CAS-CCO dynamic system analysis framework
for communications and organisational systems.
Exploring the validity of a conceptual framework composed of Complex Adaptive Systems theory and Communication Constitutes Organisation theory. A macroscopic overview of the potential usefulness of developing an analytical tool based on an emerging marriage of mutually constitutive complex relationships in social systems using a trifold approach of complexity, communications, and organisational theories.
– Rebecca Johnson –
University of Calgary
Table of contents
Overview of theories to be employed…6
Traditional models of thought… 6
The importance and applicability of CCO theory… 12
What is CCO?.. 12
The four flows of CCO… 13
The four flows… 14
Why apply CAS to CCO?..15
Fundamentals of complexity… 18
Three key indicators of a Complex adaptive system (CAS)…21
Why develop a framework combining CCO and CAS?… 23
Key attributes of a CAS-CCO framework…26
Participation & Collaboration… 27
Relinquish Control… 27
Innovation and creativity… 27
Social awareness and ethical responsibility…28
Knowledge sharing… 29
Characteristics of organisations in relation to CAS and CCO theories… 30
Boundaries – The Edges…30
Desire for health and success… 31
Desired attributes of a CAS-CCO framework…31
Real world application of a CAS-CCO framework…33
1) Many components and interconnectivity combined with Large Scope… 35
2) Interacts with external systems…35
3) Amplified perturbation behaviour…36
4) Freedom for flexibility and self-structuring…36
5) Emergence… 37
Appendix A: Terminology…44
This paper aims to explore the validity and usefulness of applying complexity theory to the communication structures of organisations. The modern communications theory of Communicative Constitution of Organisations (CCO hereafter) is a model that takes a more complex and dynamic systems approach to how communications form, affect, and constitute organisations compared with more traditional linear and reductionist approaches. Thus, CCO is an excellent point at which to bridge epistemological understanding of organisations derived from the seemingly disparate fields of strategic communications and of complexity science. In particular this paper will be examining CCO theories that are grounded in action, notably the four-flow theory proposed by McPhee and Zaug. This four-flow approach examines how differing “flows” and “cross-currents” constitute organisations as dynamic systems. There have been gaps identified in CCO theory: “schools of thought [of CCO theory] address elements, forms and CCO relationships, but only a few of them identify the types of dynamic processes that intertwine communication and organisation in a CCO relationship. Thus to expand CCO theory, scholars need to focus on the kinds of processes and interrelationships among them that occur in the ongoing streams of organizing” (Putnam et al., 2007 p.9). McPhee and Zaug’s four-flow theory addresses this, however, their approach can be seen to be at risk of providing a reductionist approach to what is essentially an emergent phenomenon.
This paper proposes that Complex Adaptive Systems theory (CAS hereafter), could provide additional support to the four-flow model of CCO theory and thus assist in developing a more encompassing framework. The author’s goal is that a blended framework of CCO and CAS would serve as a tool for broader and deeper observation of the processes and nature of organisations and social systems, with the aim of giving strategic communication leaders wider perspective on the dynamics of an organisation and its external relationships so that they can make more informed decisions. It is the author’s vision that the future of strategic communication leadership, when approached with a greater awareness of the philosophies of complex adaptive systems and how they can be applied to organisational management, will result in more robust, adaptable and innovative systems.
A fundamental shift is required to achieve this; in relinquishing traditional cognitive processes of linearity and using cause and effect behaviour to orchestrate predictive outcomes, a CAS-CCO approach would facilitate a strategic communication leader to make adjustments to a system to keep it in dynamic homeostasis thereby giving a secure platform for emergence and innovation to flourish. Ultimately, should this proposed framework prove useful, a Statistical Analysis System (SAS) template could be built to assist strategy leaders in mapping out the dynamics of their system using the insights of CCO and CAS.
Traditional linear and reductionist models of organisations as objects in which communication “happens” are now more commonly seen to be yesterday’s attitudes of organisational theory. It is increasingly obvious that we live in a far more complex, inter-connected and dynamic world than older, static models can accurately describe. Over recent years there has been a great deal of interesting and illuminating research into “communication-organization relationship[s]” (Putnam & Nictoera, 2009) as flexible, dynamic and constituting acts. These more constructivist approaches employ grounded action perspectives to gain a deeper understanding of the symbiotic nature of organisations and communications. These approaches to communication and organisational theory are strongly aligned with the ontological philosophies of complex adaptive systems. It is possible that they are simply addressing the same processes in different language, but by comparing contrasting rhetorics of the same phenomenon new insights can be gained. In the author’s opinion, even in the case of substantial overlapping, there is clear benefit to examining relationships between the two theories. Identifying bridges and similarities, as well as divergences and differences, should uncover a number of cross-over benefits resulting in the emergence of new ideas and perspectives.
In the preface to Building Theories of Organisation (Putnam & Nictoera, 2009) a key stumbling block for unpacking CCO is stated as, “both communication and organisation are abstract constructs that are difficult to anchor individually as well as interdependently. Thus, unpacking one concept often leads to anchoring the other one as an abstraction” (Putnam et al., 2009). The author posits that a simplified and non-mathematical description of complexity theory may provide an encompassing framework of multifaceted value for modern understandings of the interrelationships and dynamical process of communication within, and as constitutive to, organisations. Perhaps the language used to describe complex systems could assist communications scholars to “articulate similarities and differences among perspectives” (Putnam et al., 2009 p.2) more clearly.
It is the author’s contention that should a theoretical framework of communications in organisations, built from both complex adaptive systems theory (CAS) and communication constitutes organisation (CCO) theory, be successfully constructed and explained in fairly straightforward language, that a more holistic approach to understanding how organisations arise, change and grow or die, would ensue. In such a unified approach both the concepts of communication and organisation, as well as the dynamic flow and crosscurrent theories of CCO could be encompassed in a complex adaptive framework that interlinks with other external constructs of ontological relevance. The language of complexity theory could also assist CCO theorists in applying nomenclature for a structural framework of elements through which communication can flow, affect and be shaped by. Application of the principles of CAS to CCO could provide scope for new avenues of research that may in turn yield a greater understanding of how complex organisations evolve and react from a communications perspective.
The author aims to explore the most relevant ideas from the theories of CAS and CCO, and current academic writings on complexity theory in relation to communications systems. The goal is to determine if there is merit for further research, construction of a framework and a proposal for specific, real world testing. As the ideas here are broad and prone to abstraction, an application of a proposed framework to an existing dynamic organisation would provide a valuable tool for exploring the validity of this avenue of thought. A prime candidate for a real world case study would be a national or global social movement, activist organisation or non-governmental organisation that has a dynamic structure to facilitate adaptability and innovation. In the author’s opinion such an organisation would be more likely to lend itself to adaptive behaviour due to its greater flexibility, spontaneity and emergent behaviour in comparison with a traditional, more structured business model. Once established, the framework could be retrofitted to a commercial or government organisation that leans toward more rigid structures but that desires to increase their adaptability and innovation.
The fields of both Organisational theory and Communications theory are vibrant, multi-faceted and constantly evolving areas of thought with many diverse opinions on how to view and analyse social science systems; yet whilst many scholars have attempted to break pre-defined patterns of thinking about and unpacking a system, we are often held prisoner by a form of empiricism that relies heavily on causality and predictability. Obviously empirical and inductive reasoning has served us well as a civilisation and should not be abandoned, rather the author suggests to add a new layer to traditional reasoning to accommodate for our modern, highly complex and rapidly changing world.
Traditionally, organisations were viewed as static objects. Classical models of communications within an organisation have a very linear and hierarchical approach; in the strictest traditional models information flows from the top to the bottom. In her article “Relationships and Participation: A Complexity Science Approach to Change Communication”, Ursula Ströh defines this as, “general strategic management views of structured planning and top management decision-making” (2007). Stroh explores the potential pitfalls of this approach and gives as an example the IBM crisis of the 1990s. For close to a century, IBM was a textbook example of a traditionally structured organisation that maintained a uni-directional flow of information and control; by the 1990’s this model started to break down as the company was failing to adapt to the changing times. Ströh showcases how the 2002 organisational feedback experiment, conducted under the leadership of Sam Palmisano, to reverse the flow of information and create a participatory environment had significant positive impacts on the company (Hemp & Stewart, 2004).
The application of complexity theory to organisational theory is not new, “Since the open-systems view of organisations began to diffuse in the 1960s, complexity has been a central construct in the vocabulary of organisation scientists” (Anderson, 1999, p.216). There has been a large amount of research into applying complexity theory to organisational theory, in some cases it appears to be applied with accuracy and provides benefit to understanding organisational processes. However, complexity theory has also been applied rather loosely in popular culture notably in business genre books as well as in the health sciences as noted by Rickles et al. (2007); this looseness can lead to ambiguity and an incomplete or inaccurate application of fundamental principles. Complexity has been less frequently applied to communications theory (although that is not to say there are not some excellent scholarly writings on the subject); even less do we see the tri fold combination of complexity, organisational and communication theory.
In the author’s opinion, a more scholarly application of the principles of CAS theory to communications theory could greatly assist to fill in some gaps of knowledge and discourse in communications theory, or at the very least provide an alternative rhetoric to discuss areas of communication theory that have received less mainstream attention. For instance, one failing of traditional models of communication theory is to often ignore the meaning and power of the message itself, once it has been sent. Van Djik discussed this phenomenon, “One central element in mass communication processes, viz. the ‘message’ itself, has received little autonomous attention in mass communication research” (1985). Once a message is broadcast it can often stand alone or apart from the intent of the sender, a concept that was explored in depth by McLuhan (1964). Giving agency to the message itself indicates a far more complex set of relationships in the communication process than is described by traditional linear models. This example exhibits how the nuances of communication flows in organisations are not accommodated in traditional theories, which leads to a less than holistic representation of reality. The dynamics of CAS theory would easily embrace the agency of the message itself and facilitate a communications strategist to plot system effects of the message as being perhaps different to the intent of the message.
Despite many new avenues of research into complex adaptive behaviour in organisational theory traditional methods of epistemology have constructed within us a bias toward reductionism and linearity. Reductionism focuses on breaking down a whole into its parts, analysing the mechanics of those parts and then using deterministic reasoning to construct predictions of the behaviour of a system. Whilst this approach can be useful and indeed has been fundamental to our scientific evolution since the Enlightenment era, it has caused us to have an inferential myopia when analysing a system. This deterministic myopia blinds us when developing research into how a system may spontaneously evolve and innovate. Often when complexity thinking is applied to understanding a system in the social sciences it appears to be done in a reductionist way that whilst the language is attempting to address more emergent and self-structuring behaviour, it is in essence modelled on linear thought patterns. Correctly utilising the rhetoric of CAS theory enables a communication strategist to express and thus cogitate in a non-linear manner. Many communication scholars have explored the idea that language affects human consciousness; Walter Ong (1912-2003) perhaps the most historically notable proponent of this idea, discussed at length the concept that language and writing dramatically affect consciousness. If we have better language to describe complex phenomenon we observe, then it is likely that we will more easily observe the phenomenon in the first place!
Modern physics has perhaps led the charge in opening our cognitive perception of the universe to non-linear and non-deterministic paradigms. Using these concepts as examples, future research into how CAS could be applied to organisational-communication theory could perhaps better embrace a more accurate descriptive language that reflects the nature of complex systems including the inherent uncertainty built into any complex system. Heisenberg very eloquently brought traditional linear bias to attention when he discussed our reliance on the reductionist approach of causality, “the nineteenth century developed an extremely rigid frame for natural science which formed not only science but also the general outlook of great masses of people… this frame was so narrow and rigid that it was difficult to find a place in it for many concepts of our language that had always belonged to its very substance” (1958, P.137). Heisenberg warns of the perils of using only reductionist methods to understand the world around us. With the early to mid twentieth century developments of Relativity, Uncertainty, Paradox and Quantum mechanics, there was a shift from the traditionally deterministic and Newtonian paradigms of analysing a system toward cognitive schemas that embraced uncertainty, emergence and holistic observation. For instance, Heisenberg’s discourse on the effects of humankind on its physical environment is encapsulated as, ”One may rather consider it as a biological process on the largest scale whereby the structures active in the human organism encroach on larger parts of matter and transform it into a state suited for the increasing human population.” (1958, p.131). An astounding concept and one that is found mirrored in the works of Kauffman (1994) in his proposal of the self-organising nature of life and adaptability of a system being a greater concept than (albeit encompassing of) Darwinian ‘survival of the fittest’. In this schema we can see properties of self-structuring, adaptability and emergence, all fundamental qualities of complex adaptive systems. Fifty years later we are still coming to terms with the implications for such a dramatic shift in thinking. Unfortunately, as the language was not wide spread into mainstream culture there has been minimal cognitive shift to non-linear thinking. In the current highly complex world, people are struggling to describe, define and discuss phenomenon and process they observe with a traditional language that is insufficient for the task.
That organisations are complex dynamic systems is, today, a much agreed upon perspective. However, non-linear approaches to unravelling the dynamics of organisations and the interplay and relationship with communications have also been hindered by our desire for predictability. Being able to predict the behaviour of a system has been integral to our evolution as a civilisation. Predictability of a system is extremely useful, from predicting weather cycles to be able to maximise crop yields, to predicting economic cycles of prosperity and paucity, we rely heavily on the ability to analyse a system and foresee a range of outcomes dependent on a set of variable criteria. What use then is a model or framework that at its core is built upon non-linearity and non-predictability? The author suggests that a cognitive shift must be made by effective strategic communication leaders to embrace not only traditional causality models but also non-linear emergent frameworks that would facilitate a more in depth understanding of a system. Predictability and an understanding of the parameters of cause and effect are essential in navigating the world, but so too is a deeper understanding of the dynamic and emergent behaviour of a complex system.
To ignore a poignant perspective on reality simply because it does not seem to serve our current cognitive biases is to limit our potential understanding. The unpredictability of systems has often been acknowledged but then largely ignored as something which is not useful to us as we can’t control it or forecast it. This is reminiscent of the old scientific allegory of the drunk and the streetlight: a policeman comes across a drunk looking for his lost $2 bill in a well lit area, when the policeman asks the drunk if he is sure that this is where he lost it the drunk replies “no I lost it over there” indicating a dark alley; when the policeman enquires why he is not looking over where he lost the $2, the drunk emphatically replies “because it’s dark over there I can’t see anything, the light is much better here!”. (Story paraphrased, popularly attributed to a Massachusetts newspaper May 24th, 1924). The point is, if we continue to use out-dated methods of analysis to understand modern complex systems our chances of success are minimal.
Formal systems of codification of reality to develop neat mathematical models capable of high predictability are of course very appealing. However, it is in the social sciences where non-linearity is most obvious and thus a non-linear approach to codification of reality to develop enhanced understanding of a social system is perhaps even more useful. This idea is reflected by Durlauf in his article on economic complexity when he states, “The value of complex system thinking in the social sciences…lies in its potential for enriching our understanding of the relationships between aggregate outcomes and individual decisions” (1997, p.158), specifically Durlauf notes, “Economists using models drawn from complex systems theory have discovered a number of useful ideas and observations that challenge some of the traditional assumptions of the field”. Complexity theory is fundamentally built to encompass and describe the impact that actors, including the messages themselves, have on each other as well as on the structure of the system itself. This last is in direct parallel to CCO theory. Both theories seek to illuminate our understanding of social systems, in CCO theory this is particularly focussed on communication-organisational systems.
The following description of CCO is necessarily brief and macroscopic, this is an extensive field of academic inquiry that is very active with many different scholars continually contributing new ideas and perspectives; this description is to serve as a brief overview of a complex school of thought, with the intent of identifying aspects that are conducive to the application of complexity theory. Further research as proposed by this paper would unquestionably require a far more in-depth description of CCO.
Communication Constitutes Organisation is a field of inquiry that examines how organisations are created by (and create) communication. “Influenced by the work of Karl Weick (1969, 1979)…scholars have focused on how communication is the means by which human beings coordinate actions, create relationships, and maintain organisations” (Putnam et al., 2007). CCO theorist Taylor (1993) outlined what he believed to be of importance in organisational communication theory as, “The goal of organisational communication theory ought to be to bridge the micro/macro gap, by showing how to discover the structure in the process and delineating the processes that realise the structure” (as cited in McPhee & Zaug, 2008).
CCO theory is non-linear, dynamic and attempts to explain emergent behaviour of a system, specifically how communication in a system constitutes the system itself; it can be used as a way of understanding the nuances of an organisation’s becoming and on-going evolution. CCO is contextualist in nature but the author believes that a well-developed framework that encompasses both CAS and CCO theories will provide structuralist components, giving further understanding to the interdependent affect of structure on communication flows and the context that the organisation sits within. Just as CCO theory demonstrates how communication constitutes organisation, an encompassing framework could show how CCO itself lends to constitution of (and is constituted by) a communication’s adapted complexity theory model.
According to Schoeneborn et al., (2014) there are three schools of CCO Thinking: 1) the Montreal School of Organisational Communication; 2) the Four-flows model (based on Giddens’s Structuration Theory); and, 3) Luhmann’s Theory of Social Systems. Luhmann is a prolific social theorist who focuses on systems theory and communication theory; his works have often been compared to, and analysed in light of, complexity theory and there is much scope to explore this paper’s topic in this school of thought as well. In fact, all three schools of thought have strong parallels to complexity theory. Schoenenborn et al. highlight an over-arching requirement for a unified CCO, ”we believe that it is necessary to engage in further theoretical work at the intersections of the three main schools of CCO thinking (Brummans et al., 2014). With the aim of demarcating the common ground on which a unified CCO perspective can be built” (2014, p.287), it is possible that CAS could provide the key to a unifying framework.
However, with the intent of simplicity of approach for this preliminary exploration into the merit of applying CAS to CCO, the author has chosen the second school of thought, the Four-flow model, as the primary CCO subject of this introductory paper.
The four-flow CCO model identifies four dynamic processes that a message can undertake, as well as overlapping pathways. Mann describes this as “Process, equivalence, structure and power underpin[ning] the typology of message flows” (2015). In their highly intricate discussion of the framework structure of CCO theory, McPhee & Zaug (2000) apply a dynamic level to the formerly reductionist and relatively static construct of causal relationships between communications and organisations. This dynamism is evident in their statement, “emphasizing communication means emphasizing circulating systems or fields of messages.” Following Mintzberg (1979) and Lash & Urry (1994), McPhee & Zaug also adopt the terminology “flows” to describe the dynamic processes involved when communication constitutes an organisation. This is taken a step further to propose that the “flows” also involve “crosscurrents”. Such language is highly indicative of an approach that allows for, and is contingent upon, emergent behaviour in a system, an intrinsic element of complexity theory.
A brief overview of the four flows of CCO as described by McPhee and Zaug (2008) in Building Theories of Organisation: The constitutive role of communication, Putnam, Nictoera, Routledge (2009):
- Membership negotiation – relationship of the members to the organisation. It is “not limited to recruitment and assimilation, rather it focuses on the ways that membership becomes a relationship formation” (p.10).
- Self-structuring – a quality that shows an organisation to be more complex than a mere random collection of agents. “Interactions [between members] that steer the organization in a particular direction” (10) This flow is also seen as responsible for creating hubs and nodes in the organisation, as well as boundaries.
- Activity co-ordination – organising team efforts in achieving tasks and solving problems through membership co-operation.
- Institutional positioning – this is a macro level process that looks at how the organisation interacts with external organisations and actors. “Developing and maintaining a place in a larger social system is a type of identity” (p.11) This flow gives an organisation its contextual identity.
It is in the second flow that we see the most obvious parallels to complexity theory. This flow describes organisational self-structuring, an emergent property that is a fundamental marker of a complex adaptive system. The work that has been done in categorising and analysing this second flow can provide valuable groundwork for describing a complex system. Self-structuring can be seen as behaviour in a CAS that seeks to maximise the success of the system; as described by Bertuglia and Vaio, “an organization can be seen as a complex system which, in order to survive and develop…self-organises itself, displaying emergent properties, so as to render its interaction with the environment…as favourable as possible” (2005, p. 280). Kauffman calls such behaviour “Order for Free” and demonstrates how the spontaneity of self-organising “supplies the small ordered attractors we need.” (1995, p.80), in chapter 4 of At Home in the Universe he provides examples of proof of this concept.
The other three flows can also be easily aligned with fundamental concepts of CAS. For instance, the third flow is indicative of emergent behaviour through interconnectivity of a system. The fourth flow reflects the requirement of a CAS to engage with, and interact with, external systems in its environment. All of these flows identify and examine how information would flow throughout the various parts of a CAS. One could imagine CAS as a framework through which McPhee and Zaug’s four flows travel and interact.
The ‘crosscurrents’ described by McPhee and Zaug can also be seen as paths to emergence. This is hinted at by Mann when she states, “The four-flows involve ‘crosscurrents’ that play a role in constitutive communication beyond information transmission” (2015).
The nature of complexity theory is highly suited to extrapolating patterns and structures between different levels of a system and identifying how data is moved between varying aspects of the system; an aim similar to that of CCO theory. In Putnam et al.’s (2007) introduction to the seminal volume on CCO theory, they note that only a few of the current schools of thought “identify the types of dynamic processes that intertwine communication and organisation in a CCO relationship. Thus to expand CCO theory, scholars need to focus on the kinds of processes and interrelationships among them that occur in the ongoing streams of organizing” (p.9). This same aim is echoed in complexity theory as “How do complex interrelationships between many objects produce order in the aggregate and what types of order do they produce?” (Durlauf, 1998). These statements demonstrate a perfect alignment of goals between the two theories. By combining the research from both of them, a more encompassing framework could be developed. CCO theory “embodies the material (composition or elements), the formal (framing or forming), and the efficient causes (principles or rules for governing) that bring organisations into existence” (Putnam et al., 2007, p.4); the author posits that concepts that describe the framework of a complex adaptive system could form the structure for a new framework of thought through which the principles of CCO could flow giving enhanced clarity into how systems self organise, and either adapt, stagnate or dissolve into chaos. Putnam et al., recognise that CCO theory provides discourse on the “dynamic activities” of these systems “without unpacking the nature of these processes and how they are related to the elements that form an organisation” (2007, p.4). CAS theory is focussed on the processes of dynamism in a system and the different elements that form the structure of a system, thus making a perfect complement to CCO theory.
One of the main criticisms that has been levelled at CCO theory is that it is too focussed on the macro level and fails to recognise the importance of individual agents, “they [McPhee & Zaug] reject bottom-up or inductive answers to the constitution question, offered by the likes of Boden (1994) and Taylor and Van Every (2000)” (Cooren & Fairhurst, 2007, p.118) leading four-flow theorists to vacillate between human and organisational agents of constitution. Cooren and Fairhurst invoke early “bottom-up” arguments of organisational constitutive theory of Tarde (1999) and Latour (2002) when they note that:
“Tarde insists that it is only in the details of social life that we can find the source of its order and harmony. The latter should never be considered given, by some a priori and overarching structures, but rather be analysed as the product of infinite interactions in which disorder and chaos also have chances to emerge” (2007, p.125)
In CAS theory it is essential to understand how minor fluctuations into a system may cause greatly amplified changes at a later date, popularly known as “the butterfly effect”; a concept that Tarde is precisely touching upon in his call to not dismiss micro level communications in a system as potential major constituents to organisational structure. In the author’s opinion, neither the “bottom-up” nor the “top-down” approaches tell a complete story, they are merely two sides of the same coin and both must be included in a comprehensive framework of understanding of the communication-organisational relationship. Such a multi-polar approach is an inherent function of CAS theory.
Taylor, whilst applauding the criteria set out by McPhee and Zaug, seeks to take the theory a step further to encompass co-orientation and the phenomenon that shows that “collective identity emerges that is distinct from the communities who make it up” (2007, p.155), an expression of CAS emergent behaviour summarised as ‘the whole is greater than the sum of the parts’.
CAS addresses both of these criticisms of the four-flow model as well as aligning with the four-flow model itself. It strikes the author that from these arguments CAS could provide an excellent framework for CCO of varying schools of thought to hang on and work through. CCO provides valuable insight into the dynamics of communication interaction and how it constitutes organisation, it provides an ideal bridge to apply the more abstract ideas of CAS to real world human applications. Whereas CAS is very good as describing structure and process, CCO fills in specific details regarding communications, messages, human and non-human agents and the activity co-ordination of members of an organisation.
Complexity theory is an exciting and evolving field, and there are many different schools of thought. It has evolved in roughly the same time frame as CCO and as such is still highly flexible in definition and encompasses a wide variety of perspectives. There are many varying definitions of the key concepts of CAS that have developed from different fields, for instance: biology, anthropology, economics and health services. This does lead to potential misuse and misunderstanding of some of the basic concepts. Rickles et al., provide a simple guide to some key terms in their 2007 article “A simple guide to chaos and complexity”, these definitions are in line with those used in this paper. Additionally a brief terminology list has been appended to this article to provide clarity to the author’s intent and message. Of course these definitions can be contested and likely should be in the case of further research, but by stating the author’s understanding of key terms a level conceptual field can by laid down.
In addition, the degree of complexity of a system can often be subject to the biases of the observer, making it even more difficult to pin down a solid definition. The concept of complexity can be seen in the writings of many of the most active minds over the centuries. In his discussion on the complex nature of man, in which he recommends a more holistic approach to epistemology, in 1670 Blaise Pascal noted, “How can a part know the whole?” (p.23). Modern CAS theory has it’s roots in systems theory, chaos theory and autopoiesis theory to name just a few. More recent scholars confirm that we are still without a firm definition; “to date, the work conducted in this field has not been founded on a coherent ‘complexity theory’ even though it is a commonly used expression” (Bertuglia & Vaio, 2005, p.275); “there is some looseness in how they [complexity concepts] have been translated from their origins in mathematics and physics” (Rickles et al, 2007). Indeed, the fact that there is no agreed upon formal definition that crosses disciplines is reflexive of the nature of the theory itself!
Nevertheless, there is great usefulness in applying the concepts of complexity to any number of systems to develop a broader understanding of how a system is structured and how it functions. Bertuglia and Vaio put forth three basic characteristics of complexity, (paraphrased): 1) feedback networks which, when in the right phase, are at the “edge of chaos”; 2) creativity that is destructive of previous states of equilibrium; and, 3) inability to plan or predict creative processes or results of such.
It is generally agreed that complexity is a theory employed to analyse systems that are composed of many interacting parts “whose repeated interactions result in rich, collective behaviour that feeds back into the behaviour of the individual parts” (Rickles et al, 2007). Complex systems are adaptable to change and are by nature dynamic as they react to flows through the system enabling the system to evolve. A fundamental feature is that a reductionist analysis will never be able to describe emergent behaviour of the system. Following this, “inputs are not proportional to outputs” (Rickles et al., 2007), meaning that small perturbations to the system can have large consequences. Behaviours and patterns that arise from these dynamics are considered emergent properties and are non-predictable using linear causality due to the sensitivity of a complex system. Self-organisation and self-structuring is a means by which complex systems achieve emergent, innovative and creative behaviour.
It is important to note here that complexity and chaos, whilst sharing some characteristics, are different. Chaos is the relatively deterministic behaviour of a simple set of initial conditions whereas “complexity is the generation of rich, collective dynamical behaviour from simple interactions between large numbers of subunits” (Rickles et al., 2007). Anderson also provides an excellent introductory scope to complexity theory, notably how it relates to Organisation Science; in his article he summarises one of the key differences of chaos and complexity, “chaos theory demonstrates that simple laws can have complicated, unpredictable consequences; and complexity theory describes how complex causes can produce simple effects.” (1999, p.3). An example of chaos is that it is one of many states; for instance when water is in its frozen state it is highly ordered, in its gas state it is highly chaotic. Complexity applies more to the transitions between states, “the edge of chaos”. In other words, chaos describes a system that has some form of boundaries, whereas complexity is focussed on the boundaries themselves and what occurs in these poised states of phase transitions.
In regards to CCO, complexity can be more closely aligned with “becoming” and chaos with a deterministic structure. Chaotic systems are deterministic if one can know all of the initial state conditions; complex systems work from a state of entropy toward order, often dependent on the relationships between parts of the system as well as with external systems. Complexity rather than Chaos provides the appropriate framework to complement CCO as it more accurately reflects structures of dynamism of an organisation.
Self-organised criticality (SOC) is another sub-set of complexity theory sometimes known as Critical Phenomena, first proposed by Per Bak, Chao Tang and Kurt Wiesenfeld in 1987 in Physical Review Letters. SOC relates to the processes that happen during phase transitions “self-organised criticality provides a general mechanism for the emergence of complex behaviour in nature” (Paczuski & Bak p.4). Frigg (2002) gives a good critical account of SOC, its benefits and its failings. Frigg employs the metaphor of the pile of sand (first proposed by Bak & Paczuski) to exhibit dynamic systems and their stable and critical states, that is, that eventually one grain of sand will be responsible for the avalanching of a large pile of sand causing a major metamorphosis of the systems structure. It is mentioned in this paper as a model that can demonstrate how minor fluctuations into a system can cause greatly magnified effects. In the author’s opinion it is a sub-set of the grander theory. SOC is useful in understanding the poised states of phase transitions of a system, which is what dynamics occur at the edge of chaos. It can be directly related to CCO in a number of ways from the impact of a single individual into a system all the way through to how a critical mass of members can effect large scale change both within the system as well as producing external effects onto interrelated systems.
Complexity theory is a broader aspect of a cognitive paradigm to ontological understanding of systems in which complex adaptive system theory (CAS) is a sub-set relating specifically to dynamic and adapting systems. A healthy CAS can be described as a system that maintains dynamic homeostasis, in that it is balanced between static stagnation and turbulent chaos; it is poised at “the edge of chaos” in a phase state that is conducive to adaptability and innovation. These systems are nonlinear, important to note is that fact that their “nonlinear dynamics can give rise to self-organising and self-reproducing structures” (Bertuglia & Vaio, 2005, p.276).
A CAS application to organisational theory can be seen as a network of actors and flows that interact to produce emergent properties that exhibit innovation and creativity. Using this definition we can see that CAS is appropriate to most (if not all) social systems; “consider that each society is made up of a network of individual actors, which interact both with one another, in accordance with the rules of the internal organisation of the society, and with the actors of other societies that constitute the environment” (Bertuglia & Vaio, 2005, p.280).
There are many persuasive arguments on what are the key indicators of a CAS. Bertuglia and Vaio (2005) have summarised them to be (paraphrased): 1) large number of elements interconnected in a non-linear way; 2) interacts with other CAS; 3) receives and is sensitive to environmental feedback; 4) identifies regularities in the flow of information that it acquires and attempts to model an understanding of; 5) uses environmental feedback to learn and adapt.
Whilst the author does not disagree with this categorisation, for the purposes of bridge building to CCO theory, a simplified set of three key indicators is described below. It must be impressed that all of the above and below characteristics are indicators of a CAS; it is a matter of application as to which of them one might choose to be the highlighted properties.
This is, arguably, the most vital feature of a complex system; emergence is the result of a system in which the whole is greater than the sum of the parts. Much could be devoted to the definition of this aspect alone, Bertuglia and Vaio give an excellent summary of ‘emergent property’ when they say “(it) means that a new property of the system appears that was impossible to predict as the overall result of the individual interactions, considered one by one, between elements” (2005, p.279). The ontological approach of understanding a system by looking at its emergent properties is the opposite of traditional reductionist methods.
When given the space to self-organise, a system can evolve to dynamic stability. “By self-organising, the system passes from one attractor to another, spontaneously crossing the border between one basin of attraction and another” (Bertuglia & Vaio, 2005), it is by abandoning equilibrium that such behaviour can occur. Self-organisation is a hallmark of many social systems, especially global social movements and activist movements.
Self-organisation is a process of adaptability whereby a CAS can evolve to find the most suitable attractor or structure of being. It is a process of “becoming”. It is due to an adaptive response that self-organising behaviour occurs; as such the system becomes more robust over time. When an organisation is adaptable it is more likely to be successful over a longer period of time. Flexible and adaptable organisations can more easily weather unpredictable events, both internally and externally. As well, an adaptable organisation is far more likely to exhibit enhanced innovation.
Traditional linear models of communication approaches in organisations were long ago identified as inadequate in describing dynamic organisations. In 1999 Craig wrote, “The potential of communication theory as a field can best be realized, however, not in a unified theory of communication but in a dialogical-dialectical disciplinary matrix”. In Craig’s writings we find the emergence of the ideas of complexity theory. Even though he never invoked that term per se, he identifies the need for a more complex and reflexive approach to understanding communication theory, “The relationship between theory and culture is thus reflexive, or mutually constitutive.” (1999, p.125). As mentioned earlier, it is our deep-rooted desire for predictability that has encouraged us to remain focussed on causality models. Complexity when seen as a theory does not seek to provide a high level of accurate prediction, rather a deeper epistemological understanding of the dynamics of a system and the poised edges of state transitions where self-organised criticality lies. Should we be able to construct a conceptual framework that intersects CAS and CCO we would find a highly useful analytic tool. Such a framework could be adapted for any organisation wishing to increase innovation and adaptability to ensure prosperous longevity. Should a successful framework be developed it could be taught to strategic communications leaders to use to improve innovation and maintain their system to be robust in the face of change and crisis. Ultimately such a framework could be written into a software as a service platform to assist communication strategists with mapping and maintaining their organisations dynamical health.
The aim of this paper has been to explore the potential for further research in which a framework may be created to unify a social systems theory of how communications and organisations constitutively work in a complex adaptive system context. It is not to create a traditional predictive model that is the more popular style of models of formal systems depicting real systems and providing prediction by implication. Rather, the desired model would be seen more akin to an operational framework which could be adapted and moulded by a strategic communications leader to use in maintaining the health of an organisation by its communication flows.
Such an analytic tool would be used by a strategic communication leader to “massage” a system into dynamic homeostasis whereby robustness, emergent innovation and creativity could thrive. The proposed framework would give the strategic leader enhanced rhetoric, vocabulary, and non-linear cognitive skills when helping shape an organisation into a strong, healthy and creative force in an unpredictable and rapidly changing world.
When complexity theory is employed to understand systems in social sciences it is common to build up from a mathematical representation of the real world to establish a model that can be used to predict future behaviour of the system. This approach has its roots in the ontology of physicalism or materialistic monism. Traditional methods of creating models to understand reality have been reductionist in nature, “When we create models of reality, we identify, or at least attempt to identify, the elements that constitute it” (Bertuglia & Vaio, 2005, p. 4). Social systems such as the communications in organisations are generally far more complex and nuanced than any traditional mathematical system can accommodate; generalisations and averages must be used to construct these models that render the models far removed from the reality of the system. Rather than creating mini representations of reality by providing reductionist models the aim of a conceptual framework of CAS-CCO is not to say A=B but instead, A affects B in such-and-such a manner.
There has been significant exploration of how to apply complexity theory to organisational theory in recent years, but it is very much a developing field. Opinion on the subject can be found throughout a number of scholarly articles as well as popular business and management books available on e-readers. Many organisational theorists have come to recognise the limitations of traditional linear models and are seeking to apply new tools to organisations and their communications constructs to better understand the flows and processes of these systems. A far more extensive literature review on this aspect alone would likely yield interesting results. A common theme among these is “change management” in organisations, a theme perfectly suited to CAS theory. It many business administration courses change management is delivered with a modern flourish encasing what is essentially just a re-hash of traditional thinking. By employing philosophical concepts and language of CAS, change management could be taught in a truly non-linear paradigm.
Rather than identifying specific mathematical correlations to a social system of communications in organisations, it strikes the author that reversing the approach would yield more practical models and tools that could be more easily applied to real world situations. In essence the desired outcome would be an adaptable framework on which to apply real systems; not a formal system designed to predict and imply. Such an adaptable framework would allow a strategic communications leader to understand and manage flows of communication and their effect on organisation structure to achieve dynamic homeostasis. As Ströh noted, “Rather than creating strategies and leading the change, the leader’s role is to create channels and forums for self-organizing behaviour to emerge”, this embodies the essence of what a new conceptual CAS-CCO system would strive to achieve.
This management style has been gaining momentum over recent years and is echoed by Morrison, “Communication is a central pillar in the creation for self-organised emergence in complexity based, non-bureaucratic organisations” (2011, p.146). Modern leading management styles are tending toward the role of caretaker rather than manipulator, as such new models of analysis are required.
This is a paradigm shift in thinking about how we use models. Traditionally models have proven their success by their substantiated ability to predict behaviour. “Conceiving organizations…as adaptive complex systems enables the manager to improve his decision-making and supports the search for new solutions” (Bertuglia & Vaio, 2005, p. 281). A new framework would prove its success by making an organisation healthier, evidenced by successful and productive output, increase creativity and innovation, ethical standards and happiness of members, and the ability to handle change and crisis.
In using a top down approach to understanding what a new model may encompass, a number of key attributes can be identified as critical to creating a successful model.
In his article “Emergent Communication Strategies”, King delivers discourse on this aspect demonstrating that whatever the communication construct is, when it starts to play out, new aspects of a message or of relationships between actors will emerge. King highlights the need to consider the reader/hearer response as well as the situated context within which the communication is taking place when identifying emergent strategies (2010). This is just one example of emergence in a system as it pertains to communication. This is arguably the most essential attribute and must be more deeply explored in subsequent research.
As described by Ströh, relationships should be open, honest and with a developed level of trust. By facilitating positive relationships within a communication construct in an organisation the doors are opened for higher levels of participation and more effective collaborative efforts.
The uni-directional approach of messages moving only from management to employee, or from organization to audience is an expression of a traditional hegemonic paradigm. Since the advent of the Internet and the rise of social media we have become a more vociferous society, where the impact of all voices has become more relevant. Control, as it relates to “coping with complexity”, is explored by Nothhaft and Wehmeir who suggest that context control rather than direct control is the more appropriate definition of communication management (2007). In a new model of communications organisational theory the intent to enable communications leaders to facilitate and guide a system to dynamic homeostasis, replaces the traditional intent of persuasion, regulation and control. Reducing control on a system facilitates self-organisation, growth and adaptability.
Maintaining an organisation at a dynamic edge, poised between stability and chaos, allows for maximum potential of innovation and creativity. Innovation and creativity are themselves very large concepts; in this case potential synonyms could be: ingenuity, change, imagination and inventiveness. In a rapidly changing environment, innovation and creativity are key functions of the ongoing vitality of a system and the dynamic homeostasis of an organisation. When a system is poised “at the edge of chaos”, between static stability and chaotic disorder, it is in this transition state that we see the becoming of a system. When a system is maintained at the dynamic edge it is always in the process of transition and at such point of self criticality true innovation can emerge. When an organisation innovates it develops new ideas and ways of doing things that most appropriately meet the conditions of the moment and the relationships both within and external to the organisation. As markets, governments and societies change so too an organisation must adapt through creative and innovative means.
New technologies emerge and old ones die away often more rapidly than we can plan for, the means through which we can communicate and organise is constantly expanding, and the very physical environment of the planet is in flux. The global economic collapse of 2008 descended on us so rapidly it took even the most astute and seasoned investors by surprise. Natural catastrophes such as the Japanese earthquake and tsunami of 2011 had not only a devastating effect on the Japanese nation, but on the world economy and the global environment. A communications model, which can detect, assess change and perturbations, and adapt rapidly would be an invaluable tool to help an organisation survive and achieve success in an unpredictable environment.
In our highly connected world we are becoming increasingly aware that we are all sharing the global society and the planet together; this connectedness means that the actions of the individual can be more easily amplified into large perturbations of the global system. Ethical responsibility of a professional leader is highlighted in Faber’s statement, “This critical awareness is a key component of the professional’s occupationally derived self-image and directly informs the professional’s work-related practices”. Ethical intent and leadership is vital to the maintenance of flow of positive intent.
We live in a world more highly connected than any time before. Understanding the nature of our connectivity and interconnectivity is essential in grasping the macroscopic consequences of the actions of the individual or sub-unit. Developing a model that accounts for this hyperconnectivity is paramount to the success of any organisation in the modern world.
The interest in the “Knowledge Economy” popularised by Drucker in 1969, has become increasingly mainstream. Leaders of G20 countries are recognizing the mutual benefits of knowledge sharing as is evidenced by many of the articles and initiatives coming from G20 meetings, for example “Emerging Lessons on Institutionalizing Country-led Knowledge Sharing” (Freres & Schulz, 2011). Snowden discusses this in more depth as he posits a primary goal of knowledge management is to create the conditions for innovation (2003). The ability to freely share knowledge within the system rather than segregating knowledge and isolating components is a key indicator of a dynamic and complex adaptive system.
The vision of the author is that a CAS-CCO framework will facilitate strategic communications managers in placing organisations at pre-eminent, evolutionary fronts of potential, innovation and adaptability, building on some of the most up-to-date communications theories and aligning them with complexity theory philosophies and concepts. Fundamental to this new approach is to move away from a dependence on predictive and deterministic models to embrace new ontological techniques that utilise uncertainty as a means to maximise adaptability and emergent behaviour. This diagnostic framework would serve as a ’tool-kit’ to enable communications leaders to ‘massage’ their system to success.
No organisations (or not very many) operate in complete isolation with closed boundaries to the external world. Organisations sit within a contextual framework that includes: local and global economies, local and global laws and cultures, weather and physical climate, and a host of other factors. These external forces are always in flux and thus their influences on the organisation will also vary over time. Any analytic tool that attempts to understand organisational communications dynamics must take this into account. These boundaries are not fixed and the ability of the system to adapt to changing tides of external forces is paramount to success. The fourth flow of CCO theory, Institutional Positioning, addresses this in part by looking at the interaction between the organisation and human actors. CAS theory could provide additional framework to also consider non-human agents such as weather, physical environment, and global economic shifts.
Good interrelationships of actors and sub-units are fundamental to the health and success of any organisation. Being able to interpret and analyse the types of flows between agents as well as how they are contextually situated in relation to one another is key to managing this success. CCO theory strives to understand these interrelationships and CAS theory could be adapted to form a framework of meaning of how these interrelationships are placed.
Self-structured organisations generally come about with the need for mutual success. This is explored in depth by Kauffman (1994) when he redefines Darwinian models of evolution to a broader context of improved survival of systems able to self-organise in a way to adapt to, as well as modify, their environment. Such abilities tend to be the hallmarks of some of the most successful organisations. Homeostasis is a state in which a system makes modifications on its boundary edges to maintain internal stability; the author has extended this to include ’dynamic’ as a more active view of a healthy system or organisation. Dynamic equilibrium is another term that could help describe the desired state of an organisation. This dynamic approach to the health of a system falls in line easily with the four-flow model of CCO.
The development of a framework that would combine both CAS and CCO would best be built from the top down. At a later date a framework acting as an analytic tool could perhaps be built into a Software-As-Service application platform that could be used by strategic communications leaders. Any SAS would need to be accompanied by a training module for the strategist so that they are able to take full advantage of the concepts.
Uncertainty is a part of any organisational system and thus must be accommodated into the framework from the onset. The ability to handle uncertainty and unpredictability is essential for such a model to successfully guide a communications strategist. The way that such a conceptual framework is approached must be fundamentally different to traditional reductionist and deterministic behaviour. Such a framework would be in essence a tool-kit to assist a communications leader interpret the dynamics of a system and provide minor inputs to massage flows into maintaining dynamic homeostasis.
One key area of this analytic paradigm would be investigation into the nature of attractors or basins in which data can flow into and either out of again or remain embedded in a static feedback. Understanding how attractors interact with the four flows would provide greater insight into the contextual structure of the interrelationships of the agents of the system. Rickles et al. describe the process of attraction in a dynamic system as, “The set of points that are ‘’pulled’’ towards a particular attractor are known as the basin of attraction” (2007). An attractor in a social system can be thought of as a pattern of behavior that has a certain tendency; identifying trends of behavior is just one part of identifying movement in a complex system. Defining how attractors can be translated to the four-flows would provide insight into the causes behind flows in a system as well as which types of attractors are healthy and which may lead to stagnation or disruptive chaos.
When the majority of attractors in an organizational system are of the poised nature, existing on the edge between chaos and static stability, a state of dynamic homeostasis is most likely to emerge. When a system is in dynamic homeostasis, the permutations, or “butterflies”, into the system are accepted and modified into the poised attractors. When this occurs the system is adaptable and is not only able to handle change but can also provide a positive emergent “soup” from which creativity and innovation can spring. As Kauffman astutely noted, “What we need are laws describing which kinds of networks are likely to be orderly and which are likely to succumb to chaos” (1995, p.79).
The author believes there are three mechanisms of dynamic homeostasis: fluctuation detectors, mechanisms to effect change, and negative feedback loops. These are the key areas to massage a system into homeostasis; the way these mechanisms flow can be seen as the processes of becoming of an organisation. An analogy would be the dials on an old-fashioned TV set used to adjust the broadcast to a clear picture; they are the primary arteries of dynamism that adjust flow throughout the system and help balance and maintain its health. Understanding the flour flows of CCO theory enables the communications leader to fine-tune these mechanisms to massage the system.
It is important to remember that developing such a tool-kit is not aimed at enabling one to successfully manipulate a system to achieve a specific outcome, rather it is to allow the system to naturally emerge into successful states. A communications leader using this framework must be able to relinquish control on a system and become a caretaker, or facilitator, making small adjustments to maintain homeostasis, making room and opportunity for emergence of creativity and therefore innovation
A potential pitfall of developing a model that is intrinsically dependent on constructivism and the effects of the observer is that it becomes so abstract that it loses its usefulness and real world applicability. Therefore, attempting to apply a CAS-CCO framework to a real system during the development phases will ensure that any developed model remains aligned with authentic and palpable systems. If practical tools could be developed from a new communications model that encompassed CCO and CAS theories and applied to organisations existing in a global context, it is hoped that the health and robustness of that system would rapidly increase and lend long-term strength and stability, even in uncertain times.
In their edited collection Social Dynamics, Durlauf and Young explore in depth how complexity theory can be applied to the social science study of social interactions and neighbourhood effects, notably on the educational choices of disadvantaged families as described in the Gautreaux study. Their approach is more mathematical having its origin in economics but many of the principles are paralleled in this paper. In this volume Durlauf and Young state, “we believe that mathematics of complexity, with its emphasis on phenomena such as self-similarity, and scaling laws, will prove to be of substantial value to social scientists” (2001, p.17). In particular their description of basins of attraction as they relate to the choices and interactions of individuals within a system, is highly applicable to developing an understanding of flow processes in a ‘softer’ communications CAS-CCO framework. Their interactions-based modelling approach is aligned with many of the philosophies of CCO and CAS and the case studies outlined in this volume, such as the Gautreaux study discussed in several chapters, may be good candidates to use as systems on which to test a new communications model of CCO and CAS.
The ideal system to use as a dataset for testing the validity of developing a communications framework, would have the following attributes:
- Many components. Individuals and sub- Additionally, these components must have some form of connectivity and interconnectivity. Large scope. A national or global scope would be ideal considering organisations in the modern world often are affected by, and affect on, a national or global level.
- Interacts with external systems. This could be governments, world markets or physical systems such as weather and climate.
- Allows the amplification of change and perturbation.
- Some degree of freedom in the system. Choosing a rigid and static system will take longer to yield results and will hinder testing of many of the nuances of self-organisation, CAS and CCO. Freedom facilitates self-structuring processes.
- Exhibits properties of emergence. That the system has already shown to have emergent properties will aid in applying the fundamental principles of the model; that is, it has produced effects that cannot be determined by reductionism.
Dr. Mann of the University of Sydney has applied CCO theory to a global social movement, La Via Campesina, a “transnational network of over 160 rural peoples’ organisations in more than 70 countries” (2015); La Via Campesina is a global social movement and organisation focused on food sovereignty of small farming communities. It defines itself as an “international movement, which brings together millions of peasants, small and medium-size farmers, landless people, women farmers, indigenous people, migrants and agricultural workers from around the world.” (retrieved, viacampesina.org 12th July, 2015). Thus, it is a system of many individual components and sub-units that is organized on a global scale, one of the fundamental criteria of a CAS. Mann does point out that connectivity has been a problem for some members of this system and notes that, “strengthening links in the network through enhanced communication and information exchange remains a priority”. This satisfies the first two requirements of an appropriate system that a CAS-CCO framework may be applied to.
That La Via Campesina interacts with external systems on a global scale indicates that it “evolve[s] in reciprocal interaction with the environment, thus contributing to constituting the universe in which the same act” (Bertuglia & Vaio, 2005, p.282). This demonstrates a quality of CAS theory being constructivism of its own context and is reflected in CCO theory as “explicating configurations of power in the constituting process to offer a critical theory of how that power is manifested and shapes organisational members’ reality” (Mann, 2015). This quality is also related to the fourth flow of CCO theory, Institutional Positioning. It is evidenced in La Via Campesina as “The relationships with other civil society organisations” as well as “within national public spheres” and global organisations such as the UN and NGO’s such as FIAN (Mann, 2015, p.15).
Mann describes key characteristics of social movements as “dynamic communication systems” (Fuchs, 2006, p.101) within which individual and collective communication practices produce alternative understandings and oppositional framings that contest and seek to transform “large-scale, collective changes” (Ganesh et al., 2007, p.177). This exhibits key aspects of a complex system in that small perturbations in the global food system are sought in order to achieve amplified changes on a larger scale. This attribute of complex systems is defined by Bertuglia & Vaio as being important in the health of a system, “It is precisely the amplification of the perturbations caused by positive feedback that end up being vital to a system’s evolution” (2005, p.282). This satisfies the fourth criterion.
Such global social movements generally offer a large degree of flexibility, another aspect that is requisite of a system that desires to exhibit emergence; “Within the transnational social movement network – unstable, contingent and responsive, with the ability to combine rule-governed organisations with flexibility, open-endedness, decenteredness and spatial dispersion” (Fraser, 2008, p.128)” (Mann, 2015). Such a system would lie at the edge of chaos, a fundamental criterion of a CAS to develop innovation and creativity. Kauffman says of such a state, “Just between, just near this phase transition, just at the edge of chaos the most complex behaviours occur – orderly enough to ensure stability, yet full of flexibility and surprise” (1994). Mann indicates the self-structuring nature of La Via Campesina in the “Farmer-driven programs generating and sharing technologies and solutions”; this self-structuring appears to be fundamental and intrinsic to this organisation, thus satisfying the fifth criterion.
Further research into the emergent qualities of La Via Campesina needs to be undertaken but this property is indicated by Mann when she notes, “Adjustments and modifications take place as members presume that they are working not just on related tasks but within a common social unit with an existence that goes beyond the work interdependence itself” (2015, p.12). This echoes the CAS adage that the whole is greater than the sum of the parts. Mann concludes “Emerging through local episodes of communication the organisation is constantly ‘(re)produced, (re)incarnated and (re)embodied in local interactions, and thus subject to change and renewal’ (Cooren et al., 2011, p.20).” (2015, P.18).
From this initial look at the validity of attempting to combine CCO with CAS into a conceptual framework that could be used as an analytic tool for strategic communication leaders it would appear that there is merit to further develop this idea. This paper has drawn a number of very complex ideas from a variety of disciplines, each with several schools of thought; definitions have necessarily been very brief and highly macroscopic and require deeper scrutiny. Preliminary research into this would involve the following:
- A more thorough definition of the theories that will be drawn from including identifying which schools of thought would be most applicable.
- Development of a conceptual framework of how CCO would interact with CAS theory will compose a large section of the research. This framework will require a far more extensive analysis of how attractors may be used when describing the processes of social systems. Additionally specificity of how complexity terms would apply to a communications-organisational model needs to be mapped out. Exploration of the interplay of other concepts such as ‘butterflies’ or permutations, the edge of chaos, emergence etc., need to be mapped onto CCO models. Modelling how the four-flows and crosscurrents would move through a complex adaptive system will also be essential to intertwine the dynamics of CAS and CCO.
- Application of a real world case study, for example a social movement or an NGO to the proposed framework needs to be undertaken. Finding specific connection from a real world communication-organisation system will be essential to test the validity of the conceptual framework.
- Defining measures of success as well as usefulness of this approach.
- Analysis of the results and successes and failures to be followed by recommendations for further research if applicable.
What would be the real world benefits to organisations if this research were to be successful? Whilst the benefits and aims will necessarily shift as new findings come to light and real world case studies prove aspects of a CAS-CCO framework to be valid or invalid, the author’s goals for such research when developed and packaged into a useable tool include the following:
- Assistance in making an organisation more robust and adaptable to change and crisis. Whether this be internal or external change.
- Increased innovation and creativity in an organisation.
- Great clarity in the dynamics of an organisation and how these dynamics create the organisation itself.
- Insight into how to massage and maintain an organisation to stay poised in dynamic homeostasis.
- Ability to align an organisation more fluidly with external systems.
- Guidance for the modern strategic communications leader in thinking in a non-linear manner, enabling them to be more aware of nuanced perturbations into their organisation.
- A framework to assist developing organisations to structure themselves in a way most likely to achieve success whilst maintaining ethical responsibility both internally and externally.
Today it has become more usual for organisations to be viewed as complex, dynamic networks that consist of interactions and relationships between both human and non-human agents. Recognising the importance and the role that communication has in developing structure and form of an organisation, as described by CCO theory has been an excellent way to begin to more accurately understand these complex relationships and systems. Such symbiotic co-evolution of communications and organisation, or of agents and system structures, align perfectly with both CAS and CCO theories. There are multiple over-lapping factors including self-structuring, emergent behaviour and complex interrelationships both within and external to the system. Several CCO theorists have identified gaps in this developing field of thought, gaps that the author believes that CAS can help fill. Conversely using CCO as a consociative bridge for complex adaptive systems theory to communication theory and organisational theory, provides a sound anchor in grounded action. Essentially the trifold combination of communications, organisational and complexity theories promises to hold excellent tools for analysis of a system. It is important to note that such a framework will not be based on predictability models but will assist a cognitive shift to understanding the dynamics of a communications-organisation system with the intent that this facilitate the decision processes of strategic communications leaders when managing their system to maintain dynamic homeostasis.
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Below are definitions of some key terms used by the author. Many of these terms have multiple definitions in a variety of different fields and can be ambiguous in different contexts. The following definitions are the meanings that the author is working with. These definitions can, and have been, debated at length; the purpose of placing them here is to give more clarity to the author’s intent in the main paper.
|Attractor||A pattern, loop, state or behavior that a dynamic system evolves toward. There are three main types: static (repetitive loop, stable with no innovation), chaotic (wildly disordered) and elegantly complex (poised on the edge of chaos and static stability, the state most likely to foster creativity and innovation). An attractor in the strategic communications sense can be a pattern of communication, a funnel or basin where communication efforts commonly pass through. Understanding where attractors are in a communications system and of what type they are is fundamental in understanding the dynamics of the system. Attractors can be thought of as basins of data and patterns that a system may drain into.|
|Boundaries||In CCO theory the self-structuring nature of the second flow “includes the forming of boundaries and loci that constitute the organizational identity that agents refer to” (Putnam et al., 2007). How a system sits on its boundaries is essential to enabling success of a system. In complexity theory it is often called “the edge of chaos”.|
|Butterflies, dominos and snowballs
|There have been numerous iterations of where exactly the hypothetical butterfly flapped its wings and subsequently where a tornado occurred; the metaphor is attributed to Edward Lorenz and his studies into sensitive dependencies of dynamical systems, which he presented at the 1972 American Association for the Advancement of Science. Butterflies relate to initial conditions, dominos relate to causal effect chains and snowballs relate to processes and effects that start at an insignificant level and grow to become major percusses in a system. Semantics aside, all of these and more turns of phrase point to a system that is dynamic and in which parts are interdependent on each other as well as sensitive to external influences. Most importantly “butterflies” indicate a system that is sensitive to small changes and perturbations, whereby the small butterflies can have amplified effects in a far removed part of the system or in a future time. Butterflies are neither good nor bad (just as nature is), it is how people react to them that determine overall consequences of a human system This is echoed in CCO theory by McPhee and Zaug, when they discuss the impacts of even members low in power, “communication even by members low in power still does forceful work on the constitutive task”|
|How easily and effectively one part of the system can connect and communicate with another. A high connectivity allows for a higher participatory engagement of more parts of the system. Quantity does not override quality and the form of connectivity is just as important, if not more, than the height if it. CCO theorists such as Mann have cited the level of connectivity in a communications-organisational structure as key underpinnings of the on-going success of the system.|
|“The forming, composing, or making of something in addition to describing the phenomenon that is constituted” (Putnam et al, 2009). It must not be confused with simply identifying the parts that make up the whole as that is reductionist and does not account for emergent properties. There is lengthy discourse in CCO theory as to the definition of ‘constitute’.|
|“A system whose state (and variables) evolve over time, doing so according to some rule. How a system evolves over time depends both on this rule and on its initial conditions—that is, the system’s state at some initial time.” (Rickles et al., 2007).|
|in this sense I am expanding it from more than just a steady and stable state of equilibrium as I wish to differentiate it from static states. In this modern approach homeostasis indicates the health of the system whilst still allowing for dynamic emergence. For instance a healthy body is in a state of homeostasis whereby it dynamically regulates its system to maintain equilibrium and harmony.|
|Edge of Chaos||This is when a system is at a critical or poised phase transition state. This is a state of the system that lies between the static stability of equilibrium and the disorder or chaos. The term was coined by Doyne Farmer and Norman Packard (1988) when it was used to describe phase transitions. The term has been widely used perhaps notably by Stuart Kauffman.|
|This is what arises by means of the relationships between nodes of a system rather than what is produced by an individual. It is the patterns that emerge from dynamic and harmonious relationships facilitated by high connectivity. In its most ideal form it can be seen as a collaborative consciousness emerging from separate parts when they are brought together in a healthy system.|
|Feedback||Feedback loops can be positive or negative. It occurs when the output of a system is fed back into the system. Negative feedback is dissipative and positive feedback “increases the rate of change of some variable” (Rickles et al., 2007).|
|Entity or system, static object or dynamic construct. “For Weick (1979), organisation was the process of organising, of interpreting an enacted environment in a way that led to orderly action. His theoretical move from organisation being a static entity to a dynamic process was a dramatic turn in how organisational communication could be studied and explained” (McPhee et al.). “Organisations are ‘complex resource[s] with implications for individual agency’ (McPhee & Iverson, 2009, p.74)” (cited in Mann, 2015).|
|Poised||See “Edge of Chaos”|
|This is a multi-stage act that includes: talking, listening, understanding, and storing for future use. “Powerful statements and symbolically coded representations of jointly experienced circumstances are examples of collective sense-making whereby a “situation” is comprehended and articulated specifically in words that serve as a “springboard for action” (McPhee & Zaug, 2000, para 20).” (Mann, 2015)|
|Self Organising||This happens when “systems spontaneously order themselves (gen- erally in an optimal or more stable way) without ‘external’ tuning of a control parameter. This feature is not found in chaotic systems” (Rickles et al. 2007).|