CHAPTER 2
Models from Science and Nature
If we, on our most fundamental level, are packets of quantum energy constantly exchanging information with this heaving energy sea, it means that all of us connect with each other and the world at the level of the very undercoat of our being. It also means that we have the power to access much more information about the world than we realize.
The seemingly continuous creation, destruction, and evolution of organizational frameworks are best understood by exploring models in science and nature. When examining the underlying principles, there are many parallels to models in physics, biology (living systems, ecology, and evolution), and complexity theory. In an attempt to explain what we are experiencing—constant change, chaos, and unpredictability—the new scientific models challenge us to rethink how we view organizations and ourselves as leaders. “ ‘The New Science,’ a radical shift in our world view, is replacing the image of organizations as machines with a living systems model that offers awe, creativity, and greater cosmological connection.”1
QUANTUM PHYSICS
Quantum theory introduces yet another level of paradox into our search for order. At the quantum level we observe a world where change happens in jumps, beyond our powers of precise prediction. This world has also challenged our beliefs about objective measurement, for at the subatomic level the observer cannot observe anything without interfering or, more importantly, participating in its creation. The strange qualities of the quantum world, and especially its influence in shaking our beliefs in determinism, predictability, and control, don’t seem to offer any hope for a more orderly universe. But our inability to predict individual occurrences at the quantum level is not a result of the inherent disorder. Instead the results we observe speak to a level of quantum interconnectedness, of a deep order that we are only beginning to sense. There is a constant weaving of relationships, of energies that merge and change, of constant ripples that occur within a seamless fabric. There is so much order that our attempts to separate out discrete moments create the appearance of disorder.
Right now, scientists are debating two worldviews, one offered by classical physics and the other offered by quantum physics. Classical physics, based on Newton’s laws of gravity and motion, states that all objects move in three-dimensional space across the dimension of time. Matter is considered solid, with fixed boundaries. Heat, cold, and force from another object are the only influences that can affect change.
These theories form the basis of our philosophical view of the world—namely, that we live in a physical universe and things exist independently of each other. However, these theories began to unravel in the early twentieth century, when a few quantum physics pioneers were able to peek inside some of the tiniest bits of the universe. They discovered that subatomic particles were not solid and stable. In fact, they appeared to be tiny clouds of probability or simply potential of their future selves. They finally determined that a quantum particle was not just a particle, nor was it just a wave; it was both.
Quantum physics explores the world of the subatomic particles of light: atoms, electrons, photons, and protons. It also explores the larger world of lasers, neutron stars, and physical and biological systems. Max Planck (1858-1947) pioneered quantum theory in 1900 with the idea that energy exchange is “discrete,” that reality is composed of discrete “quanta.” This discreteness may not be visible to the naked eye, but it exists nonetheless.
The smallest unit of energy in a given subatomic event is called a quantum. Observations of subatomic particles reveal that energy moves from one orbit to another in “quantum leaps.” The distance they jump is determined by how much “quanta” (plural for quantum) of energy they contain. Later, these little packets of energy were called photons. Niels Bohr, Werner Heisenberg, Ernest Rutherford, and Erwin Schrodinger were a few of quantum physics’ pioneers. Albert Einstein also did much to pioneer the new science, although he had difficulty accepting quantum theory.
Physical science is based on a world made up of atoms. Atoms are very, very small—one breath contains about 1 million billion billion atoms. To understand this microscopic world, it is helpful to picture an atom as a minute solar system. There is a nucleus that is made up of protons and neutrons, and it is surrounded by electrons that orbit the nucleus in its stable position. Electrical forces bind the system together much like gravity binds our solar system together.
When atoms become unstable, for whatever reason, electrons move to different orbits. When an electron jumps to a different orbit, light is emitted with a certain frequency (which determines its color). Electrons interact by exchanging photons, which are particles of light. If an electron absorbs a photon, it gets an energy boost, which moves it to a new place. If it discharges a photon, it recoils, which also lands it in a new place. The movements that occur at the quantum level are random and unpredictable.2
The theories of Bohr, Heisenberg, and other quantum physicists completely contradicted the Newtonian view of matter as discrete, self-contained, and independent. In fact, they suggested that at its most fundamental level, matter cannot be separated into independent units, nor can it be independently observed. “Things had no meaning in isolation; they had meaning only in a web of dynamic interrelationships.”3
Another surprising and important discovery is the ability of quantum particles to influence each other, regardless of their position. If quantum particles were ever in contact with each other and then separated, they maintained influence on each other across vast distances. In fact, at a subatomic level they continue to exchange little packets of vibrating energy. “The universe was not a storehouse of static, separate objects, but a single organism of interconnected energy fields in a continuous state of becoming.”4
Experiments in the 1990s demonstrated that the amount of energy contained in a photon is uncertain, and this uncertainty allows it to pop in and out of existence. Photons and protons can collide in this state and create a rain of particles. So it appears that light shifts from matter and back to light, again demonstrating the both/and orientation. This actually follows relationship logic because light is both particles and waves, but it surely seems contrary and inconceivable from a rational, Newtonian, empirical point of view.
Another interesting observation of quantum systems shows us that electrons and photons shift as they interact with the environment. Experiments that dramatically demonstrate this are the famous two-slit experiments. These experiments are conducted by emitting photons from a precision light source. The photons are shot at a screen that has two slits in it, through which the photons travel. On the other side of the screen are measuring devices to observe the photons, either particle detectors or a wave detector. If particle detectors are used for observation, the photons travel through one of the slits. However, if the photons are measured collectively with a screen, the photons travel through both of the slits and are registered as waves.
Quantum experiments demonstrate the relationship between what is observed and the observer—that the presence of the researcher has an impact on the results of the experiment. Before the photons in the experiment are measured, they are neither waves nor particles, although they have the potential to be both. The way the experiment is set up (with devices that detect either particles or waves) calls forth either one response or the other. The response is based on the way that the experimenter decides to look at the experiment.
The results of these experiments, replicated over and over and in many different ways, indicate that electrons and photons interact constantly with their environment, changing as a result of this interaction with their surroundings. Subatomic particles have little meaning in isolation—they can be fully understood only as interconnections or correlations. The analogy is that, in the physical world, relationships determine who we are and interaction with others impacts our identity and our behavior.5
What brings energy into form, based on quantum physics, is the involvement of the observer. In her 2007 book, Lynn McTaggart recalls the results of an experiment, “The moment we looked at an electron or took a measurement, it appeared that we helped to determine its final state. This suggested that the most essential ingredient in creating our universe is the consciousness that observed it. Several of the central figures in quantum physics argued that the universe was democratic and participatory—a joint effort between the observer and observed.”6
For over 30 years, prestigious scientific institutions around the world have been proving that our thoughts have their own energy, with the power to influence our environment. In other words, our thoughts are capable of affecting everything from the simplest machines to the most complex living beings.
If the observer affects reality or what comes into form, this suggests that nothing in the universe exists independent of our perception. It suggests that our very consciousness creates our reality. This concept presents a conundrum for mainstream scientists whose current scientific view of consciousness, based on the theories of seventeenth-century philosopher René Descartes, is that mind is separate and different from matter and that our consciousness is limited to the physical brain. However, quantum theory is mathematically verifiable. And it is very successful at explaining the subatomic world. It is the basis for the atom bomb and lasers, which makes it hard to ignore. But because its implications are unsettling at a larger level, mainstream scientists have generally ignored quantum physics as it relates to our perception of the world.
Quantum Organizations
In the quantum world, there is a question of whether there is more influence from the system or the individual. According to Wheatley’s interpretation of the quantum world, the answer is “It depends.” This speaks to the fluctuating nature of this new paradigm. “What is critical is the relationship created between the person and the setting. That relationship will always be different, will always evoke different potentialities. It all depends on the players and the moment.”7
This concept has powerful implications for how we structure and run our businesses. If the focus of a business is manufacturing with stable production cycles and markets, then control is advantageous if not essential. However, in most Business Intelligence (BI)-intensive companies, the organizational structures are based on ever-changing products and markets. Instead of seeking control, adaptability becomes essential. If the company adopts a top-down, Newtonian style of management in all arenas, it cannot adapt quickly enough to changes in the market.
However, to see organizations from a quantum viewpoint, it is clear that new models, skills, and competencies are needed. Rather than telling people what to do, management will need to clearly communicate the purpose of the business and facilitate processes to achieve that purpose. Management will accomplish this through interactions via strong relationships. Each group or team will become its own entity as it creates a strategy to work toward the goal. The team, the department, the individual will reach its goals by birthing ideas, nurturing these ideas, and watching them grow. The loner or rugged individual will not have the same role in this new model. Instead, he or she will act like an unstable particle that destabilizes the structure for a while. The new energy this creates will stimulate innovation and the need for the reevaluation of many assumptions. At this point, the need for clarity of language and effective facilitation are paramount.
Relationships fuel the energy of the organization. These relationships are enabled through face-to-face contact as well as phone and Internet. However, with or without being conscious of it, employees have a relationship through the quantum field. If organizational leaders understand this fact and create an environment of connection and focus, the interconnectedness can be leveraged in very positive ways. These concepts are developed more thoroughly in Part Two.
EVOLUTIONARY BIOLOGY AND LIVING SYSTEMS
Nature gives us a perfect model of a living system that is constantly evolving and adapting. Every part is interconnected. There is no central control. Power is dispersed throughout the system, which gives it resiliency and flexibility. As a connected system, it easily adapts to change.
Organizations have this same capacity. Understanding what is possible gives rise to amazing potential.
Hive Mind
As we seek to understand how people connect within organizations, we find evidence of the quantum field in nature. Consider what biologists call “hive mind.” It describes the seemingly invisible interconnectedness of a swarm of bees. It also explains how a flock of birds can fly in perfect formation or a school of fish can turn at once as if following an external cue. This excerpt from Kevin Kelly’s Out of Control describes an experience of 20,000 people connecting through hive mind.
In a darkened Las Vegas conference room, a cheering audience waves cardboard wands in the air. Each one is red on one side, green on the other. Far in back of the huge auditorium, a camera scans the frantic attendees. The video camera links the color spots of the wands to a nest of computers set up by graphics wizard Loren Carpenter. Carpenter’s custom software locates each red and each green wand in the auditorium. Tonight there was just shy of 5,000 wandwavers. The computer displays the precise location of each wand (and its color) onto an immense, detailed video map of the auditorium hung on the front stage, which all can see. More importantly, the computer counts the total red or green wands and uses that value to control software. As the audience waves the wands, the display screen shows a sea of lights dancing crazily in the dark, like a candlelight parade gone punk. The viewers see themselves on the map: they are either a red or green pixel. By flipping their own wands, they can change the color of their projected pixels instantly.
Loren Carpenter boots up the ancient video game of Pong onto the immense screen. Pong was the first commercial video game to reach pop consciousness. It’s a minimalist arrangement: a white dot bounces inside a square: two movable rectangles on each side act as virtual paddles. In short, electronic ping-pong. In this version, displaying the red side of your wand moves the paddle up. Green moves it down. More precisely, the Pong paddle moves as the average number of red wands in the auditorium increases or decreases. Your wand is just one vote.
Carpenter doesn’t need to explain very much. Every attendee at this 1991 conference of computer graphic experts was probably once hooked on Pong. His amplified voice booms in the hall, “Okay guys. Folks on the left side of the auditorium control the left paddle. Folks on the right side control the right paddle. If you think you are on the left, then you really are. Okay Go!”
The audience roars in delight. Without a moment’s hesitation, 5,000 people are playing a reasonably good game of Pong. Each move of the paddles is the average of several thousand players’ intentions. The sensation is unnerving. The paddle usually does what you intend, but not always. When it doesn’t you find yourself spending as much attention trying to anticipate the paddle as the incoming ball. One is definitely aware of another intelligence online: it’s this hollering mob.
The group mind plays Pong so well that Carpenter decides to up the ante. Without warning the ball bounces faster. The participants squeal in unison. In a second or two, the mob has adjusted to the quicker pace and is playing better than before. Carpenter speeds up the game further; the mob learns instantly.
Kelly goes on to describe the audience’s experience with forming numbers as well as flying, rolling, and landing a jet. He then relates it to nature:
The conferences did what birds do: they flocked. But they flocked self-consciously. They responded to an overview of themselves as they co-formed a “5” or steered the jet. A bird on the fly, however, has no overarching concept of the shape of its flock. “Flockness” emerges from creatures completely oblivious of their collective shape, size, or alignment. A flocking bird is blind to the grace and cohesiveness of a flock in flight.8
In almost all organizations, the power of this interconnectedness is a huge untapped resource. Interconnectedness may be a function of the age of the company or a result of many years of consistent teams. With today’s changing workforce, it is even more imperative that companies are conscious of this interconnectedness and know how to leverage it.
Collective Wisdom
Another benefit of this interconnectedness is the ability of a group to unveil the truth. Considerable research shows how groups of people, when asked a question, often get the wrong answer a majority of the time. But many times the average of the answers is very close to the truth. Interest in this research emerged as a result of an innocent experiment by an arrogant scientist.
In 1906, the British scientist Francis Galton set out to a country fair to gather data for his research. He had dedicated his life to two areas: the measurement of physical and mental qualities, and breeding. His interest was driven by his opinion that very few people had the intelligence and wisdom to keep societies healthy. His extensive experiments left him believing in “the stupidity and wrong-headedness of many men and women being so great as to be scarcely credible.”9
While strolling around the fair, Galton came across a competition: Pay a small fee, guess the weight of an ox, and win prizes. Based on his evaluation of the crowd, Galton surmised that the average of the guesses would be way off. To verify his hypothesis, Galton borrowed the tickets from the organizer and ran a series of statistical tests. The average weight determined by 787 guesses came to 1,197. The correct weight was 1,198. Galton writes later, “The result seems more creditable to the trustworthiness of a democratic judgment than might have been expected.”10
Translate this to tasks within an organization. Based on this theory, employees could predict the number of widgets their company is going to sell in the next year. Or the probability that a drug will be approved by the Food and Drug Administration. Or the amount of total sales a team will bring in over the next year. Companies that solicit feedback are tapping into a wealth of knowledge, not just from each individual but from the collective wisdom.
Our Evolving Brain
Many of the stresses we experience in our lives come from a gap between what our culture requires of us and the structure of our brain. Our brain’s structure has stayed the same for 50,000 years, while the number of tasks we must do in a day, the number of social interactions we experience, and the amount of information we must process has increased exponentially. Cultural evolution is much faster than biological evolution.
The human brain is one of the most complex, if not the most complex, entity in the universe. “The typical brain consists of some 100 billion cells, each of which connects and communicates with up to 10,000 of its colleagues. Together they forge an elaborate network of some one quadrillion (1,000,000,000,000,000) connections that guides how we talk, eat, breathe, and move.”11
The National Institutes of Health declared the 1990s to be the decade of the brain. The first half of the twenty-first century is the age of brain-mind science.12
It is common knowledge that the brain has two hemispheres. For many years, scientists believed that the left brain—the rational, analytical, and logical half—set humans apart from animals because it contains the language center. The right brain, characterized as mute, instinctual, and nonlinear, was considered something that humans no longer needed.
In the 1950s, a Caltech professor named Roger W. Sperry unveiled that in fact the right brain was “the superior cerebral member when it came to performing certain kinds of mental tasks. . . . There appear to be two modes of thinking represented rather separately in the left and right hemispheres, respectively.”13 The left brain functions sequentially and excels at analysis. The right brain operates holistically, reads emotions, and recognizes patterns. Based on more recent research and the experience of Dr. Jill Bolte Taylor, a neuroanatomist, the right brain may be what allows us to access more expansive thinking or hive mind.14
The effective use of both hemispheres is necessary to survive in our rapidly evolving business landscape. The ability to quickly make good decisions is a competitive advantage. This ability taps into what researchers call the “adaptive unconscious.” It is like a giant computer that integrates a lot of data very quickly. The adaptive unconscious has allowed us to survive as a species. And now it can be leveraged for organizational survival.15
The frontal lobes, a more recent evolutionary addition, are considered to hold the chief executive position in the brain. “As the seat of intentionality, foresight, and planning, the frontal lobes are the most uniquely ‘human’ of all the components of the human brain.”16
Most recently, the frontal lobes have been the subject of intense scientific research. While much of the functioning is still unexplained, it has been determined that “the prefrontal cortex plays a central role in forming goals and objectives and then in devising plans of action required to implement the plans, coordinate these skills, and applies them in a correct order. Finally, the prefrontal cortex is responsible for evaluating our actions as success or failure relative to our intentions.”17
The frontal lobes have great cognitive power that allows humans to look to the future and be proactive. This power gives humans the ability to seek goals, make plans, dream—basically conjure up and manipulate models to represent and predict the future. “[T]he generative power of language to create new constructs may depend on this ability as well. The ability to manipulate and recombine internal representations critically depends on the prefrontal cortex, and the emergence of this ability parallels the evolution of the frontal lobes. If there is such a thing as ‘the language instinct’ it may be related to the emergence, late in evolution, of the functional properties of the frontal lobes.”18
More insights into the brain are discussed in Chapter 5.
COMPLEXITY SCIENCE AND CHAOS
Our global ecosystem is a superb example of a highly adaptable evolutionary system.
Order arises spontaneously all the time from complex, irregular, and chaotic states of matter. It is no accident that the chaos of the Big Bang evolved into atoms, molecules, elements, stars, and galaxies; it is no accident that life eventually organized into cells, tissues, organs, organisms, species, and ecological communities. A defining feature of complexity is that order arises naturally from the evolution of vast aggregates of simple subunits.19
Evolution is a process that is both open and decentralized. Our ecosystem is always importing energy from the environment and exporting entropy (the inverse of a system’s ability to change).
Open systems, which receive energy from the outside, tend to produce order, not disorder; they self-organize. Interactions among a collection of objects tend to produce aggregates that have stable spatial patterns or temporal rhythms. Higher-order behaviors emerge from the interactions of many simple components, and they do so without a central controller. No agent does the organizing; structure arises even though none of the interacting units has a plan or a goal for how the overall system should behave.20
In order to remain viable and strong, our ecosystem does not seek equilibrium, which is, by definition, a state that leads to contraction and eventual death. “In classical thermodynamics, equilibrium is the end state in the evolution of isolated systems, the point at which the system has exhausted all of its capacity for change, done its work, and dissipated its productive capacity into useless entropy.”21
As in any complex system, our ecosystem organizes through the interaction of nonlinear components that lead to positive feedback loops. Some interactions are reinforced while others die off. Even the smallest change, through this continuous feedback, can have a huge effect on the entire system.
While these changes seem random and unpredictable, the shape of their movement is finite. It is determined by what scientists call “attractors,” forces that exert a magnetic pull.22
There is no overall plan for how the process should execute. The resulting pattern is designed or controlled without any central organizing agent. In this open, viable system, the value of resiliency replaces the value of stability. Within complex systems, natural selection gives rise to both fitness and adaptability. By staying out of balance or on the edge of chaos, our ecosystem is able to continuously adapt and evolve.
Chaos Theory
Chaos theory, or dynamic systems theory, grew out of the fields of mathematics and physics over the last several decades. It is a body of knowledge generated by the understanding of many disciplines and their connectedness. Chaos theory created a revolution in the scientific world, because it impacts anyone interested in science and natural systems. It created a shift in emphasis from the quantitative with an emphasis on mechanistic structures to the qualitative, where relationships and patterns are observed. With the discovery of the chaos theory, scientists from different specialties, such as physics and mathematics, who often preferred to work separately, began to exchange information. Eventually, scientists from many other disciplines, including biology, chemistry, ecology, economics, and astronomy, contributed to the understanding of chaos.
One of the initial contributors to the chaos theory was a meteorologist and mathematician named Edward Lorenz. The “Lorenz attractor,” discovered in 1961, was the result of a data entry error. While entering a relatively long number into the computer, Lorenz left a few digits off, set the computer to print, and left the room. He assumed that their absence would be so insignificant that they would barely impact the results. He was wrong, and that mistake led him to the discovery of infinitely complex patterns that never exactly repeat themselves, but that stay within very clear boundaries and create a distinct pattern. These Lorenz attractors were later called strange attractors.
The picture of the Lorenz attractor printed by the computer looked like the wings of a butterfly, thus the term the “butterfly effect.” The butterfly effect means that small initial deviations or changes (e.g., Lorenz leaving off the last few digits in his number) have substantial impact on a system. In terms of the weather, the draft created by the wings of a butterfly in the United States could create a hurricane in Japan, and it is why Lorenz said that it would be impossible to predict the weather. The discovery of Lorenz attractors was the beginning of the chaos theory, which emerged as a new science in the 1970s.23
Two different but enlightening definitions of chaos are “The qualitative study of unstable periodic behavior in deterministic nonlinear dynamical systems,”24 and “behavior that produces information (amplifies small uncertainties) but is not utterly unpredictable.”25
The theory of chaos resulted from the study of nonlinear systems. A “system” is a collection of processes or objects that has a figurative framework drawn around it for the purpose of study.26 A system could be one person, it could the population of birds in a given area, it could be a cell under a microscope, it could be the sun and the planets, or it could be an organization. “Nonlinear” systems express relationships that are not exclusively uniform.
Nonlinearity means rules are not constant—there are many dimensions to nonlinearity. Systems are unpredictable, and the smallest variation can create large changes (the butterfly effect). Most systems in nature are nonlinear. A system is a model that depicts behavior over time using mathematical formulas. The application of chaos theory in organizations is the study of complex, unpredictable systems that, in spite of their apparent random nature, exhibit predictable patterns over time.
Universality: Order Out of Chaos
Through the study of numerical functions, the particle physicist Mitchell Jay Feigenbaum discovered a theory that shook the foundations of science for many practitioners: a “universal” theory. He discovered that when observing nonlinear systems, different systems may appear similar if they are examined in a certain way. This phenomenon is known as Universality. With the aid of computers that can quickly track a system’s evolution, natural systems can be simulated to unveil their patterns and relationships. When observed over time, seemingly random movements in a system can display incredibly structured patterns. Systems are “universal” because of the common nature of these patterns. Examples of universality are ant colonies, swinging pendulums, and dripping faucets; they all have predictable qualities that create certain patterns called “strange attractors.”
Strange attractors pull a system into visible shape once it has begun to move into a state of chaos. These strange attractors have been discovered by tracking systems on computers. Attractors occur in “phase space,” a space in which all possible states of a system are represented. In phase space, a computer creates a multidimensional map of the history of a system by plotting points that represent the long-term behavior of the system. Movement in phase space converges on a set of points, making a strange attractor visible. Pictures of attractors in phase space show us that chaos does not move outside the bounds of the strange attractor, and the attractors create order from turbulence. (See Exhibit 2.1.) Strange attractors are described by a few simple mathematical equations, although they depict complex and random behavior. Even data from a dripping faucet produces patterns that indicate the presence of strange attractors creating order from the random disorder of the real data.
As a system interacts with its environment, it shifts and moves into disorder; it becomes chaotic, existing far from equilibrium although within certain boundaries. In this place it generates information, and if effective feedback loops exist, new forms of order emerge. Information is a source of order. Order is inherent in living systems, and rises naturally from chaos. Natural systems are self-organizing—they transform chaos into ordered, dynamic patterns. Chaos is, therefore, a necessary part of change for systems. Healthy systems maintain a balance between chaos and a lack of it. They are most efficient when they are poised at the edge of chaos, between disorder and stability. Too much disorder, and the system is torn apart; too much order, and the system dissipates or is diffused.
EXHIBIT 2.1 STRANGE ATTRACTOR
Source: www.turnex.dk
Barbara Mossberg, president of Goddard College, believes that “Chaos Theory applied regularly serves to keep chaos at bay.” She says, “The theory’s premise is that even when things seem out of control, if you step back far enough in space or time, there is order.”27
Certain characteristics of chaos are useful to keep in mind:
• As energy, positive or negative, enters the system, there is a temporary destabilization. It is best to act quickly and often.
• Control works only in the short term. Stability emerges over time.
• Every component of the system, no matter how small, plays a role. Diversity feeds long-term stability. Connection and inclusion facilitate cohesion.
• A holistic view of the system is necessary to provide guidance to the system. The integrity of the system is “the congruent harmony of parts working together in a state of aligned action.”28
Complexity science offers a theoretical framework for research into fundamental questions about living and working within adaptable, changeable systems. Viewing the organization through the lens of complexity science and chaos theory can shed light on behaviors that undermine resilience. Leaders who view their organizations as complex adaptive systems will build adaptability and resilience. Tools, techniques, and practices for facilitating this approach are discussed in Part Two.
The Chaordic Age
Consider the characteristics and capabilities of a company built using an evolutionary model that surfed the tension between chaos and order. Visa International
espouses no political, economic, social or legal theory, thus transcending language, custom, politics and culture to successfully connect a bewildering variety of more than 21,000 financial institutions, 16 million merchants and 800 million people in 300 countries and territories. Annual volume of $1.4 trillion continues to grow in excess of twenty percent compounded annual. A staff of about three thousand people scattered in twenty-one offices in thirteen countries on four continents provides . . . around-the-clock operation of two global electronic communication systems with thousands of data centers communicating through nine million miles of fiber-optic cable. Its electronic systems clear more transactions in one week than the Federal Reserve System does in one year.29
Dee Hock, the founder of Visa International, built his company using the principles of chaos theory without even knowing it. After years of success, he retired to his ranch. Many years later, he was reading Mitch Waldrop’s Complexity and realized that the process he used to build his company were the very principles described in the book. In the late 1990s, he wrote Birth of the Chaordic Age.
Hock coined the term “chaordic” to represent the dynamic tension between chaos and order. A chaordic organization can be described as
a self-organizing and self-evolving entity, which ends up looking more like a neural network (like the Internet) than a hierarchically-organized bureaucracy in which decision-making power is centralized at the top and trickles down through a series of well-regulated departments and managers. Chaordic organizations do not fear change or innovation. They are, by their very nature, supremely adaptive. They also tend to be inclusive, multicentric, and distributive and, ultimately, strongly cohesive due to their unshakable focus on common purpose and core principles.30
SYSTEMS THEORY AND SYSTEMS THINKING
Systems theory is an interdisciplinary field of science and the study of complex systems in nature, society, and science. Systems thinking is the application of systems theory, or “a discipline for seeing wholes.”31 The inherent variability within the system provides an opportunity for it to be seen as a collection of parts (or subsystems) that are highly integrated to accomplish an overall goal.
Systems Thinking for Business Intelligence
Adaptability and resilience are crucial competencies for thriving in a dynamic global economy. Applying the new science principles to organizations with a focus on Business Intelligence provides a powerful framework for building adaptability. Because complex systems are so highly dependent on the flow of information, knowledge-driven organizations are uniquely poised to leverage the benefits of systems thinking. “In the new science, the notion of information is intimately linked with the degree of complexity of a system.”32
In an article on the Business Intelligence Network, an online journal that covers all aspects of business intelligence, business analytics expert Dave Wells makes this observation:
Many of today’s Business Intelligence programs focus intensely on analytics. The business wants scorecards, dashboards and analytic applications, and the technology to deliver them is mature. Still we struggle to deliver high-impact analytics that are purposeful, insightful and actionable. The key to high-impact analytics is a strong connection with cause and effect—the essence of understanding why and deciding what next. Systems thinking offers the cause-and-effect connection. It holds the key to real analytic value that is derived through insight, understanding, reasoning, forecasting, innovation and learning.33
To embrace systems thinking, knowledge-based organizations must become proficient at skills and support infrastructures that build connections, foster innovation and collaboration, improve clarity, ensure adaptability, and allow self-organization to emerge. Part Two delves into these essential competencies, or “success factors,” as they relate to knowledge-based organizations. Chapter 8 expands on systems thinking and its uses in business analytics.
NOTES
1 Carol S. Pearson, Cover, InnerEdge 1, No. 4 (October/November 1998), 1.
2 Julie Roberts, Ph.D., “Leading with Heart and Soul,” manuscript, 5.
3 Lynn McTaggart, The Intention Experiment (New York: Free Press, 2007), xix.
4 Id.,
5 Roberts, “Leading with Heart and Soul,” 6.
6 McTaggart, The Intention Experiment, xx.
7 Id., 34.
8 Kevin Kelly, Out of Control, (Reading, MA: Addison-Wesley, 1994), 8-10.
9 James Surowiecki, The Wisdom of Crowds (New York: Doubleday, 2004), xi.
10 Id., xii-xiii.
11 Daniel Pink, A Whole New Mind (New York: Riverhead Books, 2005), 13.
12 Elkhonon Goldberg, The Executive Brain (Oxford: Oxford University Press, 2001).
13 Quoted in Pink, A Whole New Mind, 14.
15 Malcolm Gladwell, Blink (New York: Little, Brown, 2005), 11.
16 Elkhonon, The Executive Brain, 23.
17 Id., 24.
18 Id., 25.
19 Philip Anderson, “Seven Levers for Guiding the Evolving Enterprise,” in The Biology of Business, ed. John Henry Kipplinger III (San Francisco: Jossey-Bass, 1999), 117-118.
20 Id., 118.
21 Margaret Wheatley, Leadership and the New Science (San Francisco: Barrett Koehler, 1992), 76.
22 Thomas L. Guarriello, “Emergence of a Living Systems-Inspired Organizational Culture,” InnerEdge 1, No. 4 (October/November 1998), 16.
23 James Gleik, Chaos: Making a New Science (New York: Penguin Books, 1987).
24 Stephen H. Kellert, In the Wake of Chaos (Chicago: University of Chicago Press, 1993).
25 Gleik, Chaos.
26 Kellert, In the Wake of Chaos.
27 Barbara Mossberg, Why I Wouldn’t Leave Home Without Chaos Theory, InnerEdge 1, No. 4 (October/November 1998), 5.
28 Jalma Marcus, personal communication.
29 Dee Hock, “Transformation by Design,” What Is Enlightenment, No. 22 (Fall/ Winter 2002), 130.
30 Id.
31 Peter M. Senge, The Fifth Discipline (New York: Currency, 1990), 68.
32 Christopher Laszlo and Jean-François Laugel, Large-Scale Organizational Change (Boston: Butterworth Heinemann, 2000), 131.
33 Dave Wells, “A Systems View of Business Analytics, Part 1,” 2008, www.b-eye-network.com/view/8143.
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