Commenting on the Overview of Systems Science (draft version 0.5) for the Guide to the Systems Engineering Book of Knowledge is problematic. Applying systems thinking on systems thinking constitutes a mess of ideas that is difficult to tease apart. Breaking the idea of “systems science” in its parts of (i) “systems” and (ii) “science” is reductive. The more compatible approach is to view “science” with a larger context of “systems thinking”.

I’ll attempt to shed some more light on concerns and perspectives in the following sections:

• 1. The definition of science often tends towards disciplinarity; systems thinking aims for transdisciplinarity
• 2. Science is part of thinking, which can be philosophically framed as episteme (know why), techne (know how) and phronesis (know when, know when, know whom)
• 3. Domains of systems thinking can be categorized into systems theory, systems methods, and systems practice
• 4. Incomplete systems thinking may suggest paths through which gaps may be filled
• 5. Systems thinking has evolved with roots of linear causality, circular causality, complexity theory and reflexivity theory
• 6. Opportunities to refresh ties between systems thinking and action science, theory of practice and social learning could be pursued

The discussion of science and systems thinking leads to perspectives at another level. There’s an additional appendix on applied philosophy that illustrates that such inquiries are not without history.

1. The definition of science often tends towards disciplinarity; systems thinking aims for transdisciplinarity

In a previous post on systems thinking and (the) systems science(s) in a system of ideas, the correlation between the term “systems science” and “social systems science” at the University of Pennsylvania was reviewed. While “social systems science” was chosen as a term to be purposively clumsy, Russell Ackoff preferred more generally to use the label of “systems thinking”, obviating some criticisms on definitions of science. Science tends to be organized as disciplines. In the Oxford English Dictionary, one definition of discipline is “a branch of instruction or education; a department of learning or knowledge; a science or art in its educational aspect”. Another is “a particular course of instruction to disciples”, which implies a master. Ackoff criticized disciples as anti-systemic, challenging his students and followers to transcend his body of work.

Effective research is not disciplinary, interdisciplinary, or multidisciplinary; it is transdisciplinary.

Systems thinking is holistic; it attempts to derive understanding of parts from the behavior and properties of wholes rather than derive the behavior and properties of wholes from those of their parts.

Disciplines are taken by science to represent different parts of the reality we experience. In effect, science assumes reality is structured and organized the way universities are. This is a double error.

First, disciplines do not constitute different parts of reality; they are different aspects of reality, different points of view. Any part of reality can be viewed from any of these aspects. The whole can be understood only by viewing it from all the perspectives simultaneously. Second, the separation of our different points of view encourages looking for solutions to problems with the same point of view from which the problem was recognized. Paraphrasing Einstein, we cannot deal with problems as effectively as possible by employing the same point of view as was used in recognizing them.

When we know how a system works, how its parts are connected and interact to produce the behavior and properties of the whole, we can almost always find one or more points of view from which better solutions to the problem can be found than can be found from the point of view from which the problem was recognized. For example, we do not try to cure a headache by brain surgery, but by putting a pill in the stomach. We do this because we understand how the body, a biological system, works. When science divides reality up into disciplinary parts and deals with them separately, it reveals a lack of understanding of reality as a whole, as a system.

Systems thinking not only erases the boundaries between the points of view that define the sciences and professions, but also erases the boundary between science and the humanities. Science, I believe, consists of the search for similarities among things that are apparently different; the humanities consist of the search for differences among things that are apparently similar. Science and the humanities are the head and tail of reality, viewable separately, but not separable. It is for this reason that I have come to refer to the study of systems as part of the scianities. [Ackoff 1999, pp. 426-427, editorial paragraphing added]

In his books, Ackoff wrote that “the pursuit of truth is the function of science“.  Truth is one of the four ideals from ancient Greek philosophy (including the good, beauty, and plenty). More practically, coming at problematique — a system of problems — with a disciplinary lens can lead — as Ian Mitroff says — to a Type III error, as “the error of solving the ‘wrong’ problem precisely” or “the probability of solving the ‘wrong’ problem when one should have solved the ‘right’ problem”. Ackoff and Mitroff were both students of C. West Churchman, who developed the Design of Inquiring Systems. Inquiry is “an activity which produces knowledge” [Churchman 1971, p. 8]. Transdisciplinary would be one of the features of the “fifth way of knowing“, as unbounded systems thinking.

2. Science is part of thinking, which can be philosophically framed as episteme (know why), techne (know how) and phronesis (know when, know when, know whom)

For a deeper appreciation of the meaning of science, let’s go back to ancient Greek philosophy, and then work our way towards the present. The intellectual virtues of episteme, techne and phronesis are articulated in ancient times, although phronesis has been slower to develop in modern philosophy. Here’s a table summarizing some of the language used in philosophy. While episteme is often described as “know why” and techne as “know how”, it’s my personal intellectual contribution to describe phronesis as “know when, know where, know whom”. This is related to themes coming from phenomenology and social theory.

As a way of illustrating some distinctions between the approaches, let me describe an experience that I’ve had with practitioners of Traditional Chinese Medicine (TCM). For some time, I’ve been seeing Dr. David Lam, who is trained in both western and Chinese techniques. He thus has been able to give me explanations in multiple ways (e.g. the west sees cortisone produced in the adrenal gland, TCM sees cortisone as produced by kidney system). He applies techniques of pulse diagnosis, and prescribed herbs — now standardized into pill form, manufactured in China. Dr. Lam exhibits understanding and experience all three virtues of episteme, techne, and phronesis. More recently, I’ve also tried an apothecary in Chinatown, who similarly uses pulse diagnosis. He prescribes decoctions of raw herbs to be cooked at home. This apothecary demonstrates techne and phronesis, as knowledge passed down through multiple generations in his family, in the practice of “tasting a thousand herbs“. As effective as the remedies have been, the apothecary has not demonstrated the skill of episteme. He does not have the university diplomas on the wall, as does Dr. Lam. My ailment may have been cured, but the theoretical explanation is incomplete.

A more detailed description of episteme, techne and phronesis as interpreted from Aristotle by Bent Flyvbjerg writes:

Episteme concerns universals and the production of knowledge that is invariable in time and space and achieved with the aid of analytical rationality. Episteme corresponds to the modern scientific ideal as expressed in natural science. In Socrates and Plato, and subsequently in the Enlightenment tradition, this scientific ideal became dominant. [....]

Whereas episteme resembles our ideal modern scientific project, techne and phronesis denote two contrasting roles of intellectual work.Techne can be translated into English as ‘art’ in the sense of ‘craft’; a craftsperson is also an artisan. For Aristotle, both techne and phronesis are connected with the concept of truth, as is episteme. [....]

Techne is … craft and art, and as an activity it is concrete, variable, and context-dependent. The objective of techne is application of technical knowledge and skills according to a pragmatic instrumental rationality, what Foucault calls ‘a practical rationality governed by a conscious goal’ (Foucault 1984b: 255). [...]

Whereas episteme concerns theoretical know why and techne denotes technical know how, phronesis emphasizes practical knowledge and practical ethics. Phronesis is often translated as ‘prudence’ or ‘practical common sense’. [....] Phronesis is a sense or a tacit skill for doing the ethically practical rather than a kind of science. [Flyvbjerg 2006, pp. 371-371]

Science in the age of the Enlightenment – which is at the foundation of science in the west today — emphasized episteme and techne. However, the primacy of phronesis in Aristotle’s philosophy has required reiteration.

In Aristotle’s words phronesis is an intellectual virtue that is ‘reasoned, and capable of action with regard to things that are good or bad for man’ (Aristotle, The Nicomachean Ethics …). Phronesis concerns values and goes beyond analytical, scientific knowledge (episteme) and technical knowledge or know how (techne) and it involves judgements and decisions made in the manner of a virtuoso social actor. [....]

Aristotle was explicit in his regard of phronesis as the most important of the three intellectual virtues: episteme, techne, and phronesis. Phronesis is most important because it is that activity by which instrumental rationality is balanced by value-rationality, to use the terms of German sociologist Max Weber; and because, according to Aristotle and Weber, such balancing is crucial to the viability of any organization, from the family to the state. [Flyvbjerg 2006, p. 370]

In a common sense view of the world, applying “know why” (episteme) and/or “know how” (techne) in the wrong place, wrong time and/or with the wrong people signals immaturity in practice. Applying “know when, know where, know whom” appropriately demonstrates an appreciation of the situation at hand, a possible implicit weighing of values, and the setting for an appreciative system.

3. Domains of systems thinking can be categorized into systems theory, systems methods, and systems practice

One breakdown of systems thinking is a three way categorization into systems theory, systems method and systems practice. This is not the only way to analyze systems thinking, yet it may be useful in an alignment with episteme, techne and phronesis. Here’s a list of some top-of-mind systems thinking domains as a sample of the breadth of knowledge, inquiries and approaches. This list is intended as indicative, rather than exhaustive, so other system thinkers may have different views. In addition, since theory and methods and practice can all influence each other, there are some ties between the domains that may not be readily apparent.

Even the most well-read systemicists may have only a passing recognition across the multitude of theories, methods and practices labelled as systems thinking or systems science. One authentic path through the body of knowledge is historical, as key figures in the systems movement have each had a system of ideas that has influenced his or her work. Surfacing some of the relationships and social ties between proponents of the systems movement was an objective of systems sciences connections conversations.

4. Incomplete systems thinking may suggest paths through which gaps may be filled

Presuming an interest in rounding out a knowledge of systems thinking, each individual comes from a different background of experiences. We each take different courses in secondary and post-secondary education, and then avocations and passions bring us along different paths. As an exercise, let’s think through three cases in which systems thinking might be developed from different staring points. These are summarized in the following table.

Summarizing approaches to logic described by Peirce:

• Deduction starts from a rule (major premise), applies a case (minor premise) and concludes with a result.
• Induction starts from a result (major premise), applies a case (minor premise) and concludes with a rule.
• Abduction starts from a rule (major premise), applies a result (minor premise) and concludes with a case.

Let’s flesh out some potential descriptions where systems thinking needs development.

Path (a): Strong on episteme and techne, weak on phronesis:

A person could be strong in episteme (e.g. classroom or book learning) and techne (e.g. methods and techniques), but weak in phronesis (e.g. practical experience). A deductive path of learning could include conscious placements into those situations (i.e. appropriate when, where and whom) on which the phronesis could be developed. This is the spirit behind job rotation, in the development of well-rounded employees.

Path (b): Strong on techne and phronesis, weak on episteme:

A person could be strong in techne (e.g. project management) and phronesis (e.g. hand-on experience), but weak in episteme (e.g. theoretical science). An inductive path of learning could include mentoring by a master who can develop insight into how prior experiences are (or are not) similar. Such regimens of abstraction can deepen expertise, separating the novice who still needs the textbook from the guru who writes them.

Path (c) Strong on episteme and phronesis, weak on techne:

A person could be strong on episteme (e.g. theory) and phronesis (e.g. learning by doing), but weak on techne (e.g. standardized processes). An abductive path of learning could propose repeatable methods that might cover the most common situations, and gradually expand to include greater variability. Technique can be improved both at individual and collective levels.  

Getting some parties to admit to gaps in knowledge may require working on their humility. Identifying the gaps to be filled is a first step in learning.

5. Systems thinking has evolved with roots in linear causality, circular causality, complexity theory and reflexivity theory

The domains of knowledge in systems thinking (and the systems sciences) have not been standing still. Critics of mainstream science often center on a philosophy of logical positivism. In a broader view, Stuart Umbleby describes four models used in the systems sciences: (i) linear causality; (ii) circular causality; (iii) complexity theory, and (iv) reflexivity theory:

One way to understand how the system sciences are developing is to look at the creation of new methods for conducting inquiry. Presently four models are being used in science.

1.1 Linear Causality

Linear causality is the way most science has been done and is still being done. It is the way most dissertations are written. It is supported by many statistical techniques, including multiple regression. It has numerous advantages. Hypotheses can be falsified. Propositions can be assigned a level of statistical significance. The objective is to create descriptions which correspond to observations.

1.2 Circular Causality

Circular causality is essential to any regulatory process – a thermostat, an automated assembly line, driving a car, or managing an organization. Circular causal processes can be modeled with causal influence diagrams and system dynamics models. Often a psychological variable is involved, e.g., perception of…, or desire for…

1.3 Complexity Theory

Complexity theory is primarily a method of computer simulation. It is based on cellular automata and genetic algorithms. The “game of life” is a simple example. The basic idea is very general and encompasses competition among species or corporations, also conjectures and refutations in philosophy. There are two processes involved — the creation of new variety and selection of appropriate variety. The combination of these processes explains emergence of new order.

1.4 Reflexivity Theory

Reflexivity theory requires operations on two levels – observing and participating. Reflexivity involves self-reference, hence paradox, hence inconsistency. Reflexivity violates three informal fallacies – circular arguments, the ad hominem fallacy, and the fallacy of accent (referring to two levels of analysis at one time). [Umpleby 2010, p. 1]

Reflexivity theory has only begun to rise over the past few decades. Since systems thinking centers on appreciating with multiple levels and time scales in relations between parts and wholes, reflexivity is not necessarily such a big stretch for the immersed. The conceptual challenge is likely greater for those more comfortable within the boundaries of disciplinary-focused perspectives. Scientists successful in the current scientific mainstream may not be so motivated to go through a paradigm shift.

… we can now ask which models are considered acceptable by the contemporary academic community. Linear causality, the first model, is the dominant conception of science. It is what doctoral students are taught to use when writing dissertations. Circular causality, the second model, was used in first order cybernetics, but it involves circularity, which some people interpret as fallacious reasoning. Complexity, the third model, includes Stephen Wolfram’s [2002] “new kind of science” and the idea of self-organizing systems. Complexity theory uses a new kind of mathematics, but does not violate any informal fallacies. It is easily recognized as “science” by people trained in the physical sciences. Reflexivity, the fourth model, is very close to second order cybernetics.

Models 1 and 3 – linear causality and complexity theory — are acceptable. No informal fallacies are violated. Model 2 — circular causality — is suspect. It involves circular reasoning. But it has proven to be useful. Model 4 — reflexivity — violates 3 informal fallacies, so is highly suspect. Scientists shun it. They do not take it seriously. Indeed physical scientists seem to have a visceral reaction against it. But the informal fallacies are just “rules of thumb.” [....]

Practicing managers and social scientists will readily agree that human beings are both observers and participants in social systems. Indeed, they say this idea is “not new.” But this perspective is not permitted by the classical conception of science. The conception of science needs to be expanded in order fully to encompass social systems. [Umpleby 2010, pp. 4-5]

Second order cybernetics dates back into the 1970s.  Reflexivity has made significant inroads into social theories in cultural anthropology (e.g. Pierre Bourdieu, with An Invitation to Reflexive Sociology and in understanding the workings of financial markets (e.g. George Soros, with a General Theory of Reflexivity).

6. Opportunities to refresh ties between systems thinking and action science, theory of practice and social learning could be pursued

Some ways of thinking in domains regarded as outside the systems movement may not have been recognized as part of systems thinking, yet could be highly compatible. With some effort from both sides, bridges could be built for mutual benefit. Many of these advances has been associated with interests in (human) action, practice and (social) learning.

Action science, as originally developed by Chris Argyris, was the foundation for the more familiar concepts of organizational learning and double-loop learning. Systemicists have often closely related this work to learning as described in Steps to an Ecology of Mind, by Gregory Bateson.

(Action science) is an inquiry into social practice, broadly defined, and is interested in producing knowledge in the service of such practice. Thus, what counts as a solution for action science both overlaps with and diverges from prevailing scientific criteria. Like the empirical-analytic tradition, action science requires that knowledge include empirically disconfirmable propositions that can be organized into generalizable theory. But at the same time, it also requires that these propositions be falsifiable in real-life contexts by the practitioners whom they are addressed. Like applied research, action science requires knowledge to be useful. Yet in so doing it emphasizes the designing and implementation of social action, and it rejects the current dichotomy between basic research and applied research. It instead asks that its knowledge illuminate basic issues in ways that are at once generalizable and applicable in particular cases. (Argyris et al. 1985, p. 232)

Theory of practice was revolutionized by Pierre Bourdieu. His system of ideas has influenced a generation of sociologists and organization scientists. Bourdieu didn’t believe in defining terms as independent and objective entities. A concise description appears in a chapter by Moishe Postone, outlining the key ideas of habitus, capital and field, in a reflexive perspective:

[In] attempting to transcend the opposition between science and its object, Bourdieu treats science and scientists as part and product of their social universe. The scientific field can lay claim to no special privilege as against other fields; it too is structured by forces in terms of which agents struggle to improve their positions. Science seeks to analyze the contribution of agents’ conceptions to the construction of social reality, while recognizing that those conceptions frequently misrecognize that social reality. By the same token, scientists’ constructions of their own reality — the scientific field and the motivations for scientific behavior — often misrecognize that reality. Consequently, it is essential to advance and endorse a reflexive science of society.

Bourdieu’s project, then, can be described generally as an ongoing attempt to overcome theoretically the oppositions that have characterized social theory and to formulate a reflexive approach to social life. Three fundamental concepts lie at the heart of this project: “habitus,” “capital,” and “field.”

The notion of habitus is central to Bourdieu’s theory of practice …. To this end, Bourdieu treats social life as a mutually constituting interaction of structures, dispositions, and actions whereby social structures and embodied (therefore situated) knowledge of those structures produce enduring orientations to action which, in turn, are constitutive of social structures. Hence, these orientations are at once “structuring structures” and “structured structures”; they shape and are shaped by social practice. Practice, however, does not follow directly from orientations, in the manner of attitude studies, but rather results from a process of improvisation that, in turn, is structured by cultural orientations, personal trajectories, and the ability to play the game of social interaction.

[....] The habitus is at once intersubjective and the site of the constitution of the person-in-action; it is a system of dispositions that is both objective and subjective. So conceived, the habitus is the dynamic intersection of structure and action, society and the individual. [....]

Bourdieu’s notion of capital, which is neither Marxian nor formal economic, entails the capacity to exercise control over one’s own future and that of others. As such, it is a form of power. This notion of capital also serves to theoretically mediate individual and society. On one level, society is structured by the differential distribution of capital, according so Bourdieu. On another level, individuals strive to maximize their capital.[....] The capital they are able to accumulate defines their social trajectory (that is, their life chances); moreover, it also serves to reproduce class distinctions.

Much of Bourdieu’s work focuses on the interplay among what he distinguishes as social, cultural, and economic capital. [....] Although the economic is crucially determining, it must be symbolically mediated. [....] Symbolic capital functions to mask the economic domination of the dominant class and socially legitimate hierarchy by essentializing and naturalizing social position. [....]

The purpose of Bourdieu’s concept of field is to provide the frame for a “relational analysis,” by which he means an account of the multi-dimensional space of positions and the position taking of agents. The position of a particular agent is the result of an interplay between that person’s habitus and his or her place in a field of positions as defined by the distribution of the appropriate form of capital. The nature and range of possible positions varies socially and historically.

Each field is semi-autonomous, characterized by its own determinate agents (for example, students, novelists, scientists), its own accumulation of history, its own logic of action, and its own forms of capital. The fields are not fully autonomous, however. Capital rewards gained in one field may be transferred to another. Moreover, each field is immersed in an institutional field of power and, even more broadly, in the field of class relations. Each field is the site of struggles. [....]

Bourdieu interrelates the three central concepts we have outlined. He conceives of social practice in terms of the relationship between class habitus and current capital as realized within the specific logic of a given field. An agent’s capital is itself the product of the habitus, just as the specificity of a field is an objectified history that embodies the habitus of agents who have operated in that field. The habitus is self-reflexive in that, each time it is animated in practice, it encounters itself both as embodied and as objectified history.

On the basis of these three concepts, Bourdieu has attempted to formulate a reflexive approach to social life that uncovers the arbitrary conditions of the production of the social structure and of those dispositions and attitudes that are related to it. [....] [Postone et al. 1993, pp. 3-6]

Social learning is generally known as the domain of “communities of practice”, originated by Etienne Wenger. With Bourdieu as one of his foundations, learning is expressed in both the contexts of individuals and collectives in a framework that includes (i) meaning, (ii) practice, (iii) community, and (iv) identity.

A social theory of learning must … integrate the components necessary to characterize social participation as a process of learning and of knowing. These components … include the following.

1) Meaning: a way of talking about our (changing) ability — individually and collectively — to experience our life and the world as meaningful.

2) Practice: a way of talking about the shared historical and social resources, frameworks, and perspectives that can sustain mutual engagement in action.

3) Community: a way of talking about the social configurations in which our enterprises are defined as worth pursuing and our participation is recognizable as competence.

4) ldentity: a way of talking about how learning changes who we are and creates personal histories of becoming in the context of our communities.

Clearly, these elements are deeply interconnected and mutually defining. [Wenger 1999, pp. 4-5]

The domains of systems thinking and systems engineering certainly have perspectives on action, practice, and learning. As we seek to deepen our appreciation of the meaning of (the) systems science(s), we should be aware of advances in other fields that could help to inform our understanding of the world.

Appendix: On applied philosophy

The above essay has jumped from science to broader definitions of thinking, and philosophy. In the same way that engineering is applied science, we shouldn’t hesitate to expand a view of science as applied philosophy. There’s a history of applied philosophy with the history of the systems movement, as described in the memoirs of Russell Ackoff.

Churchman and I designed an Institute of Experimental Method that was intended to conduct interdisciplinary research and problem solving where societies were involved. We took our proposal to the President of University [of Pennysylvania] who showed interest in it. He said he would create such an Institute if we could get the support in writing of three different departrnents. lt took almost a year to get the approvals required. In the meantime the President had retired due to illness and had been replaced by a lower level officer of the University. When we showed him the proposal and conditions for approval that his predecessor had established, he told us he was not bound by agreements made by his predecessor. He showed no interest in our proposal. I took that as a rejection of our idea and saw no reason to remain at Penn even if I could have.

I graduated with a PhD in the spring of 1947. During the summer that followed I accepted an appointment in the Philosophy Department of Wayne University in Detroit. (lt was not then a state supported institution. That came later, after I had left the University.) The Dean of the College had assured me that he would support the creation of an Institute much like the one Penn had rejected. lt was to be called the Institute of Applied Philosophy. [Ackoff 2010, pp. 98-99]

Criticism of “high science” are not new. The disconnects from Plato through Descartes have been described by Stephen Toulmin, in support of broader views of science (e.g. participatory action research).

The High Science model, then, rests on two chief assumptions. The older of these — the assumption that the only authentic knowledge is universal, general and timeless — can already be found in the Greek philosophers of Antiquity. This belief is what gave the theorems of abstract geometry their particular charm for Plato and his successors; within an axiomatic system, our understanding of spatial relations and other properties of Nature achieves — so they dreamed — a general, eternal, immutable order unavailable to the pedestrian, disorderly facts of everyday experience.

This superior kind of knowledge came to be called episteme (theoretical grasp): the Platonist dream was that the knowledge we generate in dealings with the world can be organized into systems of theorems, from whose axioms all humbler, more detailed kinds of knowledge can be formally deduced. As the inscription over the entry to the Academy declared, no one could hope to grasp the principles of public affairs who had not already mastered the model High Science — i.e. geometry.

The other assumption of thc High Science model is more recent and more elaborate. In all his own writings, from 1629 on, René Descartes combined a scientific admiration for Galileo’s telescopic discoveries with philosophical commitment to this kind of Platonism. After 1640 the use of axiom systems to organize knowledge and experience of other kinds soon became common form: Isaac Newton’s Mathematical Principles of Natural Philosophy was just one very successful example out of many. In this respect theoretical physicists, up to James Clerk Maxwell and beyond, have shared Descartes and Newton’s Platonic vision, of episteme as the exemplar of high, pure science.

Before long, the geometrical model of a scientific theory was linked to half a dozen other maxims of method. These concerned

• the kinds of experiments and observations that. are acceptable in a Science;
• the objective. detached posture of the scientist toward his objects of study;
• the inferior status of ‘practical’ knowledge, as a secondary (applied) mode of understanding.

As a youth, Descartes found Poetry and History entrancing; but, when introduced to Philosophy, he decided that those fields — though pleasing — lacked intellectual depth. History, in particular. was like Foreign Travel: it broadened the Mind. but it did not deepen it. Only mathematical knowledge (he concluded) could do that!

If, in methodological terms. the only legitimate approach to Science is to accept the Platonist vision of episteme — with or without its Cartesian additions -— the methods of inquiry of participatory action research are philosophically indefensible. Confronting these methodological hurdles, it falls at the first fence. It has practical not theoretical aims, it fails to separate the observer and observed, and its empirical results cannot be generalized or abstracted from their original loci; the list of defects goes on and on. lf we are to find a way ahead from this point, we shall need another line of approach, powerful and reputable enough to stand comparison with the familiar model of High Science. [Toulmin 1996, pp. 206-207]

Aristotle’s criticism of the Platonic model are further fleshed out by Toulmin.

Later in the Ethics, Aristotle goes on to classify the different species of knowledge: these included techne (know how) and phronesis (the ability to spot the action called for in any situation) as well as Plato’s favored episteme (theoretical grasp}. In this way, he raises the possibility that different inquiries can be pursued and judged ‘rational,’ in their own different, yet appropriate ways. He elaborates on this view in later works, starting with the Art of Rhetoric. Geometry may be admirable in its way; but practical inquiries like clinical medicine and helmsmanship do not demand (say) the formal skills possessed by mathematical whizzkids. Practical competence in such arts is acquired, rather, over the course of long experience.

Aristotle treats the multiplicity of intellectual disciplines in a democratic, not in an elitist way. We need not enthrone any single discipline as the Master Science, whether geometry for Plato or theoretical physics for 20th century readers. Nor need we rule out, as unsound, inquiries that do not follow the methods or conform to the standards of the Platonist ideal. Each discipline can match its methods and standards to its special subject matter and problems. Fields like clinical medicine, horticulture and ornithology are, thus, no more bound than political science to produce axiomatic theories, Indeed, from this alternative point of view, the High Science model is not so much convincing as pretentious. [Toulmin 1996, pp. 207-208]

To bring us up to date from the ancient Greeks to the 20th century, Rojcewicz provides an interpretation of Heidegger’s interpretation of Aristotle (interpreting Plato). We add technology into the mix.

For Heidegger … technology is a theoretical — not a practical — affair. Technology is not directed toward making things, doing things, finding means to ends, instrumentality. More precisely, technology is primarily a theoretical affair. There is a practical side to technology, but that is secondary; it follows upon the theoretical understanding. Technology is, of, course, related to making things and doing things, but it is so related only because technology first of all is an understanding of what things are in general. Technology does determine our doing and making, but only because it determines what we take to be a thing in general in the first place. Technology is not practical directly, but only indirectly: by disclosing to us what constitutes beings, it provides us with a guideline that governs all our relations to beings, including our practical relations. lt is in virtue of the truth disclosed in technology, i.e., in virtue of its theoretical significance, that technology is practical. Technology can do things only on account of what it sees, and what it sees is that which makes a being be a being at all. [Rojcewicz 2006, pp. 56-57]

Techne can then be framed with the changeable, and episteme with the unchangeable.

What then, for Aristotle, is the difference between techne and episteme, between techne and knowledge pure and simple? As Heidegger says, they differ with respect to what they disclose and how they disclose. Episteme discloses what is unchangeable, techne what is changeable. And episteme is disclosure for its own sake, while techne has an ulterior motive beyond mere disclosure. Thus episteme is literally knowledge pure and simple: it is knowledge of what is simple (the eternal and unchangeable), and it is pure knowledge (for its own sake). Let us delve a little more deeply into this basic characterization of episteme in order to understand how techne differs from it.

For Aristotle, knowledge does not change. What most properly deserves the name knowledge is constant and permanent. But such a knowledge is possible only of unchanging objects. For Aristotle it is primarily the object that determines the character of the knowledge, not vice versa. There can be genuine knowledge, then, only of what is changeless, and what is changeless is eternal, never having come into being and never going out of being. Hence, there is no genuine knowledge of individual things; knowledge is possible only of the principles of things, the essences of beings (in Plato’s terms, the Ideas), and the ultimate principle of beings is Being. The most genuine knowledge is then ontological knowledge, and this more than anything else deserves to he called knowledge, episteme. Accordingly, there is only one genuine episteme, and that is philosophy or the understanding of Being as such. This knowledge has no ulterior motive, since the object of the knowledge, Being, cannot be influenced or manipulated or changed in any way. This knowledge is disclosive looking for the mere sake of disclosure; it is purely theoretical.

Techne, in contrast to episteme, is knowledge of changeable things; its objects come and go and change in various ways, and so techne cannot be considered knowledge in the most proper sense. In particular, its objects are not the changeable things of nature, which come and go of themselves, but the things that come and go due to a role played by the one who possesses the techne. This person discloses what does not yet exist concretely; and that disclosure is subject to change, since the thing may turn out differently than it was envisioned. [Rojcewicz 2006, p. 59-60]

With a shared understanding of the foundational philosophies, the thinking originating in the times of the ancient Greeks may be advanced with our contemporary pursuits.

References

Ackoff, Russell L. 1999. On Passing Through 80. Systemic Practice and Action Research 12 (4): 425-430. doi:10.1023/A:1022404515140.http://dx.doi.org/10.1023/A:1022404515140.

Ackoff, Russell L. 2010. Memories. Triarchy Press. Preview at http://books.google.ca/books?id=63e3LQfZFYQC.

Argyris, Chris, Robert Putnam, and Diana McLain Smith. 1985. Action science. San Francisco: Jossey-Bass. Preview at http://books.google.ca/books?id=0lfRjwEACAAJ.

Churchman, C. West. 1971. The Design of Inquiring Systems: Basic concepts of Systems and Organization. Basic Books. Preview athttp://books.google.ca/books?id=gRBgAAAAMAAJ.

Flyvbjerg, Bent. 2006. Making Organization Research Matter: Power, Values, and Phronesis. In The Sage Handbook of Organization Studies, ed. Stewart R. Clegg, Cynthia Hardy, Thomas B. Lawrence, and Walter R. Nord, 370-387. Second. Thousand Oaks, CA: Sage.http://flyvbjerg.plan.aau.dk/Publications2006/PhronOrgClegg0603Handbook.pdf

Mitroff, Ian I., and Harold A. Linstone. 1993. The unbounded mind: Breaking the chains of traditional business thinking. New York: Oxford University Press, Preview at http://books.google.ca/books?id=AYX5ixVQpGcC&q.

Postone, Moishe, Edward LiPima, and Craig Calhoun. 1993. Introduction: Bourdieu and Social Theory. In Bourdieu: Critical Perspectives, ed. Craig J. Calhoun, Edward LiPuma, and Moishe Postone, 1-13. University of Chicago Press. Preview at http://books.google.ca/books?id=13fqL4FBGr8C.

Rojcewicz, Richard. 2006. The Gods and Technology: A Reading of Heidegger. SUNY Press. Preview at http://books.google.ca/books?id=BmV6_EFKUOMC.

Toulmin, Stephen. 1996. Concluding Methodological Reflections: Elitism and Democracy Amongst the Sciences. In Beyond Theory: Changing Organizations through Participation, ed. Stephen Toulmin and Björn Gustavsen, 203-225. John Benjamins Publishing. Preview athttp://books.google.ca/books?id=hMi4h6L7gWsC.

Umpleby, Stuart. 2010. From Complexity to Reflexivity: The Next Step in the Systems Sciences. In European Meeting on Cybernetics and Systems Research. Vienna, Austria. http://www.gwu.edu/~umpleby/recent_papers/2010 EMCSR Complexity an Reflexivity final.doc.

Wenger, Etienne. 1999. Communities of practice: learning, meaning and identity. Cambridge, UK: Cambridge University Press. Preview athttp://books.google.ca/books?id=heBZpgYUKdAC.

[jump to top]

Dialogic design and systems thinking can be closely related, although not everyone appreciates the ties.  For the Design with Dialogue community, at the invitation of Peter Jones, we jointly organized a workshop based on some ideas that I had previously brought together in teaching in Finland.  I’ve posted the slides — both with builds and as printable — over on the Coevolving Commons.  For people who weren’t there, I can provide an outline of the activities of the three hours.

After introducing ourselves in the circle, and speaking about dialogues that each of us might be interested in pursuing, I provided an explanation of the Map of Ignorance, as described in the Curriculum on Medical Ignorance by Witte, Kerwin and Witte in the University of Arizona College of Medicine.  We walked through the interpretation of Unknown Knowns, Known Unknowns, and Errors.

Unknown Knowns, Known Unknowns, Errors

Unknown unknowns raise questions about what might or might not be knowable.

Unknown Unknowns

Taboos and denials typically don’t enter a dialogue unless the facilitator ensures that they do.

Taboos, Denials

Questions of knowledge bring us to conceptions of science, related to scientific revolutions, whereby a quick outline of Thomas Kuhn and paradigm shifts was described.  This led to a discussion of mainstream science and post-normal science, following the work of Jerome Ravetz.  The combination of systems uncertainty and decision stakes might lead us to approaches based on applied science (e.g. engineering), professional consultancy (e.g. scientists) or post-normal science (e.g. dialogic design)

Attendees broke out into six groups.  From the predispositions individuals had outlined in the circle introductions, each group quickly chose a dialogue of focus for design.  They were asked to (i) create a quick map of ignorance for the topic, and (ii) discuss how the dialogue might be approached in the frame of mainstream science or post-normal science.

Returning to the circle, the second set of explanations was around the design of inquiring systems, as originally developed by C. West Churchman, with more concrete descriptions by Mitroff and Linstone.  Stories helped to differentiate four ways of knowing, as (i) inductive-consensual, (ii) analytic deductive, (iii) multiple realities, and (iv) dialectic.

A fifth way of knowing, a multiple perspectives systems approach, was presented as a challenge, sweeping in the four other inquiring systems.  For some attendees who were interested in business applications, I mentioned that Vince Barabba had described a multiple perspectives systems approach in Meeting of the Minds, and has recently published a new book The Decision Loom.

Participants returned to their groups to discuss what types of inquiring system(s) might be appropriate for the dialogues they were designing.

We closed down the Design with Dialogue session a little bit later than usual, as all groups seemed to want to continue working.  There was a question as whether we had covered all of systems thinking or part of it.  Inquiring systems are only one part of the larger body of knowledge in systems thinking.  Perhaps we’ll look to schedule some more systems thinking sessions relevant to dialogue designers in the future.

References

Barabba, Vincent P. 1995. Meeting of the minds: creating the market-based enterprise. Harvard Business Press, preview at Google Books.

Barabba, Vincent P. 2011. The Decision Loom: A Design for Interactive Decision-Making in Organizations. Triarchy Press. http://www.triarchypress.com/pages/The-Decision-Loom.htm.

Churchman, C. West. 1971. The design of inquiring systems: basic concepts of systems and organization. Basic Books, preview at Google Books.

Mitroff, Ian I., and Harold A. Linstone. 1993. The unbounded mind: Breaking the chains of traditional business thinking. New York: Oxford University Press, preview at Google Books.

Ravetz, Jerome R. 2004. “The post-normal science of precaution.” Futures 36 (3): 347–357. doi:10.1016/S0016-3287(03)00160-5. http://dx.doi.org/10.1016/S0016-3287(03)00160-5.

Witte, M. H, A. Kerwin, and C. L Witte. 1998. Curriculum on medical and other ignorance: shifting paradigms on learning and discovery. In Memory distortions and their prevention, ed. Deborah L Best and Margaret J. Intons-Peterson, 125–156. Psychology Press, preview at Google Books.

Earlier this year, in April, the International Federation for Systems Research hosted its biannual research conversation, this time in Pernegg, Austria.  This meeting was a four-day opportunity to continue developing ideas on the emerging science of service systems begun in July 2009.

The proceedings from the meeting have now been published.  I’ve extracted the chapter for our team as a separate downloadable document.  The report starts with a description of our activities, and an outline of our progress.

The conversation began with self-reflections on personal experiences leading each of the individuals to the systems sciences, acknowledging the influence of those trajectories on their perspectives on service systems.  In recognition of this science of service systems as a potentially a new paradigm, much of the time together was spent in sensemaking about the intersection between ongoing services research and systems sciences perspectives.  This sensemaking led the team to focus the dialogue more on posing the right questions to clarify thinking broadly, as opposed to diving deeply towards solutions that would be tied up as issues within a problematique.

During the conversation, the progress on ideas was recorded on flipcharts.  Nearing the end of our time together, the team cut up the flipcharts with scissors, and collated the discussion threads into five clusters:  (i) philosophy; (ii) science; (iii) models; (iv) education; (v) development.  With service systems as a new domain, the team found all five clusters underdeveloped.  Recognizing that all five clusters are coevolving, the phenomenon of service systems was listed in order from the most concrete (i.e. development) through the most abstract (i.e. philosophy).  Each of the five clusters was then summarized by a meta-question.

• 1. Development: How do we transition from the current paradigm?
• 2. Education: How do we help others learn about service systems?
• 3. Models: How do we understand and decribe service systems?
• 4. Science: What do we know about service systems?
• 5. Philosophy: Why do (or should) we care about services systems?

Each of the meta-questions is described below, with some of the dialogue content associated with the question clusters.

IFSR conversations follow the methods of Béla H. Bánáthy, which means that each participant starting from triggering questions individually develops partial answers and (possibly even more) partial questions.  At Pernegg, we had researchers from four countries (which is even more complicated when we list current places of residency in addition to nationality):

• Gary Metcalf (U.S.)
• Jennifer Wilby (U.K.)
• Allenna Leonard (Canada / U.S.)
• Norimasa Kobayashi (Japan)
• Todd D. Bowers (U.K. / U.S.)
• Janet M. Singer (U.S.)
• David Ing (Canada)

As researchers, we puzzled our way through developing an appreciation for service systems at a foundational level.  To give a deeper sense of the territory that we covered during the conversation, here’s an outline of the final report.

• 1. Development of service systems:  How do we transition from the current paradigm?
  • 1.1 What are the entry points to service systems from where they are?
  • 1.2 Which systems are better suited for “designing with” rather than “designing for”?
  • 1.3 What motivations or incentives encourage the shift to service systems from the legacy state?
  • 1.4 Do we know of concrete examples of the new service systems?
• 2. Education on service systems: How do we help others learn about service systems?
  • 2.1 Through which processes will novices / beginners best learn about service systems?
  • 2.2 How do the systems sciences help in learning about service systems?
  • 2.3 How is the approach to service systems different from prior approaches to education?
• 3. Models of service systems: How do we understand and describe service systems?
  • 3.1 What should the model deal with?  For what purposes to we model service systems?
  • 3.2 How do we reconcile service systems across scientists, engineers and managers?
  • 3.3 In which ways are service system models different from other models of the world we’ve already created?
• 4. Science of service systems: What do we know about service systems?
  • 4.1 What is the scope of a science of service systems?
  • 4.2 Are service systems really new?
  • 4.3 How far are we on advancing a science of service systems?
• 5. Philosophy of service systems: Why do (or should) we care service systems?
  • 5.1 Why would we need a philosophy of service systems?
  • 5.2 What shifts in philosophy might be associated with a service systems approach?
  • 5.3 What is the scope of a philosophy of service systems?
• 6. Continuing inquiry

People looking for simple answers may be disabused of that idea, as this group of researchers didn’t have that end as a goal.  People who are interested in foundational questions may find the downloadable chapter of interest.

As Service Science, Management and Engineering (SSME) has been developing, I’ve noticed a refinement of language. Rather than just abbreviating the long clause to service science, I’m now careful to use the phrase of a science of service systems, following Spohrer, Maglio et. al (2007). There’s a clear definition of service system in the final April 2008 revision of the report by the University of Cambridge Institute for Manufacturing.

What is a service system?
A service system can be defined as a dynamic configuration of resources (people, technology, organisations and shared information) that creates and delivers value between the provider and the customer through service. In many cases, a service system is a complex system in that configurations of resources interact in a non-linear way. Primary interactions take place at the interface between the provider and the customer. However, with the advent of ICT, customer-to-customer and supplier-to-supplier interactions have also become prevalent. These complex interactions create a system whose behaviour is difficult to explain and predict. [p. 6]

I’ve been sorting through the significance of this service system orientation, and have reached the following personal points-of-view.

• 1. The definition of a service system as a system is earnest
• 2. A service system creating and delivering value emphasizes a value constellation perspective over a value chain perspective
• 3. Research into service systems is muddled in the ideas of coproduction and (value) cocreation
• 4. A service system creates value with an offering as a platform for co-production
• 5. The constraints on service systems are changed with advances in technology
• 6. The (new) service economy is not the same as the service sector

Each of these points-of-view require some elaboration. (If the content that follow isn’t detailed enough, there are footnotes, too!)

1. The definition of a service system as a system is earnest

Most people use the word “system” without thinking about what it. Since I’ve had a long involvement with the systems sciences. I need to be sure that the choice of word isn’t arbitrary. The background on SSME draws on systems engineering as a source, with Tien and Berg (2003).

[A] system [can be defined as] an assemblage of objects united by some form of regular interaction or interdependence … A system can be natural (e.g., lake) or built (e.g., government), physical (e.g., space shuttle) or conceptual (e.g., plan), closed (e.g., chemicals in a stationary, closed bottle) or open (e.g., tree), static (e.g., bridge) or dynamic (e.g., human). In regard to its elements, a system can be detailed in terms of its components, composed of people, processes and products; its attributes, composed of the input, process and output characteristics of each component; and its relationships, composed of interactions between components and characteristics. [pp. 23-24]

… thus, service systems engineering is “A multidiscipline that addresses a service system from a life-cycle, cybernetic and customer perspective”. In this regard, the underlying concepts of service systems engineering are the same as those identified in Table 8, with the added concept of services as defined and discussed in Section 2 (Services).¹ [p. 26]

Since the article cites Ludwig von Bertalanffy and Norbert Wiener, it’s in the right ballpark for system scientists.

2. A service system creating and delivering value emphasizes a value constellation perspective over a value chain perspective

The definition of a service system as a “complex system” is a deep statement. The value chain perspective sees a series of handoffs from provider(s) to customer(s). Including customer-to-customer interactions and supplier-to-supplier interactions directly relates to the idea of value constellations, as described by Normann and Ramirez (1994).

From [the] value constellation perspective, value is co-produced by actors who interface with each other. They allocate the tasks involved in value creation among themselves and to others, in time and space, explicity or implicitly. This opens up many opportunities for defining relationships between actors and reassigning activities. If we look at a single relationship in a co-productive system (for example, that between customer and supplier) this view implies that the customer is not only a passive orderer / buyer / user of the offering, but also participates in many other ways of consuming it, for instance in its delivery. Etymologically, consumption means value creation, not value destruction; this sense of consumption is inherent in the “value constellation” point of view. Furthermore, as actors participate in ways that vary from one offering to the next, and from one customer / supplier relationship to the next, it is not possible to take given characteristics for granted: co-producers constantly reassess each other, and reallocate tasks according to their new values of the comparative advantage each other to have. [p. 54]

Co-production is further contrasted to value chain in Normann (2001).

What is new is not co-production, but the way it now expresses itself in terms of role patterns and modes of interactivity. The characteristics of today’s economy naturally reshape co-productive roles and patterms. The distinction between”producer” and “consumer”, or “provider” and “customer” is ever less clear as the business landscape takes more of a “service” mode. [p. 96]

In systems theory, coproduction (as in a value constellation) is contrasted to producer-product (as in a value chain). Coproduction is expressed as “the most critical concept” in Ackoff and Emery (1972, p. 23). It’s not sufficient for a business to just produce a product. A customer has to participate in the process, at least by receiving it. Metaphorically, a bus system can operate its routes without picking up any passengers, failing to serve its essential function. A taxi system can’t operate unless the passenger is a coproducer, giving the driver a destination. The make-and-sell model is contrasted with the sense-and-respond model by Haeckel (1999).

3. Research into service systems is muddled in the ideas of coproduction and (value) cocreation

There’s some confusion in language and definitions around coproduction and cocreation. Coproduction was introduced into the Service-Dominant Logic discussion as foundational premise 6 by Vargo & Lusch (1994).

FP6: The Customer Is Always a Coproducer
From the traditional, goods-based, manufacturing perspective, the producer and consumer are usually viewed as ideally separated in order to enable maximum manufacturing efficiency. However, if the normative goal of marketing is customer responsiveness, this manufacturing efficiency comes at the expense of marketing efficiency and effectiveness. From a service-centered view of marketing with a heavy focus on continuous processes, the consumer is always involved in the production of value. Even with tangible goods, production does not end with the manufacturing process; production is an intermediary process. As we have noted, goods are appliances that provide services for and in conjunction with the consumer. However, for these services to be delivered, the customer still must learn to use, maintain, repair, and adapt the appliance to his or her unique needs, usage situation, and behaviors. In summary, in using a product, the customer is continuing the marketing, consumption, and value-creation and delivery processes. [pp. 10-11]

At the same time, the phrase “cocreation of value” was coming into use. This sparked a request for response in Prahalad (1994).

The Cocreation of Value
[....] I want to congratulate the authors on challenging the dominant logic for marketing by suggesting that services ought to be at the core, and therefore consumers become coproducers. My concern is that V&L do not go far enough. [....]

What is meant by customers as coproducers? [...] Although work and risks increasingly are shared, the firm decides how it will engage the customer. It is this premise, a firm-centered perspective on how to engage the customer, that needs to be debated. [....]

The central ideas revolve around the individual consumer, the experience, the cocreation of value, the criticality of consumer communities, and the need for a network of firms. [....] We find that when we escape the firm and product-/service-centric view of value creation, which is the dominant logic for marketing and strategy (see Kotler 2002; Porter 1980), and move on to an experience-centric cocreation view, new and exciting opportunities unfold. [p. 23]

Unfortunately, the language on Service-Dominant Logic has shifted from coproduction to cocreation in Vargo & Lusch (2008).

Table 1. Service-dominant logic foundational premise modifications and additions (excerpt)

FPs	Original foundational premise	Modified/new foundational premise	Comment/explanation
FP6	The customer is always a co-producer	The customer is always a co-creator of value	Implies value creation is interactional
FP10		Value is always uniquely and phenomenologically determined by the beneficiary	Value is idiosyncratic, experiential, contextual, and meaning laden

[p. 7]

FP6: The customer is always a co-producer
[...] Clearly, S-D logic is primarily about value creation, rather than “production,” making units of output. The emphasis was intended to be on the collaborative nature of value creation, but that emphases could easily become lost in the connotations of “production.”[pp 7-8]

However, we believe that co-production, though distinct from (but nested within) co-creation of value, has a place in S-D logic. [...] In short, we argue that co-production is a component of co-creation of value and captures “participation in the development of the core offering itself” (p. 284), especially when goods are used in the value-creation process.

[...] Our argument is that value obtained in conjunction with market exchanges can not be created unilaterally but always involves a unique combination of resources and an idiosyncratic determination of value (also see FP10) and thus the customer is always a co-creator of value. On the other hand, the involvement in “co-production” is optional and can vary from none at all to extensive co-production activities by the customer or user. [p. 8]

From a systems perspective, “production” doesn’t necessarily mean participation in the manufacturing of a good. The passenger in a taxi service system is a coproducer when he or she gives the destination to the driver. While reifying the premises towards co-creation of value moves the idea of a service system closer to marketing, it moves it farther away from systems science. Digging into value more deeply could lead systems reader into a discussion of appreciative systems by Sir Geoffrey Vickers.

4. A service system creates value with an offering as a platform for co-production

One way of thinking of systems is inputs, operators and outputs. (Adding a guarantor as a fourth part, the model becomes an inquiring system as described by C. West Churchman). With this in mind, while goods are thought of as outputs from a manufacturing system, an offering in a service system is seen as an input — rather than as an output — by Normann & Ramirez (1994).

[... the] production, or rather co-production, of value in the emerging service economy is manifested in offerings, to which several actors contribute by performing specific activities. The offering is the physical and “in-person(s)” embodiment of assets made up of knowledge and experience, in themselves the result of myriad activities performed by many people dispersed in time and space. Assets and resources imply the storage of activities which have been configured for a particular purpose, for a particular actor in a given location at a given time. Some of these activities have secured access to natural resources in increasingly refined forms; others have created complex transformations of such resources, making products and subsystems possible; yet others have developed knowledge of basic technologies and sciences; all these having been combined in a systematic way, in the end ensuring access to them for users. Thus, in the final analysis, whether customers buy a “product” or a “service”, they really buy access to resources. [pp. 49-50]

The access to resources — as an output from a service system — is easily confused with an offering as an input, or a platform. This is true whether the output is tangible or non-tangible, in the example of telephone services by Normann & Ramirez (1994).

While the ownership of physical manifestations of past activity is still significant in the coproductive economy, ganing access to use of offerings (as in the case of car hire) is becoming increasingly important. Thus there are service activities in which most of the knowledge transferred to the customer is embodied in a good, but only access to the good is transferred, not its ownership. Take certain public telephone services: when making a phone call, we do not buy the whole telephone network but simply the right to access it, and we pay for the particular use we make of it. Ownership of the physical products comprising the telephone system remains with the provider. [pp. 51-52]

Although it’s possible to build a service system from the ground, up, there’s advantages to not reinventing the wheel every time, and having a base upon which to build. It’s a platform for learning, in Normann (2001).

The offering thus elevates the user in two ways. First, it gives the user a platform for providing access to an inventory of past activities in frozen form. Second, it liberates the user from this platform of past, accumulated knowledge, stimulating the user by giving him a “code” for value-creating activities and stimulating co-production and relationships. The effectiveness of an offering depends both on to what extent is is a good inventory of past knowledge and on to what extent it contains a good genetic code. [p. 119]

An offering should therefore be seen as a beginning point, not an end point. A provider can create an offering as a foundation for coproduction, but it will take a customer — and possibility also alliance partners — to create an output that has value.

5. The constraints on service systems are changed with advances in technology

A driver for a new science of service systems is advances in technology. Economic progress is related to technological progress, in Normann (2001).

The effect of technology is — and always has been — to loosen constraints. As a result of technological development, what was not possible becomes possible. Or what was not economically feasible becomes so. [p. 27]

Technology has had different impacts in different eras. Technological development broadly mean mechanical tools in the late 1700s, electromechanical machines in the late 1800s, and information and communications technologies in the late 1900s, in Tien and Berg (2003).

Table 1 A Nation’s Economic Evolution (excerpted)

Characteristics	Stages in an Nation’s Economic Evolution
	Mechanical	Electrical	Information
Economic Focus	Agriculture; Mining	Manufacturing; on-Construction	Services
Productivity Focus	Farming	Factory	Information
Underlying Technologies	Mechanical Tools	Electromechanical Machines	Information / Communication
Impact Scope	Family/Locale	Regional/National	Global
Onset in U.S.	Late 1700s	Late 1800s	Late 1900s

As information and communications technologies have gone digital, service systems can play in new dimensions, as in Normann (2001).

[....] Today’s new technology — and here I stick conservatively to information technology without speculating about what possible new dimensions genetic technology and other round-the-corner breakthroughs might bring — liberates us from constraints particularly in terms of:

• Time: When things can be done
• Place: Where things can be done
• Actor: Who can do what
• Constellation: With whom it can be done. [p. 28]

All of this adds up, cumulatively, to the issue of what can be done. [p. 29]

In economic language, changes in technology move the production possibility frontier. In systems language, changes in technology enable the customer to obtain the same or better function with an alternative structure of action. Clearly, information and computer technologies enable new strategies in Normann (2001)

The density opportunity is driven primarily by new technology, but also to a great extent by our imagination and our mind-sets. The major thrust of today’s new technological break-throughs is in the opportunities to restructure activity sets — or “reconfigure” them — in ways that were hitherto impossible. Such restructuring implies two basic proceseses. The first is achieved by shattering activity sets and assets which used to be closely linked to each other, and the second comes from being able to re-link activities and assets that used to be impossible or difficult or very time consuming or too expensive to put together. The first of this set of driving forces, thus, is related to the ability to “break up”, or to unbundle; the second to the ability to “link” and to “put together” or to rebundle. [p. 27]

Reconfiguration in an information/communication dimension is different from that possible in a physical dimension. This is played out in reconfigurable patterns of coproduction involving the provider, customer and/or alliance partners.

6. The (new) service economy is not the same as the service sector

Today’s network-form businesses and outsourcing complicates internal with external, goods with services. The counting of outputs in agricultural, manufacturing and services sectors isn’t as helpful as looking at activities and processes, in Normann and Ramirez (1994).

In the early 1930s the world of business was neatly divided by researchers trying to make sense of industrialization into three types of activities, which came to be known as “sectors”….²

This “sector” notion has survived until today, and is widely understood to encompass economic activities characterized according to their output (Norman, 1984, 1991). The weakness of this categorization is that it has become increasingly evident that the outputs of the secondary and tertiary sectors, goods and services, respectively, can no longer be neatly separated. The original differentiation between goods and services was simply that the former was a “tangible” output (like a car), while the later was an “intangible” output (e.g. health). [p 9]

[...] in terms of employment, and as we propose here in terms of value creation, with the economy that is now emerging, this goods/services distinction no longer holds, causing the “sectorial” model on which it is based to be inaccurate, unhelpful and misleading.³ [p. 10]

In the model as drawn in Figure 3.1, activities in the service “economy” take place as much within the “primary” agriculture and extraction, and in the “secondary” industrial manufacturing sectors as within the “tertiary” service sector itself — an observation consistent with the research cited above.

	Agricultural sector	Manufacturing sector	Service sector
Agricultural economy
Manufacturing economy
Service economy

Figure 3.1 The three-sector model

If “sectors” refers to fields of activity defined by its output, “economies”, on the other hand, are based on type of activity or process — specifically, the mode of operating and the way of organizing and structuring value-creation activity. [....] [p. 11]

Seen in this way, services do not comprise a set of value-creation activities different from manufacturing. Services will never replace goods, hence our opposition to labelling the current economic age “the service economy” in a “post-industrial” sense, which would imply that all activity is going to be service-centred. However, as the manufacture of goods becomes more service-intensive, the concept of sectors becomes outdated, and thus irrelevant and misguiding. This is certainly the case in business, and may quickly also be the case for statisticians cataloguing national economies. [p. 12]

If we’re going to talk about economics, let’s consider the species of capital underlying the agricultural, manufacturing and service “economies”.

With the “economies” view of value-creation activity, the agricultural economy is seen to depend on rent economics. The industrial manufacturing economy is based on scale economics, characterized by mass production and markets, standardiziation and specialization. It is captured conceptually in the “value chain” concept, which depicts the assembly line, this economy’s most typical form. Here value-creation activity is sequential and linear, with actors “adding” value to what they receive “upstream” and passing it “downstream” to the next actor.

In this book, we describe the emerging service economy: here the provider helps the customer to create value, and does not simply sell them products or services made previously. [p. 12]

The title of “The Service Economy in OECD Countries” 2005 report doesn’t help clarify the above. Certainly, the shifts in the service sector are significant.⁴ Looking at the OECD database, though, the STAN industry list follows the international standard industry classification (ISIC) as defined by the United Nations. If we following the ISIC, the impact of information and computer technologies (ICT) — e.g. the Internet, mobile phones — would be limited to the “business sector services” (ISIC 50-74), and not agricultural/extractive (ISIC 01-14), nor manufacturing (ISIC 15-37), nor community, social and personal services (ISIC 75-99). This doesn’t follow the spirit described above. Farmers certainly use mobile phones and the Internet, as do manufacturers, and government services.

Epilogue

As much as the above writing may feel like a research paper, it’s really only the foundation for a research paper. I needed to get some ideas straight in my own mind, before I could move forward. The above content may (or may not) be helpful to others. It’s a personal view that may (or may not) be shared by others, and could serve as an entry point for discussion. To repeat, the six things that I think I’ve learned are:

• 1. The definition of a service system as a system is earnest
• 2. A service system creating and delivering value emphasizes a value constellation perspective over a value chain perspective
• 3. Research into service systems is muddled in the ideas of coproduction and (value) cocreation
• 4. A service system creates value with an offering as a platform for co-production
• 5. The constraints on service systems are changed with advances in technology
• 6. The (new) service economy is not the same as the service sector

Comments are welcomed.

Footnotes

¹ Table 8 illustrates that systems engineering is a general case of service systems engineering, in Tien and Berg (2003).

Table 8 Systems Engineering: Underlying Concepts

Concepts	Definition	Attributes
System	An assemblage of objects united bysome form of regular interaction or interdependence.	Types (natural or built, physical or conceptual, closed or open, static or dynamic) Elements (components, attributes, relationships)
Engineering	Applied science	Definition Synthesis Analysis Design Test Evaluation
Life-Cycle	Series of stages of a system between successive recurrences of the initial stage.	Needs Assessment Design/Development Production/Construction Utilization/Support Phaseout/Disposal
Cybernetics	Kybernetics is the Greek word for steersman or governor.	Feedback (through evaluation of performance relative to stated objectives) Control (through communication, self-regulation, adaptation, optimization, and/or management)
Customer	A consumer (i.e., individual or entity) of goods and/or services.	Needs/Requirements Expectations Satisfaction

[p. 23]

² A description of the three sectors is provided by Normann & Ramirez (1994).

…the primary sectors was defined as agriculture and mining, the original raw material extraction and access-based type of industries that have existed since the beginnings of economic activity. The secondary sector was defined as industrial manufacturing, which covered the transformation-based production industries with specialization, standardization and mass production / mass markets described above. A diverse group of activities not fitting the characteristics of these first two sections, including activities such as transportation, distribution, restoration and healing, were “lumped” into a third category or “sector”, which was called “services”, and which in effect had no cohesive logic except that its activities did not fall into the other two sectors. [p. 9]

³ The service activities inside and outside a company’s legal boundaries shouldn’t be considered differently, in the view of Normann & Ramirez (1994).

While industrialization was epitomized in the assembly-line manufacturing of tangible goods such as Henry Ford’s Model T, it has gradually been recognized that industrial production necessarily included services, such as accounting, purchasing, insurance for workers, materials and equipment, and delivery of finished products. All of these “production costs” are “service activities”; as emerging economic patterns make their “outsourcing” common, the “teritiary” nature of these “secondary” production costs is rendered more visible. The core “secondary” sector thus becomes tied to the “tertiary” one. Thus, instead of thinking that goods-based wealth from the secondary manufacturing sector allows society to enjoy tertiary “services”, it is now becoming evident that efficient “tertiary” activities make or break the “secondary” sector. Researchers on the other side of the Atlantic have also shown that the greatest growth in teritiary activites, services, takes place in the secondary economic sector, manufacturing. [p. 10]

⁴ The OECD report should have been called “Service Sectors in OECD Countries”.

The service sector has become the quantitatively most important sector in all OECD economies…. By 2002, the share of the service sector amounted to about 70% of total value added in most OECD economies, and this has increased considerably since the 1970s. [....]

The services sector is, however, composed of a wide variety of different activities ranging from fast food to brain surgery. [....] The increase in the share of the service sector in total value added can mainly be attributed to the growth of business related services…. In particular, finance, insurance and business services have experienced a strong increase in value added shares. These industries now account for about 20%-30% of value added in the total economy, while their respective shares were between 10% and 20% in 1980. These service industries are primarily driven by market forces, which typically imply greater pressure to improve productivity.

There has been very little change in the value added shares of trade, restaurants and hotels as well as transport and communications services over the past decade. In the case of transport and communications services, trends in prices and quantities have moved in opposite directions. The demand for these services increased in the 1990s, notably in the case of telecommunication services. [p. 7]

References

Russell L. Ackoff and Fred E. Emery, On Purposeful Systems, Aldine-Atherton, 1972.

Stephan H. Haeckel, Adaptive Enterprise: Creating and Leading Sense-and-Respond Organizations, Harvard Business School Press, 1999.

Ifm and IBM, Succeeding through Service Innovation: A Service Perspective for Education, Research, Business and Government, University of Cambridge Institute for Manufacturing, Cambridge, UK, 2008.

Richard Normann and Rafael Ramirez, Designing Interactive Strategy: From Value Chain to Value Constellation, Wiley, 1994.

Richard Normann, Reframing Business : When the Map Changes the Landscape, Wiley 2001.

C.K. Prahalad, “Invited Commentaries on ‘Evolving to a New Dominant Logic for Marketing’”, Journal of Marketing, volume 68, number 1 (2004), pp. 18-27.

Jim Spohrer, Paul P. Maglio, John Bailey, and Daniel Gruhl, Steps Towards a Science of Service Systems, Computer, volume 40, number 1, pp. 71-77.

James M. Tien and Daniel Berg, “A Case for Service Systems Engineering”, Journal of Systems Science and Systems Engineering, volume 12, number 1, pp. 13-38.

Stephen L.Vargo and Robert F. Lusch, “Evolving to a New Dominant Logic for Marketing”, Journal of Marketing, volume 68, number 1 (2004), pp. 1-17.

Stephen L.Vargo and Robert F. Lusch, , “Service-Dominant Logic: Continuing the Evolution”, Journal of the Academy of Marketing Science, volume 36, number 1 (2008), pp. 1-10.

Anita Wölfl, The Service Economy in OECD Countries, Directorate for Science Technology and Innovation, Working Paper 2005/3, Organization for Economic Co-operation and Development.