intent is not to push and pull, but rather to give form to what is unfolding (1991, 217-20).

A system’s perspective, then, can handle complexity because it does not need to deal with it in a linear fashion. We don’t need to make point-to-point connections among separate things; we don’t need to move information along linear pathways. Managers have long treated information this way, guiding it through channels, passing it onto the next point. We’ve been inspired in this by mechanistic models of brain function, believing information is assiduously moved along neural pathways, passed from one neuron to the next. But we are beginning to understand brain function differently.

Newer theories of the brain describe information as widely distributed, not necessarily limited to specific neuron sites. In mapping areas of the brain to determine those that relate to specific signals (for example, those related to hand movements), neuroscientists have found that these “sites” do not correspond to any particular neurons. Instead of a specific physical place, researchers have observed a more fluid pattern of electrical activity. Instructions, such as those for a particular finger movement, seem to be distributed through a shifting network. These memories, it is now thought, “must arise as relationships within the whole neural network” (Briggs and Peat 1989, 171). Where information is stored in networks of relationships among neurons, damage to a particular area of the brain will not result in the loss of that information. Other areas in the network may retain that information in some form.

These neural nets have been simulated to some degree in computers using [112] parallel processing. Zohar describes them as a “rather messy, higgledy-piggledy wiring design, where everything seems randomly connected to everything else” (1990, 72). In both of these systems—our brains and the computers that mimic them—complex information travels seemingly randomly across broad expanses, organizing into memory and functions.

Instead of channeled flows of information, we have images of neural nets transmitting information in all directions simultaneously. How this rather “higgledy-piggledy” system works is not clear. We can neither precisely track nor control how such random distribution of information achieves a sense-making capacity. But we each live with the evidence of its effectiveness.

In a hologram, every part contains enough information, in condensed form, to display the whole. “The part is in the whole and the whole is in the part . . . ; the part has access to the whole,” writes scientist and science commentator Ken Wilbur (1985, 2; italics added). When light is reflected from an object, it creates wave patterns based on the light scattered by the object. These wave patterns are stored on a photographic plate as interference patterns. The image looks blurred, even random. But when a laser light is shone on the image, the original wave pattern is regenerated and what emerges is a three-dimensional image of the whole object. The image of the whole can be reconstructed from any fragment of the original image.

Holograms create wonderful images for the distribution of information in organizations. In fact, we already have an experience with organizational holograms in our current approach to customer service. Most organizations acknowledge that when a customer comes in contact with anyone from the organization, no matter his or her position, the customer experiences the total [113] organization, for good or ill. Under the laser light of these “moments of truth” (Jan Carlzon of SAS’s phrase), the organization becomes visible. We can improve the image that is regenerated by the glare of customer scrutiny only if we understand that every employee has these holographic qualities and truly is capable of reflecting back the image of the total organization. We improve customer satisfaction when we recognize and support organizations as holograms. Just like an actual hologram, if we distribute information broadly across the organization, we strengthen its image.                       

We have other models in our experience that teach us about the benefits of creating complex levels of information in organizations. The literature on organizational innovation is rich in lessons that apply here; and, not surprisingly, it describes processes that are also prevalent in the natural universe. Innovation is fostered by information gathered from new connections; from insights gained by journeys into other disciplines or places; from active, collegial networks and fluid open boundaries. Innovation arises from ongoing circles of exchange, where information is not just accumulated or stored, but created. Knowledge is generated anew from connections that weren’t there before. When this information self-organizes, innovations occur, the progeny of information—rich, ambiguous environments.

The process of information generating and then self-organizing is evident in one type of planning model that I and others use, that of a future search conference (see Weisbord 1987, ch. 14; and 1992). The purpose is to get the whole system in the room to develop a desired future for the organization. People from all parts of the organization as well as outside constituents work together, generating information on the organization’s past experiences, internal [114] capacities, and external demands. The first days are spent bringing to the surface the information contained in the organizational neural net of the people in the room. Information is generated in deliberately overwhelming amounts. But by the end of two or three days, the group self-organizes, weaving all that information into potent visions of the future. Rather than basing agreements on the lowest common denominator, the organization present at the conference has self-organized into a higher form, with new and challenging directions.

Although in futures search work complex levels of information are intentionally created, in nature it doesn’t take much information, necessarily, to create interesting new structures. Simple information can complexity into new forms just from being fed back on itself. One result is displayed in the ineffable beauty of fractals (see pages 80-81). These geometrical forms are generated by computers from relatively little information expressed in as few as three nonlinear equations. When the equations are fed back on themselves—a process of “evolving feedback”—elaborate levels of differentiation and scaling are created.

Fractals are . . . complex by virtue of their infinite detail and unique mathematical properties (no two fractals are the same), yet they’re simple because they can be generated through successive applications of simple iterations .... It’s a new brand of reductionism . . . utterly unlike the old reductionism, which sees complexity as built up out of simple forms, as an intricate building is made out of a few simple shapes or bricks. Here the simple iteration in effect liberates the complexity hidden within it, giving access to creative potential. The equation isn’t the plot of a shape as it is in Euclid. Rather, the equation provides the starting point for evolving feedback. (Briggs and Peat 1989, 104; italics added)

[115]As a consultant, the most important intervention I ever make is when I feed back organizational data to the whole organization. The data often are quite simple, containing a large percentage of information that is already known to many in the organization.

But when the organization is willing to give public voice to the information—to listen to different interpretations and to process them together—the information becomes amplified. In this process of shared reflection, a small finding can grow as it feeds back on itself, building in significance with each new perception or interpretation. As with the creation of fractals, the simple process of iteration eventually reveals the complexity hidden within the issue. From this level of understanding, creative responses emerge and significant change becomes possible.

Our search for organizations that are well-ordered by open and flowing information leads to two complementary processes and tasks: those that create new information, and those that feed existing information back on itself. We already know many of these processes; we just need to emphasize them differently or give them more freedom in their workings. For example, information can be created every time we bring people together in new ways. Activities that create circulation and movement, even the old chestnuts of work teams, job rotations, and task forces, are all potential creators of information. We often limit their potential because we circumscribe them with rules and chains of command or give them narrow mandates or restrict their access to information. But if we liberate them from those confines and allow them greater autonomy, constrained more by purpose than by rules or preset expectations, then their potential for generating information is great.

[116] We also create order when we invite conflicts and contradictions to rise to the surface, when we search them out, highlight them, even allowing them to grow large and worrisome. We need to support people in the hunt for unsettling or discomfirming information, and provide them with the resources of time, colleagues, and opportunities for processing the information. We’ve seen the value of this process in quality programs and participative management. In such companies, workers are encouraged to look for fluctuations, and processes are in place to support discussions among many levels of the organization. Through constant exchanges, new information is spawned, and the organization grows in effectiveness. I am intrigued by the thought that these programs work well, not simply because they support employee contribution and involvement, but because they generate the very energy that orders the universe—information.

We can encourage vital organizational ambiguity with plans that are open, visions that inspire but do not describe, and by the encouragement of questions that ask “Why?” many times over. Jantsch asks managers to be “equilibrium busters.” No longer the caretakers of order, we become the facilitators of disorder. We stir things up and roil the pot, looking always for those disturbances that challenge and disrupt until, finally, things become so jumbled that we reorganize work at a new level of efficacy.

If we accept this challenge to be equilibrium busters, we will find the task easier than we had thought. Complexity is achieved easily these days simply because so much information is available in non-linear, diverse forms. Our thinking processes have always yielded riches when we’ve approached things openly, letting free associations form into new ideas. Many would argue that we’ve used such a small part of our mental capacity because of our insistence on linear [117] thinking. Now we have the technology to mirror more generative processes. More and more, the world of information is associative, networked, and heuristic. We are coming to understand the importance of relationships and non-linear connections as the source of new knowledge. Our task is to create organizational forms that facilitate these processes.

Gore Associates, manufacturers of GoreTex®, models one such structure with its open “lattice organization.” Roles and structure are created from need and interest; relationships, exchanges, and connections among employees (almost everyone bears the title associate) are nurtured as the primary source of organizational creativity and success. One observer noted that the issue was not who or what position would take care of the problem, but what energy, skill, influence, and wisdom were available to contribute to the solution (Pacanowski 1988).

Slowly but perceptibly, other organizations are moving into the realm of increased consciousness. Thinking has become a precious resource, and not just ate higher levels of management. We now recognize that many workers need to be trained to interpret the interactions among complex variables. “Intellectual capital” is on the rise, a phrase that tells of the new value being placed on the capacity to generate knowledge. More and more, there is an openness to inter and intra-organizational exchanges, to decreasing layers of hierarchy, to smart machines, and to the flow of information among all levels. Learning organizations are taking hold. Consciousness is growing. Is new order on the way?

My own faith in the evolution of organizations to higher levels of consciousness arises from my growing understanding and belief that this is an intrinsically well-ordered universe. As I read further into biology and physics, I recognize that natural systems engage with the universe differently than we do. [118] We struggle to build layer upon layer, while they unfold. We labor hard to hold things together, while they participate openly and complex structures emerge. Jantsch contrasts these two approaches: “[Building-up] emphasizes structure and describes the emergence of hierarchical levels by the joining of systems ‘from the bottom up.’ Unfolding, in contrast, implies the interweaving of processes which lead simultaneously to phenomena of structuration at different hierarchical levels . . . . Complexity emerges from the interpenetration of processes of differentiation and integration, processes running ‘from the top down’ and ‘from the bottom up’ at the same time” (1980, 75).

We need to learn more about this “interweaving of processes” that leads to structure. In ways we have never noticed, the whole of a system manages itself as a total system through natural processes that maintain its integrity. It is critical that we see these processes. It will shift our attention away from the parts, those rusting holdovers from an earlier age of organization, and focus us on the deeper, embedded processes that create whole organizations. “What is needed,” writes Bohm, “is an act of understanding in which we see the totality as an actual process that, when carried out properly, tends to bring about a harmonious and orderly overall action . . . in which analysis into parts has no meaning” (1980, 56).

In quantum physics, relational holism describes how whole systems are created among the subatomic particles. In this process, the parts are forever changed, drawn together by a process of internal connectedness. Electrons are drawn into these intimate relations as their wave aspects interfere with one another, overlapping and merging; their own qualities of mass, charge, spin, position, and momentum become indistinguishable from one another. “The whole will, as a whole, possess a definite mass, charge, spin, and so on, but it is [119] completely indeterminate which constituent electrons are. contributing what to this. Indeed, it is no longer meaningful to talk of the constituent electrons’ individual properties, as these continually change to meet the requirements of the “whole” (Zohar 1990, 99).

This is an intriguing image for organizations. It is not difficult to recognize the waves we create in organizations, how we move, merging with others, forming new wholes, being forever changed in the process. We experience this when we say that a team has “jelled,” suddenly able to work in harmony, the ragged edges gone, a pleasurable flow to the work. We all have experienced things “coming together,” but it has always felt slightly miraculous. We never understood that we were participants in a universe that thrives on information and that will work with us in the creation of order.

Much of the present thinking about organizational design stresses fluid and permeable forms that can be resilient to unending change. These ideas have sparked both hesitation and curiosity. Perhaps if we understand the deep support we have from natural processes, it will help dispel some of the fear. It is not that we are moving toward disorder when we dissolve current structures and speak of worlds without boundaries. Rather, we are engaging in a fundamentally new relationship with order, order that is identified in processes that only temporarily manifest themselves in structures. Order itself is not rigid, but a dynamic energy swirling around us. Relational holism and self-organization work in tandem to give us the living universe. Two dynamic processes, fed by information, combine to create an ordered world. The result is evolution, the organization of information into new forms. Life goes on, richer, more creative than before.

[120]

CHAPTER 7

Chaos and the Strange Attractor of Meaning

 

“Thus before all else, there came into

being the Gaping Chasm, Chaos, but there

followed the broad-chested Earth, Gaia, the

forever-secure seat of the immortals . . .

and also Love, Eros, the most beautiful

of the immortal gods, he who breaks limbs.”

—Hesiod

 

Several thousand years ago, when primal forces haunted human imagination, great gods arose in myths to explain the creation of all beings. At the very beginning was chaos, the endless, yawning chasm devoid of form or fullness, and Gaia, the mother of the earth who brought forth form and stability. In Greek consciousness, Chaos and Gaia were partners, two primordial powers engaged in a duet of opposition and resonance, creating everything we know.

These two mythic figures again inhabit our imaginations and our science. They have taken on new life as scientists explore more deeply the workings of our universe. I find this return to mythic wisdom both intriguing and comforting. It signifies that a new relationship with Chaos is available, even in the midst of increasing turbulence. Like ancient Gaia, we need to appreciate the necessity for Chaos, understanding it as the life source of our creative power. From his great chasm comes support and opposition, creating the “light without which no form would be visible” (Bonnefoy 1991, 369-70). We, the generative force, give birth to form and meaning, dispelling Chaos with our creative expression. We fill the void with worlds of our creation and turn our backs on him. But we must remember, so the Greeks and our science tell us, that deep within our Gaian centers lives always the dark heart of Chaos.

The heart of chaos has been revealed with modern computers. Watching [122] chaos emerge on a computer screen is a mesmerizing experience. The computer tracks the evolution of a system, recording a moment in the system’s state as a point of light on the screen. With the speed typical of computers, we can soon observe millions of moments in the system’s history. The system careens back and forth with violent unpredictability, never showing up in the same spot twice. This chaotic movement is seen as rapidly moving lines zooming back and forth across the screen. But as we watch, the lines weave their strands into a pattern, and an order to this disorder emerges. The chaotic movements of the system have a shape. The shape is a “strange attractor,” and what has appeared on the screen is the order inherent in chaos (see illustration, page 79).

Chaos has always had a shape—a concept contradictory to our common definition of chaos—but until we could see it through the eyes of computers, we saw only turbulence, energy without predictable form or direction. Chaos is the final state in a system’s movement away from order. Not all systems move into chaos, but if a system is dislodged from its stable state, it moves first into a period of oscillation, swinging back and forth between different states. If it moves from this oscillation, the next state is full chaos, a period of total unpredictability. But in the realm of chaos, where everything should fall apart, the strange attractor comes into play. (Science uses other attractors. These particular ones were named strange by two scientists, David Ruelle and Floris Takens, who felt the name was deeply suggestive [Gleick 1987, 131]. As Ruelle said, “The name is beautiful and well-suited to these astonishing objects, of which we understand so little [in Coveney and Highfield 1990, 204].)

A strange attractor is a basin of attraction, an area displayed in computer-generated phase space that the system is magnetically drawn into, pulling the [123] system into a visible shape. Computer phase space is multi-dimensional, allowing scientists to see a system’s movement in more dimensions than had been possible previously. Shapes that were not visible in two dimensions now become apparent. In a chaotic system, scientists now can observe movements that, though random and unpredictable, never exceed finite boundaries. “Chaos,” says planning expert T. J. Cartwright, “is order without predictability” (1991, 44). The system has infinite possibilities, wandering wherever it pleases, sampling new configurations of itself. But its wandering and experimentation respect a boundary.

Ruelle, like many chaos scientists, reaches for poetic language to describe these strange attractors: “These systems of curves, these clouds of points, suggest sometimes fireworks or galaxies, sometimes strange and disquieting vegetal proliferations. A realm lies there of forms to explore, of harmonies to discover” (in Coveney and Highfield 1990; 206).

Briggs and Peat, in describing the computer images of systems wandering between orderly and chaotic states, paint a similarly compelling picture of this dance between turbulence and order:

Evidently familiar order and chaotic order are laminated like bands of intermittency. Wandering into certain bands, a system is extruded and bent back on itself as it iterates, dragged toward disintegration, transformation, and chaos. Inside other bands, systems cycle dynamically, maintaining their shapes for long periods of time. But eventually all orderly systems will feel the wild, seductive pull of the strange chaotic attractor. (1989, 76-77)

 

In much of new science, we are challenged by paradoxical concepts—matter [124] that is immaterial, disequilibrium that creates global equilibrium, and now chaos that is non-chaotic. Yet the paradox of chaos was known anciently, in its mythic pairing with order. In every system lurks the potential for chaos, “a creature slumbering deep inside the perfectly ordered system” (Briggs and Peat 1989, 62). But chaos, when it erupts, will never exceed the bounds of its strange attractor. This mirror world of order and disorder challenges us to look, once again, at the whole of the system. Only when we step back to observe the shape of things can we see the patterns of movement from chaos to order and from order to chaos. “Here,” recalls chaos scientist Doyne Farmer, “was one coin with two sides. Here was order, with randomness emerging, and then one step further away was randomness with its own underlying order” (in Gleick 1987, 252).

Chaos of this nature (known as deterministic chaos) is created by iterations in a non-linear system, information feeding back on itself and changing in the process. (This process of iteration also characterizes the self-organization observed in biological and chemical systems [see chapter 5].) Non-linearity has been described by Coveney and Highfield as “getting more than you bargained for” (1990, 184). Very slight variances in the conditions of the equation, variances so small as to be indiscernible, amplify into unpredictable results when they are fed back on themselves. If the system is non-linear, iterations can take the system in any direction, away from anything we might expect. The proverbial straw that broke the camel’s back is one familiar example of non-linearity: A very small change had an impact far beyond what could have been predicted.

Until recently, we discounted the effects of non-linearity, even though it abounds in life. We had been trained to believe that small differences averaged out, that slight variances converged toward a point, and that approximations [126] would give us a fairly accurate picture of what could happen. But chaos theory ended all that. In a dynamic, changing system, the slightest variation can have explosive results. Hypothetically, were we to create a difference in two values as small as rounding them off to the thirty-first decimal place (calculating numbers this large would require a computer of astronomical size), after only one hundred iterations the whole calculation would go askew. The paths of the two systems would have diverged in unpredictable ways. Even infinitesimal differences are far from inconsequential. “Chaos takes them,” physicist James Crutchfield says, “and blows them up in your face” (in Briggs and Peat 1989, 73).

Scientists now emphasize the very small differences at the beginning of a system’s evolution that make prediction impossible; this is termed “sensitive dependence on initial conditions.” Edward Lorenz, a meteorologist, first drew modern-day attention to this with his “butterfly effect.” (At the end of the nineteenth century, mathematician, physicist, and philosopher Henri Poincare had called attention to chaos in dynamic systems and its impact on prediction, but it was chaos science late in this century that revived his findings..) ‘Does the flap of a butterfly wing in Tokyo, Lorenz queried, affect a tornado in Texas (or a thunderstorm in New York)?” Though unfortunate for the future of accurate weather prediction, his answer was “yes.”

Science has been profoundly affected by this new relationship with the nonlinear character of our world. Many of the prevailing assumptions of scientific thought have had to be recanted. As the scientist Arthur Winfree expresses it:

The basic idea of Western science is that you don’t have to take into account the falling of a leaf on some planet in another galaxy when you’re trying [127] to account for the motion of a billiard ball on a pool table on earth. Very small influences can be neglected. There’s a convergence in the way things work, and arbitrarily small influences don’t blow up to have arbitrarily large effects. (In Gleick 1987, 15)

But chaos theory has proved these assumptions false. The world is far more sensitive than we had ever thought. We may harbor the hope that we will regain predictability as soon as we can learn how to account for all variables, but in fact no level of detail can ever satisfy this desire. Iteration creates powerful and unpredictable effects in non-linear systems. In complex ways that no model will ever capture, the system feeds back on itself, enfolding all that has happened, magnifying slight variances, encoding it in the system’s memory—and prohibiting prediction, ever.

Chaos theory is based on Newtonian mechanical principles, but in its unpredictability, it shares the uncertainty experienced at the quantum level. In both sciences, uncertainty arises because the wholeness of the universe resists being studied in pieces. Briggs and Peat, in their intriguing exploration of the mirror world of chaos and order, suggest that wholeness is “what rushes in under the guise of chaos whenever scientists try to separate and measure dynamical systems as if they were composed of parts .... The whole shape of things depends upon the minutest part. The part is the whole in this respect, for through the action of any part, the whole in the form of chaos or transformative a change a may manifest” (1987, 74-75). The strange attractors that form on our screens, Briggs and Peat suggest, are not the shape of chaos. They axe the shape of wholeness.

Iteration launches a system on a journey that visits both chaos and order. The [128] most beautiful images of iteration are found in the artistry of fractals, computer-generated models drawn by the iteration of a few equations (see also chapter 6). The equations change as they are fed back on themselves. After countless iterations, their tracks materialize into form, creating detailed shapes at finer and finer levels. Everywhere in this minutely detailed fractal landscape, there is self similarity. The shape we see at one magnification we will see at all others. No matter how deeply we look, peering down through very great magnifications, the same forms are evident. There is pattern within pattern within pattern. There is no end to them, no scale small enough that these intricate shapes cease to form. Because the formations go on forever, there is no way to ever gain a finite measurement of them. We could follow the outline of forms forever, and at ever smaller levels, there would always be something more to measure (see illustrations s, pages 80-81).

Fractals entered our world through the research of Benoit Mandelbrot of IBM. In discovering them, he gave us a language, a form of geometry, that allowed us to understand nature in new ways. Fractals are everywhere around us, in the patterns by which nature forms clouds, landscapes, circulatory systems, trees, and plants. We observe fractals daily, but until recently, we lacked a means for understanding them or how they were created.

Fractals, as common as they are, teach some new and important things. For example, it is impossible to ever know the precise measurement of a fractal. Mandelbrot’s seminal fractal exercise was a simple question posed to colleagues and students. “How long is the coast of Britain?” As his colleagues soon learned, there is no final answer to this question. The closer you zoom in on the coastline, the more there is to measure.

[129] Since there can be no definitive measurement, what is important in a fractal landscape is to note the quality of the system—its complexity and distinguishing shapes, and how it differs from other fractals. If we ignore these qualitative factors and focus on quantitative measures, we will always be frustrated by the factors incomplete and never-ending information we receive. Fractals, in stressing qualitative measurement, remind us of the lessons of wholeness we encountered in the systems realm. What we can know, and what is important to know, is the shape of the whole—how it develops and changes, or how it compares to another system.

In organizations, we are very good at measuring activity. In fact, that is primarily what we do. Fractals suggest the futility of searching for ever finer measures of discrete parts of the system. There is never a satisfying end to this reductionist search, never an end point where we finally know everything about even one part of the system. When we study the individual parts or try to understand the system through its quantities, we get lost in a world we can never fully measure nor appreciate. Scientists of chaos study shapes in motion; if we were to approach organizations in a similar way, what, would constitute the shape and motion of an organization?

We have started edging toward an answer to this question in our growing focus on studying organizations as whole systems rather than our old focus on discrete tasks. Organizations that are using complex system modeling (mentioned also in chapters 2 and 4) are experimenting with these skills. In other organizations, this newer awareness of dynamic shape may occur simply in how problems are approached. Is there an attempt to step back from the problem, to gain enough perspective so that its shape emerges out of the myriad variables that [130] influence it? Are people encouraged to look for themes and patterns, rather than isolated causes? Some of the analytic tools introduced in corporate quality programs, although relying initially on diverse and minute mathematical information, eventually prove effective because they allow people to appreciate the complex and ever-changing shape of the organization, and how multiple forces work together to form it.

Fractal principles have given us valuable insight into how nature creates the shapes we observe. Mountains, rivers, coastlines, vegetables, lungs, circulatory systems—all of these (and millions more) are fractal, replicating a dominant pattern at several smaller levels of scale (see illustrations, pages 80-81.) The scientist Michael Barnsley was intrigued to see if he could recreate the shapes of natural objects by deducing the initial equations that described their forms. He invented the “Chaos Game,” in which he decoded objects to derive the number rules that expressed certain global information about their shapes (his first attempt was with a fern). These numbers captured only essential information about the shape. They were surprisingly simple, devoid of the levels of precise prescriptive information we might expect. Barnsley then interjected randomness, setting the numbers loose to feed back on themselves. They were allowed to follow their own iterative wanderings, working at whatever scale they chose. With this approach, he successfully reproduced an entire computer garden of plant shapes.

His work with “random fractals” and the chaos game are very instructive. First, Barnsley shows us that predictability still exists. The shapes that he created are predictable, built into the numbers. But indeterminism (randomness) also plays a key role. It is randomness that leads to the creation of the pattern at [131] different levels of scale. The same shapes appear predictably everywhere with only simple levels of instruction and large amounts of freedom. It seems that with a few simple guidelines, left to develop and change randomly, nature creates the complexity and harmony of form we see everywhere.

Creating complexity from simplicity. Strange as it seems, the basic shape of a fern is captured in a simple stick drawing (top left). To make a fern of curving, intricate complexity, all that is required is this stick shape, or “seed,” and a few basic rules. The only rules are that the seed shape is free to repeat itself at many different levels of scale, that it is placed in an upright direction, and that it connects with what is already on the page. From this combination of a few simple rules and high levels of autonomy-of order and chaos working in tandem-emerges the beautiful complexity of a fern. (This process can be used to create other complex fractal objects, such as trees or intricate patterns, once the basic shape is abstracted.) Drawing used with permission, Linda Garcia, 1991 (in The Fractal Explorer, Dynamic Press, Santa Cruz, CA.)

 

Many disciplines have seized upon fractals, testing whether self—similar phenomena occur at different levels of scale in both natural and man-made [132] systems. For example, business forecasters and stock analysts have observed a fractal quality to stock market behaviors and have seen patterns that resemble one another in daily and monthly market fluctuations.

And I believe that fractals also have direct application for the leadership of organizations. The very best organizations have a fractal quality to them. An observer of such an organization can tell what the organization’s values and ways of doing business are by watching anyone, whether it be a production floor employee or a senior manager. There is a consistency and predictability to the quality of behavior. No matter where we look in these organizations; self—similarity is found in its people, in spite of the complex range of roles and levels.

How is this quality achieved? The potent force that shapes behavior in these fractal organizations, as in all natural systems, is the combination of simply expressed expectations of acceptable behavior and the freedom available to individuals to assert themselves in non-deterministic ways. Fractal organizations, though they may never have heard the word fractal, have learned to trust in natural organizing phenomena. They trust in the power of guiding principles or values, knowing that they are strong enough influencers of behavior to shape every employee into a desired representative of the organization. These organizations expect to see similar behaviors show up at every level in the organization because those behaviors were patterned into the organizing principles at the very start.

Fractals and strange attractors echo the principles evidenced in the globally stable, locally changing structures we observed in self-organizing systems. In both realms, whether it be a biological system or a mathematical rendering of a chaotic system, the structure is capable of maintaining its overall shape and a large degree [133] of independence from the environment because each part of the system is free to express itself within the context of that system. Fluctuations, randomness, and unpredictability at the local level, in the presence of guiding or self-referential principles, cohere over time into definite and predictable form. It was this odd combination of predictability and self-determination that attracted some early scientists of chaos. The science seemed to explain how free will could be expressed and have value in an orderly universe. “The system is deterministic, but you can’t say what it’s going to do next” (Gleick 1987, 251).

These ideas speak with a simple clarity to issues of effective leadership. They bring us back to the importance of simple governing principles: guiding visions, strong values, organizational beliefs—the few rules individuals can use to shape their own behavior. The leader’s task is to communicate them, to keep them ever-present and clear, and then allow individuals in the system their random, sometimes chaotic-looking meanderings.

This is no simple task. Anytime we see systems in apparent chaos our training urges us to interfere, to stabilize and shore things up. But if we can trust the workings of chaos, we will see that the dominant shape of our organizations can be maintained if we retain clarity about the purpose and direction of the organization. If we succeed in maintaining focus, rather than hands-on control, we also create the flexibility and responsiveness that every organization craves. What leaders are called upon to do in a chaotic world is to shape their organizations through concepts, not through elaborate rules or structures.

Ever since my imagination was captured by the phrase “strange attractor,” I have wondered if we could identify such a force in organizations. Is there a magnetic force, a basin for activity, so attractive that it pulls all behavior toward it [134] and creates coherence? My current belief is that we do have such attractors at work in organizations and that one of the most potent shapers of behavior in organizations, and in life, is meaning. Our main concern, writes Viktor Frankl in his presentation of logotherapy, “is not to gain pleasure or to avoid pain but rather to see a meaning in . . . life” (1959, 115).

I became aware of the call of meaning in our organizational lives when I worked with a number of incoherent companies that had been tipped into chaos by reorganizations or leveraged buyouts. They had lost any purpose beyond the basic struggle to survive. Yet under these circumstances, I saw some employees who continued to work hard and contribute to the organization even when the organization could offer them nothing, not even the promise of a job in the future. Most employees had, more predictably, checked out psychologically, just putting in their time, waiting for the inevitable. But others stayed creative and focused on creating new services, even with the great uncertainty of the future. This puzzled me greatly.

I assumed at first that they were simply denying reality. But when I talked to these employees, it became evident that something else much more important was going on. They were staying creative, making sense out of non-sense, because they had taken the time to create a meaning for their work, one that transcended present organizational circumstances. They wanted to hold onto motivation and direction in the midst of turbulence, and the only way they could do this was by investing the current situation with meaning. Frankl, in Man’s Search for Meaning, points out very clearly that meaning saved lives in the concentration camps of Germany. The one thing that can never be taken from us, he writes, is our attitude toward a situation. If we search to create meaning, we can survive and [135] even flourish. In chaotic organizations, I observed just such a phenomenon. Employees were wise enough to sense that personal meaning-making was their only route out of chaos. In some ways, the future of the organization became irrelevant. They held onto personal coherence because of the meaning attractor they created. Maybe the organization didn’t make sense, but their lives did.

I have also seen companies make deliberate use of meaning to move through times of traumatic change. I’ve seen leaders make great efforts to speak forthrightly and frequently to employees about current struggles, about the tough times that lie ahead, and about what they dream of for the future. These conversations fill a painful period with new purpose, giving reasons for the current need to sacrifice and hold on. In most cases, given this kind of meaningful information, workers respond with allegiance and energy.

All of us want so much to know the “why” of what is going on. (How often have you heard yourself or others say, “I just wish they would tell me why we’re doing this”?) We instinctively reach out to leaders who work with us on creating meaning. Those who give voice and form to our search for meaning, and who help us make our work purposeful, are leaders we cherish, and to whom we return gift for gift.

The formative powers of meaning echo back, at least in my own thinking, to a lesson I learned from self-organizing systems, where the principle of self-reference or self-consistency plays such a critical role. A self-organizing system has the freedom to grow and evolve, guided only by one rule: It must remain consistent with itself and its past. The presence of this guiding rule allows for both creativity and boundaries, for evolution and coherence, for determinism and free will.

[135] When I think about meaning as a strange attractor, I see links to these sciences. Meaning or purpose serves as a point of reference. As long as we keep purpose in focus in both our organizational and private lives, we are able to wander through the realms of chaos, make decisions about what actions will be consistent with our purpose, and emerge with a discernible pattern or shape, to our lives.

When a meaning attractor is in place in an organization, employees can be trusted to move freely, drawn in many directions by their energy and creativity. There is no need to insist, through regimentation or supervision, that any two individuals act in precisely the same way. We know they will be affected and shaped by the attractor, their behavior never going out of bounds. We trust that they will heed the call of the attractor and stay within its basin. We believe that little else is required except the cohering presence of a purpose, which gives people the capacity for self-reference.

The science of strange attractors can be linked back, in its images and teachings, to other sciences in many ways. Chaos theory, based on Newtonian mechanics and applicable to the world of large objects, conjures up visions of unseen forces that create order and manage coherence. The fields of quantum space speak of energy that takes form when two subatomic fields intersect. The fields of biological morphogenesis describe physical forms shaped by invisible geometries. It is important to keep the distinctions between these sciences clear (at least for now), but it is also important to note a resonant similarity. Each attempts to describe the presence of non-visible influences that facilitate orderly processes of creation and change.

In chaos theory it is axiomatic that you can never tell where the system is [137] headed until you’ve observed it over time. This is also true for organizations, and it is what makes trusting something as ethereal as a strange attractor difficult. It takes time to see if a meaning-rich organization really works. A few are already out there, bright beacons to the future. But if they have not been part of our own experience, we are back to acts of faith. As the universe keeps revealing more of these invisible allies, perhaps we will grow in the belief that systems can evolve into an orderly shape when they center around clear points of self-reference.

We can use our own lives as evidence for this because they evolve in just such a fashion. By the end of our lifetime, we are able to discern our individual basins of attraction. What has been the shape of our life? What has made seemingly random events now appear purposeful? What has made “chance” meetings fit smoothly into the movement of our lives? We discover that we have been influenced by a meaning that is wholly and uniquely our own. We experience a deeper knowledge of the purpose that structured all of our activities, many times invisibly and without our awareness. Whether we believe that we create this meaning in a retrospective attempt to make sense of our lives, or that we discover meaning as the preexistent creation of a purposeful universe, it is, at the end, only meaning that we seek. Nothing else is attractive, nothing else has the power to cohere an entire lifetime of activity. We become like ancient Gaia who boldly embraced the void, knowing that from Chaos’ dark depths she would always pull forth order.