The work intends that the professors of managerial theory in the universities and the leaders of the organizations of the countries of the region are interested in enriching the administrative sciences with contributions from the complexity theory. In this sense, the main concepts and principles of the theory of chaos and complexity are raised. It is not a question of giving a lecture on these theories, but rather initial ideas, raised in draft, should be considered. The task is not easy, one risks being called utopian, although this qualifier is not offensive. What would science and world be like if utopia didn't exist? Utopia is a force that makes creativity possible.
But, my presence at this forum is not to teach about these theories or to disregard the traditional principles of the Administration; my purpose is also to learn from this exchange. The teachings of the classics and some modern writers work for simple realities; however, today's world is very complex and simplicity is the exception. Business reality is a space where there are many worlds and each world responds to different and contradictory logics. For this reason, the administrative sciences are privileged with complexity, in which the knowledge of the infinitely small forms a unity with the knowledge of the infinitely large.
It has been tried, as much as possible, to describe the principles that characterize complex thinking and at the same time refer it to the field of Administration. Thus, the key concepts are described, such as chaos, attractors, determinism, predictability, the principles of the excluded and included third party, uncertainty, complementarity, transdisciplinarity, interaction, resonance, emergence, dialogic and others. Finally, some conclusions derived from complex thinking are presented.
Introduction
The work is presented within the framework of the IX General Assembly of the Latin American Association of Faculties and Schools of Accounting and Administration, to be held in Havana, Cuba, in September 2005. These events are spaces for reflection and analysis on the theoretical problem and practice of administrative and accounting sciences; For this reason, they are very important for the development of science in general, particularly the sciences that define the content of this assembly. The objective is to sensitize managers and professors of universities in our countries to abandon the old business paradigms at once and decide to dive into the deep waters of complexity. It is time for university professors of management theory to equip ourselves with new thinking for a new reality.An opportunity is these discussion dialogues to expose our ideas and enrich management theory.
An approach to the problem
The organizations and individuals that make it up have been the object of study from different approaches to science. Thus, we find works carried out under the sociological, psychological, anthropological perspective, etc.
These works respond to other cultures and other realities very different from those of our countries, whose rulers and political leaders show little concern for the advancement of science; Therefore, the investigations that are carried out lack the scientific rigor to be considered serious and credible studies and, therefore, offer little contribution to the investigative process in management sciences.
In our universities, scientific research, in general, does not have the importance and support that academic institutions in developed countries have, and social sciences, even less.
The budgets allocated by governments to state universities, in many cases, are insignificant in relation to GDP; Perhaps it is the product of ignorance of the importance of research or, perhaps, it is due to the fact that research is a powerful instrument for the integral development of countries and individuals and this causes some fear in governments and in the great world powers that view, with suspicion, the development of the so-called third world countries.
The few studies that are carried out on managerial theory, in less developed countries, to use a less cruel term, are very weak from a scientific point of view and are dedicated to repeating, and sometimes badly, what other researchers from other latitudes they have said about traditional aspects of the Administration; therefore, its results are not very new.
The method applied in these works is far from being scientific. It is an offense to the scientific method and mentality.
Many research papers have this weakness; but, in the works referring to managerial theory, this weakness is deeper. Perhaps, if there were a Nobel Prize in Administration, things would change; But something will have to be done, even without a Nobel Prize, for our benefit and that of humanity. It seems to me that it is time that we look at management theory with new eyes, with another perspective, with the principles of the complexity paradigm.
That is precisely my goal, to raise some very preliminary ideas about this approach that provoke debate, to apply a shake-up in the traditional management theory that we learned in universities, in such a way as to shake the tree with force so that the dry leaves fall that add little to the vitality of the tree.
In this sense, I have tried to offer some kind of answers to the following questions: What is complexity theory? What are its main postulates? What is the level of application to the Social Sciences and, especially, to managerial theory? The proposed responses should be considered as initial proposals, placed in draft for debate.
These and other questions that are generated in the development of this work constitute the central object of study. Due to the nature of this work, it was not possible to answer in depth the previous questions; however, I hope that I have achieved such a scope that the ideas presented here motivate the professionals of our universities to continue debating and developing this interesting topic.
The manager is a privileged being of complexity and chaos. The world in which the Administrator has to act is one of the most paradoxical: the company. A world where there are workers, each with their own world and with different logics: the logic of the world of the operator is not the logic of the world of the employer.
The company is a set of parallel worlds that respond to actions with different logics, characterized by the existence of uncertainty, complexity, ambiguity and chaos. To understand this logic, if there is one (at least as it is traditionally understood), it is necessary to change our way of thinking about life and the world, change the current paradigms for other more totalizing, more complementary ones. What are the basic concepts of the emerging paradigm that will change our worldview? On this occasion, the paradigm that I am going to refer to later is represented by the Complexity Theory and the Chaos Theory.
Offering answers, even initial ones, to the questions raised above is not an easy task. To do so, we also have to answer another question: What is reality? And, so far, no one has been able to define the concept of reality. There are as many conceptions of it as authors have tried to define it. Nobody knows what reality is. What we have are perceptions of reality; but they are just that: perceptions. These perceptions are contained in the models or theories that try to explain reality. For many researchers, model building is very similar to the anecdote of three blind men trying to describe an elephant. The first blind man touched the tail and concluded that the elephant is like a rope.
The second touched the elephant's leg and said it was a tree. Finally, the third blind man touched his trunk and claimed that the elephant was a snake. Each blind man placed himself in a different perspective and created a different explanation of the elephant.
What lesson does the previous anecdote leave us? That reality is very elusive and that we can never know the absolute and total reality.
The most we can do is approach it by successive approximations, knowing that the next step is closer to it than the previous one; but, it will always be an approximate truth, since it is in permanent change. The situation is similar to that person who wants to reach the rainbow, no matter how much he approaches to touch it, he will never achieve it. Furthermore, how we observe and how we interpret reality will depend on what theoretical approach we are using to observe it.
Objective reality - says Heisenberg - has evaporated and what we observe is not nature itself but nature exposed to our interrogation method ”(cited by Raiza Andrade and Cadenas, Evelin et al., 2002).
A brief review of the Theories of Chaos and Complexity
There is a discussion about the meaning and scope of the terms chaos and complexity. Many argue that Chaos Theory studies nonlinear dynamics and that Complexity Theory is part of it.
Others, for their part, maintain the opposite, and there are others who see small differences between the two. Some even maintain that both theories are two sides of the same coin and that the term complexity is, sometimes, interchangeable with chaos; but, that the former is used to refer to irregularities in space, while chaos refers to irregularities in time.
Russ Marion (1999, 5) is of the idea that, although complexity presents characteristics of chaos, it is different from it. The two concepts share the characteristic of non-linearity; but, they represent different phenomena. Theorists maintain that the dynamics of both theories go beyond "if A, then B", relationships in which the outputs are a simple function of the inputs. They argue that the behavior of the system is the result of complex, non-linear interactions between its constituent parts and that, due to non-linearity, it is difficult or impossible to predict the behavior of the system.
The characteristic of non-linearity, a key concept in Chaos Theory and Complexity Theory, means that the effect is disconnected from the cause; that is, a change in a causal variable does not necessarily generate a proportional change in the affected variable. Rather, the following situations can happen: there is no answer; that there is a dramatic response or that there is a response at certain levels of the cause.
Consider, for example, the behavior of a worker and a superior in an organization and assume, for the moment, that the emotions they experience are only anger and fear. When the boss approaches the worker to reprimand him, the two may experience anger and argue heatedly. A simple model of causality could predict that the anger of each one could increase in proportion to the degree of intensity of the discussion.
Nonlinearity theorists argue that the discussion is not a known answer; Rather, when the situation reaches a certain level of intensity, the emotional state of one of them can suddenly turn into fear, submit and withdraw.
Discuss or withdraw: the result has a sensitive dependence on the precise state of the emotions of each one of them, on the subtle nuances of the interaction between them and between each individual and among other things.
Chaos Theory
Chaos Theory, also known as the theory of dissipative structures, refers to certain mathematical models and their applications. He argues that the development of the phenomena of the universe does not follow a predictable and determined behavior, like that of a clock, but rather presents chaotic aspects; but, that this unpredictability or instability are not the product of the observer's ignorance, rather, they are an inherent characteristic of reality itself.
A characteristic of chaos is its sensitive dependence on initial conditions; This means that reality depends on many uncertain factors: a chaotic system, which starts from two very similar initial states, can have completely different results.
This sensitive dependence is known as the butterfly effect. Very small changes, in initial conditions, can have huge effects unpredictable by later events, leading some chaology theorists to claim that any prediction would be useless.
We will see, later, to what extent this is true. But, this is not new. Decision theory presents us with the enormous consequences of a decision that can change the history of an organization in a totally unpredictable way. What is the radical departure of chaos theory from the traditional idea that micro-changes can produce unpredictable macro-effects?
Chaos Theory, by its nature, uses a deterministic mathematical model, expressed in dynamic equations, to predict the evolution that a reality phenomenon will have and, if we want to use this theory, our first step is to set the initial conditions with which the model will work. But, we will never be fully sure of knowing reality, so we are only able to know the initial conditions with some level of error; we can only know the truth with some approximation. Since the initial conditions, which are entered in the equations, carry a degree of error, the model will produce an erroneous solution that can grow with time.
For the model to be useful for establishing predictions, we must know with what speed our dynamic model increases the errors introduced in the initial conditions and, according to the theorists of the subject, the chaotic models of greatest interest are those that reproduce the error at a exponential speed.
When we say that the models used by Chaos Theory are dynamic and deterministic, we are referring to the fact that they deal with phenomena in the real world that change over time and that determine a unique evolution for given conditions and over a period of time. Deterministic equations, which represent chaotic models, are those that, for any set of initial values, pose a unique solution over a period of time; consequently, trajectories in phase space cannot intersect or join, and a single trajectory cannot intersect itself either, because if this happened it would contradict the deterministic assumption. It can happen that the single state variable is attracted towards a fixed point. In the case of equations with two variables,the trajectories can take the form of loops several times and define a closed loop.
These fixed points and cycles of attraction are called attractors: delimited sets of points in phase space such that the trajectories that begin in their vicinity converge towards them (Smith, Peter, 2001, 16). Attractors are very important to explain the behavior of long-term trajectories.
Attractors
An attractor is stable; if it is disturbed, it will return to its original motion. It is also finite, since its behavior is confined to an area, from which it will not leave. In classical physics, an attractor is periodic or almost periodic; that is, their behavior is repetitive or almost repetitive. This type of attractor formed the foundation of Newtonian physics.
In the early 1960s, Edward Lorenz discovered another attractor that was named the strange attractor by David Ruelle and Floris Takens.
Lorenz built a very simple model of convection in the atmosphere, starting from the classical equations of the flow of incompressible fluids, represented by a reduced set of ordinary differential equations composed of only three variables. When Lorenz performed the numerical integration using a computer, he discovered that, for almost any initial state, the values of the variables were confined within defined limits; however, within these limits, the values vary in a random and unpredictable way.
Furthermore, he accidentally discovered that if he assigned initial values with small differences to the variables, the results of the model varied significantly. The model was very sensitive to initial conditions. When plotting the trajectories of the values of the variables in 3D, adopt a figure of two wings or loops.
Let us review, slightly, the behavior, in time, of these variables from initial values. If we take a single starting point, it defines a trajectory that will end rotating in the form of a two-loop structure, attracted asymptotically closer and closer to the so-called Lorenz attractor (Smith, Peter, 2001, 18). Now, if we follow the track, not to a point, but to two starting points that are close to each other and close to one of the loops of the Lorenz attractor, we will observe that the trajectories of these points will separate each time more as they advance and, in the end, they will not agree on anything. Also, there is no single path that is exactly reproduced.
The Lorenz attractor - states Peter Smith (2001, 19) - thus winds the trajectories attracted towards it forming an almost flat bundle of infinitely long threads, which never intersect, in which the neighbors diverge without interruption. A strange attraction, no doubt. Unlike classic attractors, it is neither periodic nor quasi-periodic; that is, the behavior of the system it represents is never repeated.
This strange attractor is the result of non-linearity and interactivity.
In relationships between individuals and organizations, the change of one variable is directly related to the change of another variable.
Dynamic systems are asynchronous, a change in one variable causes a change in the other; but, this change is not proportional. A single word mentioned in front of an audience, for example, may not happen at all or it may cause anger in an entire town. The behavior of nonlinear systems is unpredictable. The uncertainty of what can happen to each word spoken, in the example mentioned, illustrates this. Will people be happy or indifferent for every word that is mentioned? What will happen?
The lack of predictability in the behavior of this strange attractor is due to two factors. The first is related to what Lorenz called sensible dependence on initial conditions. Nonlinear systems are sensitive to small changes in initial conditions.
This means that something as small as the flapping of a butterfly can have significantly different results than those that would have occurred in its absence. For example, Ian Stewart (Stewart, 1989, 141) tells us: The flapping of a butterfly today produces a minute change in the state of the atmosphere. Over a period of time, the way the atmosphere behaves diverges from what it would have done in its absence. So, after a month, a tornado that would have devastated the Indonesian coast does not develop. Or it may happen that what would not have happened. (Cited by Smith, Peter, 2001, 73).
The butterfly is an element that is part of an interactive system, a chaotic system and, therefore, whatever it does will influence, in an unpredictable way, all the elements of the system. This phenomenon is called the butterfly effect. The micro errors in setting the initial conditions will be amplified into macro errors and the results are not negligible.
One insignificant word mentioned to workers can dramatically lower production in a company. Under these conditions prediction is very difficult.
The second factor, which determines unpredictability, has to do with what the famous French mathematician (1854-1912), Jules-Henri Poincaré, called resonance. According to Poincaré, each particle has two types of energy. Kinetic energy, which uses the particle for its present behavior, and potential energy, the source of its future behavior. Therefore, the motion of a single particle can be described by deterministic equations, since the amount of current energy that the particle has can be measured, it is the kinetic energy.
However, many particles close to each other will interact, releasing potential energy in an unpredictable way; in such a way that, if the initial conditions of a particle system could be measured very accurately, chaos would always exist, due to the interaction and potential energy. So that a small error in the initial conditions, instead of also creating a small error in the final results, would propagate an error of enormous proportions in them, so the phenomenon becomes unpredictable and it is not our ignorance of reality that that causes the error, but is the same reality that is elusive and does not allow us to fully know it.
The particles of a system interact, giving rise to a very important phenomenon called correlation. This concept helps a lot to understand human behavior. When two particles collide, their behaviors reflect a certain degree of synchronization, of harmony in their actions. The presence of stable behavior in chaos is observed here, described by what we know as attractors.
The same is true in organizations. Individuals interact throughout the organization, establishing a set of interactions with causality and bi-directional complexity, as coiled chains of interrelationships and their behaviors are correlated with a result. We see here the appearance of chaos.
Chaos, which we are studying, is an inherent characteristic of some dynamic models of the world, which present sensitive dependence on initial conditions, confinement and aperiodicity.
That is to say, the sensible dependence makes the trajectories tend to disperse more and more in time; the confinement consists of the folding of the trajectories on themselves so that they can remain within their limits and the aperiodicity means that the typical trajectories never repeat themselves. This simultaneous dispersion and retreats, together with the aperiodicity and the absence of any crossover between trajectories, gives rise to a very complex situation. This intricacy is typical of geometric structures called fractals.
The fractal concept was introduced by the mathematician Benoit Mandelbrot and it is a geometric structure that if we divide it into parts by means of folding and stretching (without breaks, intersections or contacts with itself), each of its parts is an exact replica of itself.. The constructions of Koch curves and the Cantor set are some mechanisms to generate fractals. Strange attractors, such as Lorenz's, are considered by chaologists to have fractal geometry.
State space
The state space, also called phase space or parameter space, is the abstract n-dimensional space that contains the coordinates of the values of the n state variables of a phenomenon of reality. In this space, any coordinate point will represent a particular state at a given time in a dynamic system. Thus, if we have a point x (0), which represents this state in an initial time instant, the dynamic equations will define a trajectory in the phase space of the point x (t), which represents the initial state in later times.
The state space or phase space describes the path followed by the trajectories of the values of the variables of a dynamic system; that is, it is the set of all possible states of a system. Gradual changes in the parameters of a system cause gradual changes in the phase space and the shape of the attractor of the system is slowly transformed. Attractors can expand or contract; they can evolve into simple periodic attractors or they can be lowered as an attractor point.
These transformations are not very dramatic. However, there are regions in phase space where the changes are dramatic; These changes are known as bifurcations.
At this point, the system can evolve towards one of two possibilities: it can return to the original state of equilibrium or it begins to self-organize to develop a new structure, a dissipative structure, so called because it consumes more energy than the organization it replaced..
This phenomenon gave rise to the theory of dissipative structures. Catastrophic changes occur when a system abandons its strategic lines and adopts others. Catastrophic changes do not necessarily mean they are dramatic; rather, they refer to radical changes in the structure, in behavior, in strategic plans, in their working methods. When, for example, universities change their curricula, when they create regionals, when they modify their technology, when they create new majors, they experience a catastrophic change.
In state space, catastrophic changes happen when a system breaks through a wall of parameters and enters a new niche. These changes occur in chaotic systems and are very rare in stable systems. A chaotic system is in an area of the state space where the regions are intricately intertwined, where a small change in parameters can move the system through a bifurcation wall, enter a new region, and lead the system to dramatic changes.. Dramatic changes can be caused by small internal events and their size cannot be predicted.
The Complexity Theory
When we try to understand reality, it appears very elusive, very elusive and what it teaches us is that in order to understand it, it is necessary to study it from different angles, from different points of view, in a multifaceted way. We cannot understand the individual if we study him apart from his culture, his environment, his history, his origin, his biological, psychological and social component. The reality is complex. But what is complexity?
The term complexity refers to our inability to understand real phenomena, to our confusion and insecurity when dealing with them, to our disturbance and frustration when we cannot give a simple definition of everything that, by its very nature, cannot be simple. Because reality, however simple it may seem at times, never is.
Traditional science, in its attempt to know and explain the phenomena of reality, applies simplifying methods, mutilating the processes and, therefore, producing mutilated thoughts.
There are two ways to interpret complexity. A subjective, which refers to the inability of the subject to know reality; another, objective, as an inherent characteristic of the object to be known. Complex thinking states that reality is a system in permanent change and that its constituent elements interact, facilitating a process of generation of new structures. In this sense, Steven Levy (in Russ Marion, 1999), defines complex systems as follows:
A complex system is one whose components interact so intricately that it cannot be predicted by standard linear equations; there are so many variables that function in the system that its total behavior can only be understood as an emergent consequence of the holistic sum of its innumerable behaviors contained in it.
Complexity is the characteristic of most of the phenomena that exist in organizations; therefore, to obtain a better understanding of them, it is necessary to consider them from different approaches, from transdisciplinarity. Etymologically, transdisciplinarity means that which is beyond all discipline, that which cuts across all disciplines (from Latin, trans = through). Transdisciplinarity is located on the edge, in the space of the different disciplines and represents the realm of the unknown and allows us to understand the world free of dogmatisms.
An analysis of the differences between the science of the 19th and 20th centuries, that is, the deterministic position and the new Physics, Quantum Physics will help us understand the complex approach.
Determinism
Classical Newtonian physics describes a reality independent of the observer, a reality that exists outside the individual, in space. This is the image that is found in the third book of the Principia (Newton, 1687) and that considers the universe as a machine.
Here determinism equates to mechanism. The mechanisms are governed by exact causal laws and subject to a necessity or determinism; in quantum mechanics the two concepts are not equivalent.
I believe that the best explanation of determinism is found in the physics of Pierre Simon de Laplace, who took up the concept of Newtonian mechanics. Newtonian laws for motion imply that the future behavior of a system of bodies is completely determined by knowing the positions and velocities at a single instant of time.
Laplace not only attached great importance to Newton's determinism, but also extended the application of the term to other fields:
An intelligence that at a given moment knew all the forces that animate Nature, as well as the respective situation of the beings that compose it, if it were also broad enough to subject such data to analysis, could include in a single formula the movements of the largest bodies in the universe and those of the lightest atom; nothing would be uncertain and both the future and the past would be present before his eyes. (Laplace, De la probability, 1814; cited by López Corredoira, Martín in Determinism in classical physics: Laplace vs. Popper or Prigonine, nd).
Here are a few words closer to our topic:
… in our own plans and companies we take into account the effect of motives on men with a certainty that would be completely equal to that with which the mechanical effects of mechanical devices are calculated, as long as we knew the individual characteristics of the men to be treated here with the same exactitude with which the length and thickness of the beam, the diameters of the wheel, the weight of the loads, etc. are known. (Schopenhauer, The two fundamental problems of ethics, 1993; in López Corredoira).
Determinism and predictability or computability
Predictability or computability refers to the fact that human beings can predict the future state of a physical system; that is, we can calculate the values of all its variables. The concept refers us to epistemology, to what we can observe, analyze or calculate. It depends partly on nature and partly on us. Determinism, on the other hand, refers to the way things are in themselves, to ontology; it depends on the behavior of nature, regardless of its observers. Determinism is a broader concept than predictability or computability. We must clarify that determinism does not imply predictability and that a deterministic system does not have to be knowable. Thus, there may be a destination that determines a fact and yet it is not possible to know that destination and therefore is not predictable. But,predictability implies determinism; in such a way that, if we intend to accurately predict the behavior of individuals in organizations, it must respond to exact deterministic laws and we must know those laws.
Gödel, who developed the famous principle of incompleteness, suggested that it is possible the existence of a deterministic theory that explains the behavior of an individual based on their genetic inheritance and their environment; However, it is not possible for the human being to know it in order to change his destiny, unless he does not want to change his destiny and that not wanting to change it is also predestined (Rucker, 1983; in López Corredoira).
Quantum physics
It was the German physicist Werner Heisenberg who laid the definitive foundations for the new physics with his famous uncertainty principle, which completely transforms the relationship between the observer and the observed.
In classical physics, the interaction between the observer and the observed object is assumed to be negligible because the former hardly affects the latter and can therefore be neglected or eliminated from the result. On the other hand, in quantum physics, the interaction between the observer and the object produces enormous changes that cannot be controlled and, therefore, any attempt to know exactly the simultaneous values of two variables is, in many cases, impossible.
The accuracy with which they can be known has limits: the more I know the value of one variable, the less knowledge I can obtain about the value of the other, and this is not due to the inability of the observational instruments, but is a characteristic of the reality.
The more determined one, the more indeterminate the other. This is the uncertainty or indeterminacy principle.
There is another principle related to the uncertainty principle, that of complementarity formulated by Niels Bohr. The principle of complementarity is that different images can be used to describe atomic systems that may be perfectly adequate, even though they are mutually exclusive.
In the case of light, sometimes it behaves like a particle, other times like a wave. Wave and particle are complementary states. Light is both, as long as we do not observe it. If we want to question it as a wave, it will answer us as a wave; but if we question it as a particle, it will answer us as such. Every study modifies the object observed. Quantum physics expresses itself through paradoxes; hence Bohr's famous expression: if when thinking about quantum mechanics you don't feel vertigo… you really haven't understood.
Richard Feyman, Nobel Prize winner in Physics in 1965, shrugging his shoulders, commented that nobody understands quantum mechanics.
The principles of quantum physics cracked the traditional principles of science and made a great difference with the postulates of traditional logic.
Logic, whose object of study is the norms of truth, always govern the actions of individuals and leaders in organizations; Behind all conduct of people in companies there is always a certain rule. Therefore, it is a certain logic that governs the actions of an individual, of social groups, of a company, of a state.
The correlations between individuals and between groups is determined by a specific logic. There is a direct relationship between logic and the existing climate in organizations.
The environment, behavior, and understanding of individuals in organizations change over time, and therefore logic changes as well. There is an organizational behavior for each era and a logic that explains that behavior.
It has always been believed that logic does not change, without realizing that the evolution of social groups obeys certain logics and we act, consciously or unconsciously, according to Aristotelian logic. It is this logic that has governed and governs today the understanding of behavior in organizations. Aristotelian logic is based on three well-known axioms:
1. The axiom of identity: A is A
2. The axiom of non-contradiction: A is not not A
3. The axiom of the excluded third: There is no third term T (T for "excluded third party") that is at the same time A and not A
Let's take the following example:
1. The axiom of identity: A rational individual is a rational individual
2. The axiom of non-contradiction: A rational individual is not a non-rational individual
3. The axiom of the excluded third: There is no one who is both a rational individual and not rational.
Aristotelian logic is binary (A and not A) and responds to a horizontal reality, to a single level of reality. The evidence for the axioms of classical logic comes from that provided by sensory knowledge. Therefore, behavior based on this logic, due to the excluded third party, leads to an authoritarian leadership style.
The quantum revolution is based on a logic of the third included, a ternary logic, which leads to a unity of the contradictory from which a new identity arises.
Thus, two contradictory phenomena can exist simultaneously; a person can be both rational and irrational; effective and not effective; stupid and not stupid. Man belongs to two levels simultaneously: the macrophysical level and the microphysical level. And, therefore, it responds to binary logic and ternary logic; but, it is the latter that complements the former. While binary logic is linked to knowledge, ternary logic is linked to understanding. Today's business world privileges knowledge, attaches great importance to efficiency and is the basis for specialization, and many are excluded from this process. We are not saying that specialization is not useful; however, extreme specialization is a danger to the integral development of the individual. So under binary logic,it is impossible for the being to be efficient in its work and, at the same time, achieve fulfillment. But is it possible to resolve this contradiction?
The answer is yes and it is offered by transdisciplinarity, with the logic of the third party included. Transdisciplinarity is a collective concept; It means that there is not a single level of reality and, therefore, a single logic that appropriates the truth, but rather several levels of reality and many logics.
Complexity and chaos
Social systems and biological systems, unlike physical systems, adapt and possess information about their past and their environment; they are able to learn from their experiences and adapt their behavior accordingly and can anticipate their future and try to influence it.
In the opinion of Russ Marion (1999), Chaos Theory laid the foundations for a theory that studies these adaptive systems, called Complexity.
Complexity is a hybrid state that sits between stability and chaos. Chris Langston (Russ Marion, 1999) has experimented with complex phenomena with an instrument called a cellular automaton to observe that organizations emerge from stability and chaos. This consists of a game board of checkers in which the players live or die, depending on the availability of resources. Supported by this game, Langston concluded that life processes such as social activity and organizations are simultaneously stable and chaotic, constant and changing, capable of storing reliable information and processing it dynamically.
Complexity and organization
It has been suggested in this work that new structures result from the relationships established between the different components of a system. Individuals with their own interests, and without any external element that coordinates them, relate to each other, forming small circles, which are called units. These units are governed by their own rules and are grouped spontaneously, without structured plans. Their behaviors are based on imperfect and primitive projections of their results; they interact in some way, through language, through the presence of others, or in any other way. These interactions between individuals cause the emergence of a system and, since their interactions are spontaneous, the emerging system does not obey deliberately created plans; simply,emerges without any external force. In other cases, individuals may know what they must do to organize and, in this sense, the process is planned; however, they may not be able to remember why or how they got there or why the adopted organizational structure was chosen among other possible ones. Interactions between individuals are two-way; This is important for the total system to exercise strong control over individual behaviors and, furthermore, to ensure their dynamism and survival.Interactions between individuals are two-way; This is important for the total system to exercise strong control over individual behaviors and, furthermore, to ensure their dynamism and survival.Interactions between individuals are two-way; This is important for the total system to exercise strong control over individual behaviors and, furthermore, to ensure their dynamism and survival.
The emerging system has the following characteristics (Russ Marion, 1999):
- The total system is more powerful than its component parts It is much more functional than its component elements or the sum of its individual capabilities It can contain and use a large amount of information It can reproduce itself and, even more, produce more replicas complex than the system that emerged The new system violates the second law of thermodynamics because it can grow and be stronger than structures that dissipate energy It is able to maintain its integrity in the face of a disturbance process.
Emergence of the new order
The Theory of Dissipative Structures was developed by Ilya Prigonine (Belgian physicist and chemist of Russian origin, Nobel Prize in Chemistry 1977) and his collaborators. A dissipative structure is, for Prigonine, an open system that keeps itself far from equilibrium and yet is stable: the same structure is maintained despite the constant flow and change of its components.
When the flow of energy increases, the system can encounter a point of instability, known as the bifurcation point, in which a new state can emerge in which new structures and new forms of order appear. How does the process by which these ordered systems occur? As mentioned above, complexity theorists answer that the process of new structures is the result of individual interactions, that it does not require planned effort nor is it the product of evolution. Order emerges freely all of a sudden and natural selection plays a secondary role in this process.
For Prigogine, thermodynamic systems develop through three possible states or phases. The first is a state of equilibrium, in which the stability of the structures is the result of the antagonistic dynamics between energy and entropy. The second represents a quasi-equilibrium stationary state, in which the flows are proportional to the forces. It is a state close to equilibrium; However, there are small differences that characterize a slight imbalance and that control the homeostatic processes of the system and, therefore, disappear without causing significant changes. The emergence of new organizational structures is not possible in either of these two states.
The third state, situations far from thermodynamic equilibrium occur, which Prigogine calls «order by fluctuations»:
the small existing disturbances are amplified and originate a macroscopic fluctuation, stabilized by the exchanges of the system with the environment. Small deviations occur that destabilize the uniformity of the system, and the one that is randomly selected at the so-called "bifurcation points" determines the macroscopic evolution of the system.
Prigogine calls the structures that emerge from this process "dissipative", since their stabilization requires an energy expenditure.
En el proceso de interacción, existe una dinámica denominada autocatálisis. Este fenómeno puede facilitar la aparición de un resultado; en otras palabras, un catalizador hace que sucedan cosas que de otra manera no sucederían. Un proceso catalizador puede dar origen a otros procesos y puede ir creciendo cada vez más para formar una reacción en cadena Por ejemplo, la aparición de los movimientos de oposición en una organización, puede ser descrito con este proceso. Es posible que cierto estilo de liderazgo pueda producir (catálisis) un sentimiento de odio y resentimiento en algunos grupos.
Groups of individuals emerge and come together to convey their ideas and plans to other individuals; which increases the feeling of hatred and resentment. In addition, this situation can lead to the disintegration of people in their jobs and can, in turn, lead to destabilizing behavior that increases the differences between the organization and the focus groups. The feeling of hatred and resentment inhibit the processes of organizational development, which leads to the phenomenon of ungovernability. This tangle of relationships continues to grow and an atmosphere of uncontrollable unrest is created. Once a critical level of hatred-resentment-disintegration-destabilization-ungovernability and so on, any single event can lead to a catastrophic situation. At this time,a point of instability has been reached, because the organization is unable to process and integrate this new information in its current order and is forced to abandon some elements of its structure, behaviors and policies. A situation of chaos, confusion and uncertainty appears that can result in a new order, organized around new purposes.
The new order was not the product of individual action, but emerged as a result of the collective creativity of the organization.
Let's see the stages that occurred in this process. In the first place, the existence of some opposition in the organization; an acceptance to cause disturbance to set the process in motion; the development of an active communication work with feedback processes to amplify the event. The next stage is the point of instability, which was experienced as tension, chaos, uncertainty, and crisis.
At this precise stage, the organization either collapses or makes its way to a new state of order. It is convenient to emphasize that new solutions are created in the context of a culture of a particular organization, so they cannot be mechanically transferred to other organizations with different cultures.
In organizations there are two types of structure. The designed structure is the formal structure of the organization, which exists in the working documents.
Also, there is the emergent structure that is created by the informal collective work relationships and by the community of interests of the members of the informal groups. These structures are not independent, rather they are complementary. The designed structure represents power; the emerging, imagination and creativity. Both are necessary for organizational development and are interdependent. For this reason, skilled managers know that in turbulent environments, such as today's, their challenge is to find the correct balance between the creativity of the emergency and the stability of the designed structure. (Fritjof Capra, 2002).
To define a formal structure, the manager must have the ability to construct mental images; on the other hand, it must facilitate the emergence of new structures and, for this, knowledge of the theories of complexity and chaos is required.
How useful is a chaotic model for making predictions?
The question is rooted in what we have said about chaos. If the chaotic models are very sensitive to the initial conditions, this means that the inevitable errors that are made when setting the initial conditions increase exponentially, from which it follows that the predictions derived from the use of this chaotic model will be extremely wrong.. Is a model with such characteristics useful?
Let us remember what we have said about the Lorenz model: the trajectories are attracted very quickly towards the attractor. So to answer the question, we must study the behavior of the trajectories on the attractor. As trajectories are attracted very quickly towards it, if we determine the starting point of a trajectory, it is possible to predict its behavior for at least a short time, although the precision will decrease rapidly depending on the precision with which we set the starting point.
If we were precise enough to mark the starting point, for a longer time we will be able to predict the evolution of the trajectory; the confidence and duration with which we can predict depends on the permissible error in setting the initial conditions.
It may be tempting to think that the model is predictable for as long as we like ("let's just make the initial error ε small enough…"). (Smith, Peter, 2001, 61). Although if we want to use the Lorenz model, we need to fix the initial data with a precision difficult to achieve in reality and, in addition, the Heisenberg uncertainty principle of Quantum Physics imposes limits to the measurement. Only Laplace's demon, with infinite capacity, can know with all the precision it wants the initial data and predict with infinite precision; But, we humans are far from being almighty gods or demons.
Although we could set the starting points with great precision, the detailed prediction of a trajectory is not possible, because there will come a time when we will lose information about it. But not all is lost; It is possible to predict the evolution of trajectories in the short term and, in addition, we can predict the general long-term behavior of the trajectories, because, according to what we have proposed, they are finally confined to an area of the attractor.
Thus, chaotic models are predictively useful, since we can use them to track short-term trajectories, and it is also possible to predict the general long-term behavior of trajectories.
And not only that, they are also very useful for conducting sensitivity analysis that offers qualitative and quantitative information on the way in which the behavior of the model changes when the values of the relevant variables vary.
Organizational attractors
So far everything is very interesting. We have suggested that attractors, a central element of chaotic models, represent a very special role in physical and natural systems; But, does it have any application in organizational systems? My answer is yes. If we try, if we make an effort without trying to force reality, we will achieve it. At least we will have to try. Later we will see.
Organizational behavior can be described with a strange attractor and, if we can identify the appropriate indicators, the behavior of individuals in organizations can be physically described with an attractor. Of course, it is necessary to study this subject in greater depth; therefore, the statements that are raised in this work remain at the level of initial hypotheses, offered for debate.
The strange attractor is stable; But, their behavior is never exactly repeated and has the capacity to change: it can grow or diminish to encompass a wide or small range of behaviors. It can change its appearance, become another completely different attractor, and it can even disappear.
Organizational behavior has a similar behavior. Like attractors, the behavior of individuals in organizations changes over time: fashions change, relationships with institutions change, and organizational processes evolve.
Organizational attractors sometimes undergo radical changes, such as the change that happened in the former USSR in the late 1980s. Corporate systems, such as attractors, can disappear: many of us have witnessed the disappearance of small and large corporations.
Towards an understanding of the behavior of individuals in organizations
I will try to develop, in this part, how the contributions of complexity theory can help to re-understand the behavior of organizations from a new, more comprehensive perspective.
The behavior of beings is the result of two types of forces in constant interaction: on the one hand, deterministic forces, linear and governed by the laws of causality, and yet it does not imply that we know that determination and, on the other hand, another, chaotic, non-linear forces. Determinism and chaos coexist in the life of organizations and both define the emergence and behavior of individuals and groups in organizational systems. If we had the ability to identify a deterministic phenomenon from another chaotic one, perhaps we would be able to provide answers to questions that very frequently arise in companies, such as, why does one person behave differently from another in the same circumstance? ?,Why are the individuals in one department less conflictive than those in a neighboring department? Why are some people so aggressive? Why has a minor incident had catastrophic consequences? Why does conflict exist in the organizations? An initial answer to these questions is that some events in organizational life do not respond to linear causes. We are used to thinking this way.
Thus, we say that morale causes productivity and that productivity determines business profitability. However, it may not be that way and that the relationship is not linear, but circular causal: that the effect also determines the cause. It is necessary to recognize the complexity of organizational behavior.
At this point, perhaps no one doubts that biological and cultural factors are involved in all human behavior, and yet many act as if they don't know. Man, as Morín says, is unidual, that is, he is at the same time completely biological and completely cultural; For this reason, it is necessary to overcome the dilemmas: or biological or cultural, or rational or irrational, or conflict or collaboration and think in a dialogical way to overcome antagonisms and make them complementary so that they generate harmony.
In all beings, present behavior and potential behavior coexist; present behavior is observable and potential is not; but it is waiting for its time to manifest itself and make itself present; being is one and the other at the same time.
Therefore, the individual is the multiplicity in unity. The behavior of an isolated individual can be predictable; however, the behavior of the interacting individuals is very unpredictable, due to what Jules-Henry Poincaré called resonance.
When individuals interact, they transfer energy to each other, they transfer information in the same way that the billiard ball that receives the first impulse goes off and when it collides with another ball it transfers energy and it does the same with others, and so on. successively, in such a way that the trajectories that the balls will describe are completely unpredictable.
This is resonance. When individuals in organizations interact, their actions begin to coordinate, harmonize, and people can develop a common vision, a common purpose, and a common agreement on how they can solve their problems and meet their needs. These individuals can sensitize others to join the group and increase their influence over the organization.
Their behaviors are correlated, roles are defined which is the basis for specialization and cooperation; it is a process of autocatalytic interaction. We see, in this interactive dynamic, the emergence, in a natural way, of the order resulting from the resonance of spontaneously coordinated behaviors. A new attractor has emerged spontaneously.
In organizations there are several attractors, some with great attractive force and others with less. An attractor can be an idea-force. People cluster around attractors; therefore, they can facilitate certain changes or resist them. The existence of idea-forces are powerful attractors that allow organizations to enter a dissipative process of problem solving. Dissipative logic is, by definition, unpredictable. We cannot be entirely certain which idea-force may be attractive to individuals in problem solving. The leader must not impose it; what it must do is facilitate its emergence, promoting collective participation and, at some point, the idea-force will appear spontaneously and attract other attractors.This cluster of attractors will increase its attractive force to such an extent that its influence on the development of the organization will be very strong. Leaders should not try to force the process; it develops spontaneously.
According to Russ Marion, the number of attractors that can emerge in a social system is the square root of the number of individuals in that system. Attractors attract all kinds of people, selfish and altruistic. If an organization leader were to form a group only with altruistic people, in a short time he would find in the group selfish people who have forked from his group. This phenomenon is known as critical oscillation and allows open systems to self-regulate to maintain homeostasis. In other words, the existence of egoists is necessary for altruists, as long as the amount does not exceed a certain critical range to maintain balance. If the number of selfish individuals exceeded that of altruists, the system would become chaotic and lose its balance. It is not known when this happens.
Conclusions
The main conclusions that stand out in this work are:
When it is intended to analyze the behavior of individuals in organizations from a complex perspective, there is a risk of reaching extrapolations that come out of the scientific field, so its application must be carried out with great care and mastery of the subject.
Chaos Theory and Complexity Theory consider organizational structure and behavior as the product of interactive dynamics.
There is a belief that decisions are made with rigorous planning and under a rational process. When the steps of the rational model are presented to administrators, many responses are: Who the hell has the time to do that! The rational model (at least John Dewey's rational model) holds that problems are independent of the environment, that decision-makers have access to complete information, and that events respond to a simple and single causal direction. Complexity theory holds that managerial decisions are rarely logical, since it is very difficult for someone to have access to all the information, because most of the problems that managers face are complex in nature, that there are few simple causes in human behavior and that, on the contrary,the cause is generally two-way: leadership style can affect productivity and productivity, in turn, can affect leadership style. In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Two-way: leadership style can affect productivity and productivity, in turn, can affect leadership style. In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Two-way: leadership style can affect productivity and productivity, in turn, can affect leadership style. In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Leadership style can affect productivity and productivity, in turn, can affect leadership style. In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Leadership style can affect productivity and productivity, in turn, can affect leadership style. In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.In this sense, there is a circular relationship between the environment and the organization, both are the product of their relationships with the other, both are created and recreated; therefore, the problems managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.the problems that managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.the problems that managers solve are the product of those relationships and not the product of a passive environment. The decision-making process, then, is an interactive process. Looking at the development of the business process, one can see that great ideas and project completion were rarely the result of rigorous planning processes. Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Many of the great ideas were carried out without being aware of the scope and consequences of their actions.Many of the great ideas were carried out without being aware of the scope and consequences of their actions.
Within the framework of transdisciplinarity, it is possible to reconcile the irreconcilable in organizations, find a solution of balance between the contradictory, the effectiveness and the completeness of the individual. Transdisciplinarity requires new leaders who are capable, not only of holding a vision, articulating it and communicating it with passion and charisma, but also catalyzing the emergence of new structures.
To do this, you must create the conditions rather than give directions to facilitate creativity. The vision that predominates in the business world (consciously or unconsciously) is basically anti-transdisciplinary, governed by the binary, fragmentary, exclusion logic in which authoritarianism, intolerance, and misunderstanding are possible.
On the other hand, administrative complexity responds differently, its main effort consists in studying the nature of organizations, which is, in turn, logical and illogical. As the physicist Basarab Nicolescu said in his lecture at the AXA University Seminar Course, devoted to the Management of Disorder and Complexity:
Thus, the singular of specialization (logic, language, causality, space-time, Reality, knowledge) responds to the plural of transdisciplinarity (logics, languages, causalities, space-times, different levels of Reality, the different types of knowledge). There is a considerable source of tolerance there.
Transdisciplinarity in organizations will be possible with a change in managerial mentality and new individual and group behaviors that make the concepts of productive efficiency and transformative efficiency complementary, and not contradictory. Let us therefore advocate for a transdisciplinary administration.
Bibliography
Brigg, J. & Peat, FD (1999). The Seven Laws of Chaos. The advantages of a chaotic life. Barcelona: Grijalbo.
Capra, F. (2002). The Hidden connections. A science for sustainable living. New York: First Anchor Books Edition.
Gleick, J. (1987). Chaos. Making a new science. Canada: Penguin Books Ltd.
González, de Alba. (2001). Sancho's donkey and Schrödinger's cat. México, DF: Editorial Paidós Mexicana, SA
Hawking, S. (2002). The Universe in a Nutshell. Barcelona: Criticism-Planet.
López Corredoira, M. (sf). Determinism in classical physics: Laplace vs. Popero
Prigonine. Canary Islands: Institute of Astrophysics.
Marion, R. (1999). The Edge of organization. Chaos and complexity theories of formal social systems. California: Sage Publication, Inc.
Rall, JG & Webb, KA (1999). The nature of chaos in business. Houston, Texas: Gulf Publishing Company.
Smith, P. (2001). The chaos. Madrid: Cambridge University Press.
Tipler, FJ (1997). The physics of immortality. Madrid: Alianza Editorial, SA.
