Toward a science of qualities in organizations: lessons from Complexity theory and postmodern biology
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Toward a science of qualities in organizations: lessons from Complexity theory and postmodern biology
Reason, P., & Goodwin, B. C. (1999).
Toward a Science of Qualities in Organizations: lessons from complexity theory and postmodern biology.
Concepts and Transformations, 4(3), 281-317.
Abstract
The development of complexity theory in the natural sciences is described, and summarized in six principles of complex emergent wholes. It is suggested that complexity theory is leading biology toward a science of qualities based on participation and intuition. It is argued on metaphorical and epistemological grounds that these principles which describe the emergence of complex wholes can be applied to social and organizational life. The six principles are then applied to qualitative and action research practice, with a particular reference to co-operative inquiry, in order to provide principles for good practice and theoretical support for the nature of valid inquiry processes.
Acknowledgements
The authors appreciate the critical and constructive comments they have received on earlier versions of this paper from John Heron, Paul Roberts, and Mary Jo Hatch
Introduction
In this paper we outline the bases of complexity theory and review some of its applications in the natural sciences, particularly in biology. We suggest that this line of thinking, particularly as it has developed in postmodern biology, leads us toward a science of qualities based on participation and intuition, and that there are remarkable similarities to the kinds of knowing which are seen as central in constructionist and participatory approaches to social and organizational life. We continue to argue that social life in general, and organizations in particular, can well be seen as complex self-organizing systems, and that drawing on complexity theory to explain them, while necessarily metaphorical, is epistemologically justifiable. We then apply the six principles to complexity theory to the practice of qualitative and participative forms of organizational research, and argue that these principles lead us toward new ways of thinking about the quality of a research endeavour.
Limitations of the Control Paradigm
Reductionist science is essentially a strategy of divide and conquer: dividing the world into constituent systems whose parts are simple enough to allow prediction of their behaviour, and hence to exert control over their activity. This has worked remarkably well in many physical systems and even, to some extent, in biology. The approach exemplifies the principle that can be described metaphorically as linear thinking, which regards a whole as no more than the sum of its parts. Manipulation of the parts then results in control over the whole.
The limitations of this approach are becoming ever more apparent as we struggle to grasp the inherent complexities of organisms and ecosystems, organizations and societies, and patterns of global ecological change. Gregory Bateson was one of the first to point to the epistemological errors that arose when linear thinking is applied to the natural world, showing how conscious purpose creates errors since it abstracts small arcs of complex ecological circuits. He argued that "the most important task today... is to learn to think in the new way" (Bateson, 1972:462), and stressed the importance of appreciating the intricate networks of information and actionthe circuits of mindthat characterise the living realm.
A systematic foundation of such an alternative method of studying complex systems has been developing for nearly a century. It started with the forays by Henri Poincaré, the great French mathematician and physicist, into the roots of chaos in something as apparently predictable as planetary motion. Towards the end of the last century, he applied the classical Newtonian theory of gravitational attraction to the movements of three bodies simultaneously, such as the Sun, Earth, and Moon, and observed that the equations gave rise to very strange dynamic behaviour that seemed to carry a distinct, though obscure and unfamiliar, signature: it appeared that even a simple system of three bodies in space is not fully predictable in its behaviour. It was not until the early 1960s that the details of this distinctive pattern were characterised. Edward Lorentz, a meteorologist at the Massachusetts Institute of Technology, working on equations that describe the dynamics of the weather, found the same behaviour that Poincaré had. He had the advantage of a computer which showed him a picture of the dynamic behaviour. Using Poincaré's method of studying nonlinear systems, he saw a new and beautiful mathematical object: a strange attractor (Figure 1) (Lorentz 1963, 1991).
Lorentz realised that he was dealing with a radically new type of behaviour pattern whose properties led him to an immediately graspable metaphor: a butterfly flapping its wings in Iowa could lead, via the strange dynamics of the weather, to a typhoon in Indonesia. Stated in another way, very small changes in initial conditions in the weather system can lead to unpredictable consequences, even though everything in the system is causally connected in a perfectly deterministic way. The way this works in relation to the figure is as follows. Suppose you choose any point on the tangled curve in Figure 1 as the starting point, corresponding to some state of the weather. This will develop in a perfectly well-defined, though complex, manner, by following the curve from the (arbitrary) starting point in one direction, which is prescribed by the equations. Every successive state is clearly definedi.e. everything is perfectly deterministic, since this is what dynamical equations describe. However, suppose there is a small disturbance that shifts the weather to a neighbouring part of the system, to a point on a nearby part of the tangled curve. Then, comparing the state of the initial weather system with that of the disturbed system as they both develop along the curve, a basic property of the strange attractor is that they move away from each other exponentially fast. That is, knowing what the weather is now is no predictor of what it will be a couple of days hence, because tiny disturbances (the butterfly effect) can produce exponentially divergent behaviour. This is the signature of deterministic chaos, now identified in a great diversity of mathematical equations whose dynamic properties are described by strange attractors.
The consequences of this mathematical discovery are enormous. Since most natural processes are at least as complex as the weather, the world is fundamentally unpredictable in the sense that small changes can lead to unforeseeable results. This means the end of scientific certainty, which is a property of 'simple' systems (the ones we use for most of our artefacts such as electric lights, motors, and electronic devices, including computers). More complex systems, and particularly living ones such as organisms, ecological systems and societies, are radically unpredictable in their behaviour, as we all know from experience. But now we have a precise hypothesis about what may underlie this complexity: they may all live dynamically on strange attractors, or similar types of intelligible order governed by sensitivity to initial conditions, obeying dynamic rules that make it impossible to predict or control their behaviour.
This is where another aspect of the complexity story enters. A typhoon may well be the unforeseen consequence of the butterfly innocently seeking nectar from the flowers growing in the fields of Iowa. But a typhoon is not itself a chaotic weather pattern: it has a highly organised dynamic structure with well understood behaviour. Where does this order come from? It emerges from the intrinsic properties of the weather as a dynamic system (not included in Figure 1, which is a greatly simplified picture despite its own complexity). That is to say, a typhoon is one of the (relatively few) patterns that the weather system can generate. So there is something about the dynamics of the weather that combines both order and chaos. They live together. Although we cannot predict what will be the consequences of a small disturbance, we do know that one of a limited set of possibilities will followa typhoon, a high pressure region with sunny skies, a low pressure front with rain, and so ona large but not indefinite set of possible patterns. The weather unfolds in irregular cycles of varying duration. This is a signature of complexity.
Life at the Edge of Chaos
These basic insights into the dynamics of complex, nonlinear processes have now been applied to a great diversity of phenomena, particularly in biological evolution. They raise doubts about Darwin's fundamental insight into the origins and extinctions of species, the processes of macroevolution (Goodwin, 1994), though it is universally acknowledged that the Darwinian mechanisms of adaptive change are fundamental to microevolution, the small-scale modifications whereby organisms become better adapted to their habitats. In the Darwinian perspective, what drives evolution is competition for scarce resources between organisms that differ from one another in their 'fitness', their capacity to leave offspring. The survivors of this struggle are the better adapted, those that can function better in their environment. However, the evidence from studies of species emergence and extinction during past geological ages and from models that simulate these processes, is that species do not go extinct because of failure to adapt to changing circumstances, or because of cataclysmic events such a meteorite impacts or volcanic eruptions. Although these have undoubtedly contributed to the disappearance of the dinosaurs, for example, it appears that there is an intrinsic dynamic in complex systems, such as interacting species in ecosystems, which results in intermittent extinctions that vary from small to large, with a characteristic distribution, which occur independently of the sizes of external perturbations. Meteorite impacts and large volcanic eruptions can certainly trigger major extinctions so that, as David Raup (1991) put it, species go extinct not because of bad genes but because of bad luck. However, there seems to be a natural dynamic to creative processes such as evolution that involves inevitable extinction with a characteristic pattern of survival that is not due to individual success or failure but to the interactive structure of complex processes (Solé et al, 1998). The type of attractor involved may be similar to what Bak and Snepen (1993) have described as self-organised criticality. The game of life, we might say, is cycles of creative emergence and extinction in which the reward is not long-term survival but simply transient expression of a coherent form, a revelation of a possible state of life which we call a species, whose value is intrinsic to its being. Life, it seems, is not to be measured by quantity of success but by quality of creative living.
Clearly the metaphors are shifting here from competition and survival to creative emergence and expression of appropriate novelty. These are not necessarily in conflict. In fact, they are united in another fundamental insight of complexity theory. While studying the dynamic behaviour of cellular automata, which are particularly useful for modelling complex systems, Norman Packard and Chris Langton (see Waldrop, 1992) had the intuition that the 'best' place for these systems to be in order to respond appropriately to a constantly changing world is at 'the edge of chaos'. Here order and disorder are combined in such a way that the system can readily dissolve inappropriate order and discover patterns that are appropriate to changing circumstances (Kauffman, 1993, 1995). This fertile suggestion has been subject to severe criticism, as should any proposal that attempts to capture a generic property of a whole new class of systems. However, the basic idea that creative, adaptive systems are most likely to function best near the edge of chaos is proving to be a robust insight, despite the difficulty of pinning it down precisely (i.e. mathematically and logically). One of the consequences of living on the edge is precisely the curious dynamics mentioned above: intermittent waves of extinction sweep through the system. Thus even though a player adopts a game plan of not holding on too tenaciously to any working strategy so that it can be dissolved when circumstances change and a more appropriate order allowed to emerge, there is no guarantee that the new order will result in survival. Clearly no-one can predict and control such systems. However, there are ways of maximizing creativity, providing us with a postmodern paradigm of learning to participate in an unpredictable, but nevertheless intelligible, world.
Six Principles of Complexity
After this discussion of the general characteristics of the science of complexity, we focus on six principles that capture what we believe to describe the essence of this approach to the dynamics of complex processes and their emergent properties. There is as yet no general consensus on how to axiomatise this subject (see, e.g., Holland, 1998), so that our characterisation is in no sense canonical.
1. Rich interconnections
Complex systems are defined in terms of rich patterns of interconnections between diverse components (Kauffman, 1993). We can contrast this with simple systems which can have many components, but they themselves, and their interconnections are simple and uniform. A gas, for example, can be made of billions of molecules but they are all the same and act in the same way. Hence the order that gases express, such as is described by the gas laws and transition to the liquid state at particular temperature and pressure, is well defined and their behaviour is predictable. However, in complex systems a knowledge of the properties of the components is not sufficient to allow one to predict the novel order that will emerge. There are two reasons for this. First, as mentioned above, knowing the present state does not allow one to predict future behaviour, as in the weather; and second, the whole system has self-organising properties that transcend the properties of its parts, a feature that arises from nonlinearity. This is why reductionism fails in complex systems (Cohen and Stewart, 1995).
2. Iteration
Complexity theory describes novel, emergent form and behaviour as arising through cycles of iteration in which a pattern of activity, defined by rules or regularities (constraints), is repeated over and over again, giving rise to coherent order. The order arises as a rich network of interacting elements is built up through the iterative process and the consequences of the process emerge.
A well-known example is the Mandelbrot set, a complex spatial pattern in which complex order emerges from an iteration procedure on a simple mathematical equation (Mandelbrot, 1982). The iteration involves using the result of each calculation on a simple mathematical equation as the initial value for the next calculation. This gives rise to a sequence of points that define an unfolding spatial pattern. The complex potential of simple rules emerges through iteration. Instead of focussing on solutions which converge on a particular state, which are the classical attractors of dynamical systems, computers facilitate the exploration of convergent and divergent states at the same time and map them systematically in relation to each other. This results in the identification and characterisation of fractal patterns and the visualisation of strange attractors, such as the Lorentz attractor (Lorentz, 1963), which simultaneously describe convergent and divergent motion.
3. Emergence.
The order that emerges in a complex system is not predictable from the characteristics of the interconnected components and can be discovered only by operating the iterative cycle, despite the fact that the emergent whole is in some sense contained within the dynamic relationships of the generating parts. A simple example of this is the emergence of a rhythmic cycle of activity-inactivity in ant colonies from chaotic individuals. Experimental studies (Cole, 1991) revealed that individual ants of the genus Leptothorax have a chaotic pattern in their transitions from activity (movement) to inactivity (no observed movement). However, when there are enough individuals within a confined space (i.e. a high enough density), the whole group develops a rhythmic pattern with a cycling time of about 25 minutes from activity to inactivity and back, as is observed in the brood chambers of species of these ants ( Franks and Bryant, 1987). From the observation of individual behaviour it is clearly not possible to predict that a colony could have a rhythmic pattern, even if one adds the observation that an active individual stimulates an inactive one into movement. To show that chaotic individuals plus excitation can generate a rhythm, it is necessary to model the process, as was done by Miramontes et al (1993). The model colonies showed the same behaviour as the real ants, with a rhythmic cycle of activity-inactivity emerging over the colony as a whole at a critical density of the population. The whole system was governed by simple rules defining the chaotic behaviour of individuals and their interaction, and the process is iterated to find out what patterns emerge.
4. Holism.
Emergent order is holistic in the sense that it is a consequence of the interactions between the component elements of the system and is not coded in or determined by the properties of a privileged set of components. A familiar example that comes from biology is the use of cuttings to propagate plants. These can be taken from shoots or rootsany part that is growing has the potential to develop into a whole plant. We see that there is no privileged part of the organism that has the instructions to make a whole from a part. What has this power is the dynamic relationships that characterise the living being, which has the potential for emergent order. This is a condition of dynamic organisation; it is not a set of preordained instructions. The order that emerges can have different degrees of stability, or robustness. In biology there are certain patterns that are extremely stable and have persisted for many millions of years despite continuous extinctions of species that manifest these patterns. Plants again provide a striking example. Although there are currently some 250,000 species of flowering plant, there are only three ways in which the leaves are arranged up the stem. They either have a spiral pattern (the majority), as in ivy; or a whorl of two or more leaves at a node whose position rotates up the stem so that leaves at successive nodes are located over the gaps between leaves in the previous whorl, as in fuschia; or, finally, single leaves that are located on opposite sides as they ascend the stem, as in maize. These are very robust patterns with some fascinating mathematical features describing them, and there are many other examples in biology (see Goodwin, 1994). However there are also less robust patterns such as the forms of many fungi and lichens, which are very responsive to environmental conditions and so do not have any stable shapes, rather like clouds .
5. Fluctuations.
Complex systems in their chaotic state have a distinctive pattern to the fluctuations in the variables. However, this pattern changes as order begins to emerge from chaos. Considering again the case of the ant colony, when there is a low density of ants and they are behaving chaotically, most of the fluctuations in activity involve few ants. However, as the critical density for the emergence of order is approached, transient patterns of activity arise that involve many ants and the fluctuations extend over the whole space of the colony. This is a sign that the collection of chaotic individuals is beginning to become a higher-order unit, a superorganism. As the density increases further, these large-scale transient fluctuations become organised into rhythmic activity patterns with waves that propagate throughout the colony.
Of course the transition can equally well go the other way, from order to chaos, as density decreases in the colony. Then the pattern is from initial organisation over the whole colony, which breaks down through large-scale fluctuations to chaotic patterns of individuals, with pockets of local order in small groups.
6. Edge of chaos.
Emergent processes occur in a region of dynamic space described as the edge of chaos at which there is a mixture of nascent order and chaos, as described above. This region of the dynamic spectrum has a rich and distinctive pattern of fluctuations which can be seen as transient manifestations of the pattern that emerges when parameters (such as the density of ants, above) change such that there is a transition to relatively stable expression of the order. If the system moves far into the ordered regime, particular dynamic patterns may become firmly established and there is a loss of capacity to respond flexibly to an unpredictably changing environment. Detailed studies of the behaviour of the human heart as recorded in electrocardiograms have revealed that, within the stable mean heart rate of a healthy subject, there is a complex pattern of variability between heartbeats with a signature similar to that of chaos (Peng et al 1995, Ivanov et al, 1996). Individuals with cardiac disorders such as arrhythmias often have an ordered pattern of variation between heartbeats. This somewhat paradoxical phenomenon of disease manifesting dynamically as too much order is interpreted as a loss of capacity in the heart to respond flexibly to the unpredictable demands of the body. Senescence is also accompanied by reduced intrinsic variability or flexibility of physiological variables (Lipsitz, 1995). It is recognised that too much chaos or disorder is equally malfunctional in complex systems.
These observations are generalised to mean that complex adaptive systems perform best when their order is not far from the transition to chaos so that their dynamic patterns are both robust and flexibly responsive to context. Furthermore, in evolving systems it is necessary for inappropriate order to be dissolved and replaced by more adaptive behaviour as circumstances change. System behaviour located not far from the transition to chaos is then seen as the best place to be in an uncertain and unpredictably changing world (Kauffman, 1995).
From Quantity to Quality: Intuition and a Science of Qualities
The science of complexity takes us to the threshold of a new relationship with the complex processes that define the context of our lives: the weather, the ecological systems on which we depend for clean air and food, and the social systems, organisations and economies within which we live and which we try to manage. These all appear to fall outside the realm of control and manipulation of the type that is possible with mechanical systems (clocks, cars, computers). However, these types of complex processes are not without their own subtle expressions of order. The collective patterns of ordered activity observed in ecosystems, in colonies of social insects and in human society, can be understood and described as emergent properties of complex systems, arising from the activities and interactions of the component individuals, though not reducible to these. The science of complexity has its focus on the study of these emergent properties, which are intelligible as consistent manifestations of principles of organisation that characterise the systems, but are not reducible to the properties of their component parts.
The question that then arises is how we can best relate to these systems with their subtle emergent order. We cannot control them through manipulation of their parts to achieve predictable, desired results; but we do influence them, for better or for worse. One of the major constraints on conventional science that limits the ability to gain insight into the realm of complex phenomena is the restriction of data to quantifiable, measurable aspects of natural phenomena. These are the primary qualities of things, as described by Galileo, such as mass, position, velocity, momentum, and so on. The qualities are considered to be the only reliable source of scientific information about the world. Secondary qualitiesthe experience of colour, odour, texture, aesthetic pleasure in beholding a deer or a landscapeare not taken to be reliable indicators of objective nature. However, there is no intrinsic reason why this constraint should be accepted. What is required in a science is some methodology whereby practising subjects come to agreement on their observations and experiences. This is the basis of quantitative measurement: acceptance of a method whereby different practitioners can reach intersubjective consensus on their results. Where there is no consensus there is no objective scientific truth.
Why should this not be extended to the observation and experience of secondary qualities? In fact, this extension is practised in the healing professions, whether conventional Western medical practice or complementary therapeutic traditions. The presenting subject's experience of pain and its qualities are certainly used in diagnostic practice; and so are many other qualities such as colour and texture of skin, posture, tone of voice, etc. Paying close attention to these, as well as to quantitative data such as temperature, pulse, and blood pressure, is a significant part of the art of diagnosis. Conventional wisdom accepts that these skills can only be acquired through practice and experience, which hones the intuitive faculty to perceive reliably the underlying condition that is the cause of change from health to disease. Health is in fact an emergent property that cannot be reduced to the sum of quantitative data about different aspects of the body. Its perception requires the healer to pay attention to qualities as well as quantities, and to make use of the intuition in coming to a holistic judgement about the condition presented.
Conventional scientists begin to get very nervous when this type of procedure is described as science. They are suspicious of the intuition, and they mistrust qualitative observation. As far as the intuition is concerned, they need have no anxieties: it is a universally recognised subjective component of scientific discovery. It is the intuitive faculty that makes sense of diverse data and brings them into a coherent pattern of meaning and intelligibility, though of course the analytical intellect is also involved in sorting out the logic of the intuitive insight. What is not practised in science is the systematic cultivation of the intuitive faculty, the capacity to recognise the coherent wholes that emerge from related parts. However, the study of emergent properties in the science of complexity clearly requires use of the intuition in high degree. It is what is required to perceive the subtle order that characterises the holistic properties of complex systemsecosystems, social systems, health. Furthermore, these emergent properties are closely associated with secondary qualities. The health of an ecosystem is reflected in the quality of birdsong as well as in the (quantitative) diversity of species. However, scientists are trained to pay attention only to quantities. As people and as naturalists they are aware of qualities, which are often the primary indicators of change. But as scientists they factor them out of their consciousness. This restriction is based on a convention that has worked extremely well for simple systems, but it has severe limitations in the face of complexity. It is time for the move into a science of qualities.
A science of qualities is not new in the Western tradition. This is the science that was practised by Johann Wolfgang von Goethe in the late 18th and early 19th century. Regarded for many years as an aberration because of an apparent conflict with Newtonian science, Goethe's studies have been largely ignored within mainstream science. However, it is now evident that Goethe's approach to natural processes is not so much in direct conflict with the dominant science of quantities as different from it (c.f. Bortoft, 1996). In Goethe's study of colour, for example, which is where he ran into trouble for challenging Newton's colour theory, an explicit goal is to understand not simply the conditions under which various colours emerge, but also to relate this to the experience we have of different colours, i.e., their qualia. The assumption is that our feelings in response to natural processes are not arbitrary but can be used as reliable indicators of the nature of the real processes in which we participate. Qualities include the realm of the normative, our assessment of the rightness or wrongness, appropriateness or inappropriateness, of particular actions in relation to our knowledge. A science of emergent qualities involves a break with the positivist tradition that separates facts and values and a re-establishment of a foundation for a naturalistic ethics (Collier, 1994).
Participation now enters as a fundamental ingredient in the human experience of any phenomenon, which arises out of the encounter between two real processes that are distinct but not separable: the human process of becoming and that of the other, whatever this may be to which the human is attending. In this encounter wherein the phenomenon is generated, feelings and intuitions are not arbitrary, idiosyncratic accompaniments but direct indicators of the nature of the mutual process that occurs in the encounter. By paying attention to these, we gain insight into the emergent reality in which we participate. Of course there are idiosyncratic, personal components of the insight, just as there are idiosyncratic elements to the integrating theories that come with flashes of intuitive insight to individual scientists. These need to be distinguished from the more lasting and universal aspects of the insight, which is where the process of intersubjective testing comes in to find consensus amongst a group of practitioners. The same type of process is required to evaluate the insights gained from use of qualities of experience to understand the subtle order of complex systems.
The sensitivity of these systems to initial conditions means that we must be exquisitely careful and finely tuned to the process we seek to influence beneficially in order to monitor our effects, as in any healing process. This requires training that goes beyond what is cultivated in quantitative science. The additional components are the systematic cultivation of the intuition as a way of perceiving the integrity of healthy wholes and hence the capacity to see disturbances from health; and training in the ability to distinguish the idiosyncratic from the universal in the perception of qualities via intersubjective comparison. These are basic ingredients of a science of qualities. In a sense they are no more than a statement of what holistic practitioners have been engaged in. However, it is time to develop such a science systematically as an extension of quantitative science in a direction that is appropriate to the urgent needs of our age.
The social sciences have notoriously followed the physical sciences in attempts to identify and measure primary qualities, with arguably little success. In economics, for example, the focus on what can be measured, particularly Gross National Product, has led to what Daly and Cobb have called the "fallacy of misplaced concreteness" (Daly & Cobb, 1990), so that we the constructs of our measurments as economic facts. Shotter makes a similar point, suggesting orthodox social sciences can lead to "misleading realism" (we explore Shotters contribution below). In management science Mitroff has recently challenged the orthodox view by arguing that "truth is not solely a property of formal propositions", not, in our terms, based on the discovery of primary qualities, but is a "human activity that must be managed for human purposes": epistemology then becomes the "management of truth". (1998:70). Writing about qualitative research, Lincoln and Guba (Lincoln & Guba, 1985) have pointed out that all observations are theory laden, and so the search for such primary qualities is misguided.
Over recent years there have been many moves toward a science of qualities in social and management sciences, many of which can be seen as dimensions of an extended epistemology: there are ways of knowing other than the empirical and the rational which characterise traditional Western Science (Gergen, 1994; Heron, 1996, 1971). In particular, these various moves assert that knowing lies not so much in the mind of individual actors, but arises in relationship and through participation (Heron & Reason, 1997): as Gergen asserts, not cogito, ergo sum, but communicamus ergo sum (Gergen, 1994:viii).
Maybe most celebrated and acknowledged, although still not integrated with conventional research, is Polanyi (1962), who described clearly his concept of tacit knowledge, a type of embodied know-how that is the foundation of all cognitive action. He rejected the notion of the objective observer in science or any other area of inquiry, expressing his belief in engaged practice that necessarily joins facts and values in a participatory mode of understanding.
Writing more recently, Shotter argues that in addition to Gilbert Ryles distinction between knowing that and knowing how there is a "kind of knowledge one has only from within a social situation, a group, or an institution, and thus takes into account& the others in the social situation" (Shotter, 1993:7, emphasis in original). It is significant that Shotter usually uses the verbal form knowing of the third kind, to describe this, rather than the noun knowledge, emphasizing that such knowing is not a thing, to be discovered or created and stored up in journals, but rather arises in the process of living, in the voices of ordinary people in conversation.
Shotter draws on a social constructionist perspective, while Park (forthcoming 1999), writing in the context of participatory research and drawing on the emancipatory traditions of Freire (1970), Habermas (1972) and others, has identified representational, relational and reflective forms of knowledge. Representational knowledge provides explanation through identifying the relationship between discreet variables; or understanding through interpretation of meaning. Relational knowledge is the foundation of community life and its development fosters community ties as well as helping create other forms of knowledge. Reflective knowledge has to do with normative states in social, economic and political realms, it concerns a vision of what ought to be, what is right and what is wrong, and arises, Park argues, through the process of consciousness raising, conscientization.
Reflective knowledge& instils conviction in the knower, and the courage to go with it, and commits him or her to action. (Park, forthcoming)
Abram, drawing on the tradition of phenomenology, and in particular Merleau-Pontys phenomenology of perception, shows how perception itself is based in relationship so that
... in so far as my hand knows hardness and softness, and my gaze knows the moon's light, it is as a certain way of linking up with the phenomena and communicating with it. Hardness and softness, roughness and smoothness, moonlight and sunlight, present themselves in our recollection not pre-eminently as sensory contents but as certain kinds of symbioses, certain ways the outside has of invading us and certain ways we have of meeting the invasion (Merleau-Ponty, 1962:137)
We do not discover primary qualities but participate in relationship with qualia. As Abram has it, this means that there is
underneath our literate abstractions, a deeply participatory relation to things and to the earth, a felt reciprocity.... (Abram, 1996:124)
From a feminist perspective, Belenky and her colleagues wrote of womens ways of knowing (Belenky, Clinchy, Goldberger, & Tarule, 1986) which distinguished between connected and separated knowing: separated knowing adopting a more critical eye and playing a doubting game, while connected knowing starts with an empathic, receptive eye, entering the spirit of what is offered and seeking to understand from within. Feminist scholars generally have emphasized relational aspects of knowing (e.g. Bigwood, 1993) and of the practice of management (Fletcher, 1998; Marshall, 1995).
Torbertwho builds on the foundations offered in Argyris work (e.g. 1985), but has extended it considerably to draw on constructive developmental theory and the traditions of search for an integrative quality of awarenessdescribes the process of developmental action inquiry as addressing three questions: how to develop a quality of awareness that attends both to its origins and to action in the world; how to create communities of inquiry; and how to act in a timely manner (Torbert, forthcoming 1999). Torberts work has emphasized the importance of a quality of attention which moment to moment is able to interpenetrate four territories of attention: an intuitive knowing of purposes, an intellectual knowing of strategy, an embodied, sensuous knowing of one's behaviour, and an empirical knowing of the outside world. Action inquiry is thus described as
an attention that spans and integrates the four territories of human experience. This attention is what seems, embraces, and corrects incongruities among mission, strategy, operations and outcomes. It is the source of the true sanity of natural awareness of the whole. (Torbert, 1991:219)
Finally, we have argued (Reason, 1994; Heron & Reason, 1997; Reason & Torbert, in preparation) for a participative paradigm for inquiry in the social sciences, in which it can be seen that a knower participates in the known, articulates a world, in at least four interdependent ways: experiential knowing, in which we resonate with the presence of other, presentational knowing, which draws on aesthetic imagery, propositional knowing which draws on concepts and ideas, and practical knowing, which consummates the other forms of knowing in action in the world. We have defined co-operative inquiry as a systematic process of action and reflection in which co-inquirers cycle through this extended epistemology (See Table 1).
While all these descriptions of extended epistemologies differ in detail, they all go beyond orthodox empirical and rational Western views of knowing, and assert, in their different ways, that knowing starts from a relationship between self and other, through participation and intuition. They assert the importance of sensitivity and attunement in the moment of relationship; they assert the importance of knowing not just as an academic pursuit but as the everyday of acting in relationship and creating meaning in our lives. They thus echo the science of qualities to which the postmodern biology points, and invite us to consider how to establish an organizational science of qualities. But before we can do this, we need to consider in more detail the relevance of complexity theory to organizational life and human knowing.
Organizations as complex wholes
Is it reasonable to apply theories which have their origins in the natural and biological sciences to social life and to organizations? And if we do so, are we simply employing metaphors, rather than making a sound epistemological argument? These are questions with which reviewers of an early version of this paper challenged us. We will first argue that metaphor lies at the basis of all theorizing, and go on to argue that there are sound reasons for arguing that organisational and social life can be understood as a complex system and that such a perspective, metaphorical or not, can be seen as what Gergen describes as generative theory.
As Lakoff and Johnson argue
& metaphor is pervasive in everyday life, not just in language, but in thought and action. Our ordinary conceptual system, in terms of which we both think and act, is fundamentally metaphorical in nature (Lakoff & Johnson, 1980:3)
Morgan builds on Lakoff and Johnson, on Pepper (1942) and others, to show how
our theories and explanations of organizational life are based on metaphors that lead us to see and understand organizations in distinctive yet partial ways& [M]etaphor exerts a formative influence on science, on our language, and on how we think, as well as on how we express ourselves on a day-to-day basis (Morgan, 1986:12-13)
So it would seem there is a good basis for arguing that metaphor is at the basis of all theory. Shotter takes this further, arguing that
& our disciplined ways of knowing are founded, or rooted in, and relevant to, rhetorically organized, two sided, everyday traditions of argumentation (Shotter, 1993:1)
Shotter later asserts that we must be wary of knowledge formulated as system, for talk of systems leads to a "misleading realism", which suggests that "everything of importance is already in existence" and fails to acknowledge the ways in which relationships are "self-constructed" and "essentially unsystematizable" (p. 59). We should rather seek a "poetics of relationships, a way of talking that leaves their precise nature open" (p. 59), that allow for what he (quoting Ingold) describes as "the generative possibilities of the relational field&." (p. 61).
The question, then, is not whether in applying complexity theory to organizational and social life we are being metaphoricalit would seem that metaphor is unavoidable. The first question, rather, is whether we can see through our metaphor (Hillman, 1975), to use the metaphor rather than having it use us, so to speak, and avoid the trap of reifying our metaphor and applying it indiscriminately. As Skolimowski has pointed out, one of the tragedies of Western civilization has been the indiscriminate use of the machine metaphor. And a major contribution of the deconstructionist movement has been to demonstrate the unconscious way in which we employ metaphors such as growth and progress to underpin our worldview (Gergen, 1994; Harvey, 1990). And the second question is whether we can use metaphor in a creative and transformative way, to open new up realities and new resources:
Concepts of human conduct operate much like tools for carrying our relationships. In this sense, the possibility of social change may be derived from new forms of intelligibility& I [have] proposed the term generative theory to refer to theoretical views that are lodged against or contradict the commonly accepted assumptions of the culture and open new vistas of intelligibility. (Gergen, 1994 #441:60; emphasis in original)
So we argue that, while of course complexity theory is a metaphorical construct, it is a construct which is in Gergens sense generative when applied to social life and to organizations, and we will continue to show that it draws our attention to particular qualities of postmodern inquiry which provide support for emerging approaches to organizational inquiry.
So we now turn to show how it is helpful to see social and organizational life as a complex, self-organizing process. Indeed, we have already hinted at this in drawing on Shotters argument that relationships are self-constructive and have generative possibilities. Shotter argues that relationships take the form of joint action, in a zone of uncertainty somewhere between individual action and natural event:
The most obvious circumstance in which joint action occurs is in dialogue with others, when one must respond by formulating appropriate utterances in reply to their utterances. What they have already said constitutes the situation on hand, so to speak, in which one must direct ones own reply. It is thus clear why, in such circumstances, we as individuals do not quite know why it is that we act as we do: rather than speaking out of an inner plan& we speak into a context not of our own making, that is, not under our own immediate control. Thus the formative influences shaping our actions are not there wholly within us, prior to our actions, available to be brought out ahead of time (Shotter, 1993:4)
This seems to us to be a description of a complex self-organizing process which cannot be understood in linear terms ("not under own immediate control"), nor in terms of the properties of the parts (individuals) but rather unfolds with emergent relational order. No wonder Shotter argues that we need a poetic, where "the word poet is derived from the Greek poietes = one who makes, a maker, and artificer" (Shotter, 1993:64). Our view that Shotters perspective is congruent with complexity theory is supported by his own references to Prigogines account of dynamic structures
created and maintained (by being continually reproduced) within& continuous but turbulent structuring processes& (Shotter, 1993:66)
He goes on to say that a relationship cannot be conceived as constructed out of elementary particles:
Whatever its elementary components we can be sure they are in some sense relational, that is to say, they only exist as sensibly distinct, novel moments within an otherwise flowing totality. In other words, there is no point in thinking of relational fields and the nature of their generative potentials as systematically ordered things, they are loci of activity. Although they have no specifiable form, they can be specified by their formative powers. (Shotter, 1993:67)
More generally, the constructionist perspective argues that our world, and our knowing of it are best seen as created rather than given:
knowledge and truth are created, not discovered by mind (Schwandt, 1994:125)
The terms and forms by which we achieve understanding of the world and ourselves are social artifacts, products of historically and culturally situated interchanges among people (Gergen, 1994:49)
In arguing for a participative paradigm for inquiry, we argued that human presence meets given reality through participating in its being, "in its experiential participation in what is present, in what there is" (Heron & Reason, 1997:277). Thus human knowing is rooted in experiential encounter with the world, and, while sharing with the constructionist perspective the view that our world is creation that arises from the interaction of an unknowable given world and the human mind, we argue that constructionist writing does not attend sufficiently to this experiential dimension of knowing:
& the point about experiential knowing is that the very process of perceiving is also a meeting, a transaction, with what there is. When I hold your hand, my tactual imaging both subjectively shapes you and objectively meets you. To encounter being or a being is both to image it in my way and to know that it is there. To experience anything is to participate in it, and to participate is both to mould and to encounter, hence experiential reality is always subjective-objective. (Heron & Reason, 1997:278)
So we argue that since our world, and our knowing of it, can be seen from constructionist and participatory perspectives to be emergent and self-organizing, then the principles of complexity theory may well help illuminate the process.
Turning specifically to the use of complexity theory to account for organization, we can best draw on the work of Stacey and his colleagues at the Complexity and Management Centre at the University of Hertfordshire (Stacey, 1992, 1995, 1996; for a broad range of contributions to this debate see also Business Process Research Centre, 1998). Stacey argues that we should pay attention to complexity theory because
organizations are nonlinear, network feedback systems and it therefore follows logically that the fundamental properties of such systems should apply to organizations (Stacey, 1995:481)
Organizations will therefore be characterized by bounded instability and spontaneous self-organization and emergent order. Stacey continues to demonstrate the significance of this perspective for the study of organization, drawing on the theoretical strands very similar to those in the first sections of the present paper. He goes on to argue that if organizations are best understood as complex systems this has major implications for the approaches to inquiry:
The reductionist approach of testing hypotheses about causality independently of each other assumes that the systems being studied are linear, or can be approximated to linear systems&. From a complexity perspective, however, organizations are essentially nonlinear systems which cannot be approximated to any linear form and to be creative have to operate far from equilibrium& reductionist approaches to researching them are likely to produce seriously misleading conclusions. (Stacey, 1995:493)
Thus we argue that it is quite appropriate to apply complexity theory to an understanding of social and organizational forms and turn to consider the nature of a science of qualities in organizational research.
Toward a science of qualities in organizational research
In their magisterial introduction to the Handbook of Qualitative Research, Denzin and Lincoln (1994) identify a series of "moments" or "successive sets of new sensibilities" in the story of qualitative research, an account of the move from the clarity and unity of a positivist perspective rooted in a clear sense of Northern World superiority, to current times of relativism, pluralism and constructivism. Their first moment is the 19th century colonial enterprise of understanding primitive people; the second is the positivist mode which becomes the dominant approach to social science by the third quarter of the 20th century. After World War II, an interpretivist mode emerges which is pluralistic, interpretive, and open ended, taking cultural representations and their meanings as being appropriate points of departure in the social sciences. Denzin and Lincoln suggest that the in present moment, a time of enormous ferment, scholar/practitioners committed to qualitative inquiry face the twin crises of representation and legitimation: "Is it possible to represent what our experience was in some way that we can characterise as having integrity and fidelity?" "If we cannot claim to create texts which are objective and wholly true, from where do we derive our authority and our legitimation as social scientists?" (Lincoln, 1997:7)
If this is true for qualitative research, it is even more true for participative forms of action research, for here scholar/practitioners are not primarily interested in producing texts, but in opening the possibility of transformative action through first-, second- and third-person research/practice (Gergen, 1994; Reason & Torbert, in preparation). The scientific merits of action research have been a contentious issue, debated for at least three decades since the celebrated Susman and Evered paper in Administrative Science Quarterly (1978), which we are addressing elsewhere (Reason & Torbert, in preparation). Here we wish to argue that the principles of complexity theory lead us toward a science of qualities in organizational and social research, just as it is beginning to do in the natural sciences. We will do this by drawing on the six dimensions of complexity theory discussed above and illustrate our argument by drawing in particular on our experience with the process of co-operative inquiry (Heron, 1996; Reason, 1998; Reason, forthcoming; Reason & Heron, 1995; Reason & Heron, 1996).
Rich interconnections
The touchstone of a science of qualities is experiential, participative knowing, Shotters knowing of the third kind which arises through relational engagement: a deep and intimate sense of connection is sought with the phenomena being studied. While this can be approached through observation, interviews and other forms of qualitative data gathering, rich interconnections are most fully developed through participative inquiry in which the object of inquiry is experience and action within ones own life world in collaboration with ones peers. For example, in co-operative inquiry all those engaged in the inquiry venture work together as co-researchers, contributing both to the ideas that form the basis of the inquiry, and to the action which is its focus; they explore their own and each others experience and action through a sustained process of inquiry, typically meeting over several months, allowing experiential contact to develop at many different levels (see Heron (1996) for a full description of co-operative inquiry). This inquiry process brings about an intimate and critical encounter with the phenomena being explored, producing a rich sense of experiential knowing: what gestalt practitioners would describe as good contact (Herman and Korenich, 1977), opening to the presence of the experience.
High quality research/practice also requires rich interconnections among those involved in the inquiry, whether they be the co-researchers of a co-operative or appreciative inquiry (Cooperrider & Srivastva, 1987), the community engaged in participatory research (Fals-Borda & Rahman, 1991), insider/outsider relationship (Louis & Bartunek, 1992). Co-researchers can provide each other with support and encouragement; they can challenge blind spots and defensiveness both in individuals and in the culture of the group. Beyond this the group can provide a living container for the emergence of new order, new ideas and new practice. For a dynamic culture of inquiry, with diversity of viewpoint and complex internal communication, can be seen as having the qualities of an excitable medium, a term complexity theorists (Goodwin, 1994) use to describe the capacity of a system to generate pattern spontaneously. Complex, nonlinear interactions result in a dynamic field which is self-organizing. An inquiry group exhibiting the qualities of an excitable medium will find new patterns emerging from its own dynamics, which will involve a mixture of order and chaos of the type which is described above as 'living at the edge of chaos'.
This argument for high quality connections is of course in contrast to some forms of qualitative research, in which contact is made only through interview or relatively distant observation, and certainly in contrast to those forms of quantitative research in which contact is made only through pre-determined measurements. In our view, it is not possible to conduct a science of qualities except from a place a rich mutual engagement, a place which opens the inquiry community to experiential, tacit knowing. This invites imaginative representation, if possible through multiple media, so that the richness of experiential contact is articulated and its potential meanings explored. It invites creative and challenging use of ideas and theories, with speculative theory building which nevertheless remains close to the experience. And it leads toward bold and original practice, taking novel experimental action into the field of practice with courage and commitment. Complexity theory suggests to us that these rich interconnections are not simply a way of logically saturating our data in order to confirm that data represent the phenomena being studied, as theorists of qualitative research would argue (Glaser & Strauss, 1967; Lincoln & Guba, 1985); they are the very ground from which new order may emerge.
Iteration
As Shotter argues, the form of relationship emerges over time through the process of action and interaction; and as we described above, complexity theory describes how novel form arises through cycles of iteration in which a pattern of activity is repeated, giving rise to coherent order.
Applying these ideas to the process of group development shows how unique and complex form emerges from very simple principles. Many theories of group development trace a series of phases of development in the life of a group. Early concerns are for inclusion and membership. When and if these needs are adequately satisfied the group focuses on concerns for power and influence. And if these are successfully negotiated they give way to concerns for intimacy and diversity in which flexible and tolerant relationships enable individuals to realize their own identity and the group to be effective in relation to its task (see for example Srivastva, Obert, & Neilson, 1997). This phase progression model of group behaviourin which the groups primary concern moves from issues of inclusion to control to intimacy (which the Srivastva paper bases on Schutz (1958) original formulation), or from forming to norming to storming to performing (Tuckman, 1965); or from nurturing to energizing to relaxing (Randall & Southgate, 1980)is easy to express in propositional terms. But however accurate this may be as a statement of the parameters within which group life unfolds, each actual group unfolds these processes in its own particular fashion. Every group becomes a unique product of human interaction which is impossible to fully describe, not simply because the map is not the territory, but because the territory is in a continual process of emergence. Each group evolves a rich originality while conforming in principle to the same pattern, analogous to a Mandelbrot set (although far more complex).
Many descriptions of qualitative and action-oriented research methods describe an iterative cycle of data-gathering and sense-making, or of action and reflection. Lewin first described the process of action research in the 1940s as a cycle of planning, action, and evaluating. Glaser and Strauss (1967) articulation of grounded theory describes a constant comparative method of moving between data gathering and theory generation, and Lincoln and Guba (1985) place a cycle of purposive sampling, inductive data analysis, grounded theory, and emergent design at the centre of their description of naturalistic inquiry. Recently, Greenwood and Levin (forthcoming) have taken the argument forward, pointing out that the physical and natural sciences take the form of a highly iterative and dynamic activity involving repeated action-reflection- action cycles in which thought and action cycle around each other repeatedly (check reference in book on publication).
The iterative process is also central to the work of a co-operative inquiry group: the inquiry process cycles through phases of action and reflectionor more accurately between phases of experiential, presentational, propositional and practical forms of knowingin which the same realm of experience is visited on several occasions. The group may choose convergent cycling, in which one aspect of experience is explored in increasing depth over several cycles; or divergent cycling so that different aspects of experience are explored and the group can see particular experience in a wider context; or both. Through convergent cycling the co-researchers are checking and rechecking their discoveries with more and closer attention to detail. Through divergent cycling they affirm the values of heterogeneity and creativity that come with taking many different perspectives, and they acquire a systemic view of the phenomena.
As we learn from complexity theory, convergence and divergence together contribute to the building of a fractal structure, which is a mathematical description of the rich complex wholes we see both in the natural world and, as we suggest above, in social processes such as groups. The iterative process of research cycling moves people away from linear cause-and-effect thinking into a cyclical, ecological mode., which in some sense in which this reconnects people with what Bateson (1972) would describe as the circuits of Mind rather than the arcs of conscious purpose. Our understanding of the world becomes more complex, interconnected and holistic: poetic, as Shotter (1993) might describe it, rather than systematic.
In this way, a science of qualities elaborates the pattern in both its uniqueness and its generality. The orthodox distinction between emic and etic research is superseded in that the single case contains the general as iteration proceeds. Complexity theory provides some support for Carl Rogers' intuition, of many years ago, that when you travel to the unique heart of a person you find yourself in the presence of eternal truth. As you peel off layer after layer, every aspect of the uniqueness is expressing the core, and one can learn both to appreciate the principle while honouring its unique manifestation. From this perspective, a reductionist approach to inquiry which starts from establishing linear causal propositions is clearly inadequate. In particular, we need to move away from prediction, and move to an exploration of emergence.
Emergence
The order of a complex system is not predictable from the characteristics of the interconnected components nor from any design blueprint, but can be discovered only by operating the iterative cycle, despite the fact that the emergent whole is in some sense contained within the dynamic relationships of the generating parts. In a science of qualities, the interactive process, given rich interconnections and deep engagement, will lead to emergent order. A science of qualities, as a form of bounded instability, is radically unpredictable. As Lincoln and Guba put it
& within the naturalistic paradigm, designs must be emergent rather that preordiate: because meaning is determined by context to such a great extent; because the existence of multiple realities constrains the development of a design based on only one (the investigators) construction; because what will be learned at a site is always dependent on the interaction between investigator and context, and the interaction is not fully predictable; and because the nature of mutual shapings cannot be known until they are witnessed. All these factors underscore the indeterminacy under which the naturalistic inquirer function. The design must therefore& unfold, cascade, roll, emerge (Lincoln & Guba, 1985:208-209)
The principle of emergence is similarly central to co-operative inquiry. It is not possible to set up a co-operative inquiry and expect it to work in a particular way; rather the form of the inquiry process emerges in response to the particular people involved and focus of inquiry, the context, and so on. Just as the rhythm of the ant colony emerges through the interaction of its members, and the pattern of a Madelbrot set emerges through iteration with divergence and converge, so the process of co-operative inquiry emerges over time. The knowing is in the active, iterative process of co-creating a world through aware action, not in a goal or outside purpose.
It also appears from experience that the precise focus of inquiry can only emerge through the process of iterative inquiry cycles. An inquiry may be launched with a particular set of concerns and interests that the participants wish to explore. They may think they know exactly what they want to find out, or they may know that their interests lie within a general area. But the actual outcome arises from the unpredictable emergent process of the group and of the inquiry cycles. It is not possible to set up a co-operative inquiry group with a specified goal; it is only possible to facilitate its emergence. This means establishing an iterative process, nurturing a deep expe
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