Hull University Business School | University of Hull

Research Memorandum 46 • April 2004

‘Learning’ with Complexity : Metaphors from the New Sciences

PETER MURRAY The University of Hull, Business School Hull, HU6 7RX, United Kingdom Email : [email protected]

ISBN 1 902034 422

2

ABSTRACT The paper explores three of the rich group of metaphors drawn from complexity available to those reflecting on the practice of management education. The metaphors used are the concepts of the strange attractor, fitness landscapes and networks, and self-organisation by a group. There are many examples of the use of complexity as a source of metaphor in the management area, but this paper is the first to use the metaphors in management education. The paper describes a typical management classroom activity (a case study), and discusses in detail the insights which the complexity concepts provide to the process. These metaphors provide new and stimulating approaches to the development of the process in the classroom, the attitude of the teacher and his or her ability to direct the case study, and the issue of what constitutes a successful outcome. The discussion highlights the role of the process itself in management education, and reflects on the extent to which the teacher manipulates the outcome. The conclusions are relevant to management educators in the light of the growth in interest in complexity, and the questions as to the relevance of management complexity in education.

Introduction The author of this paper has taught on undergraduate and masters programmes for eight years at the University of Hull and elsewhere. During that time, I have become very excited by the ‘new sciences’ of catastrophe, chaos and complexity, and have contributed several papers in this area (Murray 1998, Murray 2002). I have found that my teaching experience, which I would dare to grace with the name of empirical observations, has led me to develop a view that the new sciences provide valuable insights into the process of management education. I do not see these insights as being unique, but I do think that they have considerable relevance to others engaged in the process. The insights of the new sciences are often presented as providing answers to management problems such as the difficulty of long term planning, or how to encourage teams of staff to be more creative and self organising. I am not (yet) convinced that the theory can be used in this way, but I do believe that if the insights of complexity theory are used in a metaphorical sense, they enable us to make sense of some aspects of these management issues. Using this metaphorical approach to the insights provided by complexity theory, it is the aim of this paper to give an idea of the impact of those insights on management education. In achieving this aim, I have tried to do three things. First, this paper provides a simple explanation of each of three new metaphors drawn from complexity. I go on to discuss each metaphor in relation to the

Research Memorandum • 46 • The University of Hull Business School

3

challenges it provides to my own approach to management education in the context of MBA teaching. Finally, I have drawn some conclusions which indicate the difference the complexity metaphors can make in the approach taken by management educators. The original idea for this paper was sparked off by McAndrew (1997), who applied new science concepts to school level education. This paper extends his idea by making more detailed use of the complexity metaphors to deepen understanding of the learning process. I recognise the contribution made by Aram and Noble (1999), and others at Hertfordshire, in particular Stacey (for example 1996, 1999) who has been a major influence in assisting me to understand the value of complexity in organisational settings. Their work describes how they use complexity to provide insights into issues such as the shadow system, self-organisation and extraordinary management. The present paper adopts a different and potentially complementary approach in that I try to use the metaphors of complexity to analyse the process of management education, which I, like Aram and Noble, view as of comparable value to the content of that education. A further valuable use of metaphor appears in McKenna’s (1999) paper, where he uses many of Morgan’s (1997) metaphors. I have not tried to provide a detailed explanation of organisational complexity, but I have tried to use metaphor in as precise and detailed a way as he does. In the next section, I will give a short account of the process which I adopt in teaching management case studies. The main part of the paper will consist of a section for each of the three metaphors, in which I will explain the insight, and then apply it metaphorically to show its impact on my teaching, before indicating some imperatives for teachers from the application. In the final section, I will draw conclusions in relation to teaching experience, reflecting some more general ideas of ‘management complexity’. Note on Terminology Throughout this paper, I shall use the term ‘complexity’ to denote the new science concepts of catastrophe, chaos and complexity theory. I justify this shorthand since it enables me to avoid discussion of the relationship between catastrophe, chaos and complexity theories. Following Rosenhead (1998), I shall also use the phrase ‘management complexity’ to denote the many writings where complexity is used, or is claimed to be used, to make sense of organisational issues. Acknowledgement The idea for this paper originated with Jon Simon at The University of Hull, and who co-authored an earlier version of the paper which appeared at the

4


“Management Education and Development in the Developing Nations’ conference in Al Ain, UAE in 2000. I acknowledge his assistance, and the valuable comments I received at that meeting.

TEACHING ON THE MBA I tend to make considerable use of case study material when introducing management concepts to MBA classes. Such classes are generally taught a management module (such as Strategy, or Management Thought, or Quality) in an intensive period of instruction, lasting a week full time, or over a weekend. In general the teacher will not have met the students before, so that one is trying to create a rapport with the class, and identify individual learning needs, at the same time as delivering the subject. A key point in the process, typically after three or four hours of teaching, is when the students are presented with a case study, and a set of questions that I, as teacher, invite the students to consider. The invitation is deliberately couched in non-directive language, so that the students are faced with considering both what they should discuss as well as how to do it. My motive in setting poorly structured cases is to communicate my experience that management issues are not necessarily clearly defined, and if they are this is frequently because a senior manager has created boundaries which provide the definition. The students typically go into huddles, and sit reading the case study in silence. This is normal for a short time, but when the silence extends beyond say twenty minutes, I feel it necessary to stimulate some discussion by asking a particular group whether they are clear on what is required, and perhaps suggesting an approach to defining and then addressing the problem. I am quite open that my main objective is to get the group to undergo the process of discussing the case study (and making sense of the theory taught in the lectures). It seems to me that the progress of each group can follow one path (from a collection of several), and although they do not take exactly the same steps, there are several strategies that I adopt to keep them on what I judge to be the straight and narrow. Each of these paths is a procession along the contours of some kind of attractor (see below), and the result of my effort is to jog the group onto a different path, possibly heading for a different attractor. Which attractor the group finally reaches will appear as one of several outcomes, more or less desirable from my point of view. In the following sections, I shall apply three metaphors (strange attractors, fitness, and self-organisation) to this situation. In each case, I shall provide a limited explanation of the insight from complexity theory for the reader to understand the point of the metaphor. I would encourage those who are excited by the insights to read further into the new sciences, and would recommend the


5

texts by Stewart (1989), Stacey (1999) and Marion (1999) as suitable starting points, in addition to many of the other references I have cited.

STRANGE ATTRACTORS AND THEIR UNPREDICTABILITY The idea of an attractor is in the process of entering management language (Morgan used it in his 1996 edition), and provides an attractive picture for a process which in practice is not nearly as orderly as it has been described. I have written extensively about this metaphor (Murray 2002). The chaos theory, from which the picture comes, deals with the unpredictability of events such as an unstructured case study, but also discusses the possibility of creative outcomes unforeseen by the teacher. It is probably easiest to see an attractor as being a picture, although it actually has a precise mathematical meaning. A practical example of a simple attractor is a lake in a volcano crater, into which the land falls from all directions. In such a situation, water will naturally flow towards the attractor, collect there, and unless there is an outflow, will not be able to escape from the attractor. This type of simple attractor is called a point attractor. A different attractor (known as a cycle attractor) is one in which the attractor is not a point, but rather a lake with an island in the middle. Here water will flow down the sides, and can then flow around the centre, but cannot escape from this path. Such a cyclical attractor is also called simple, since the water will follow a well defined and predictable track. But we can find more interesting (and for our purposes more useful) attractors, known as strange attractors, because the path followed by the system, unlike the water in the simple cases, does not appear to be predictable. Instead it follows a path which remains in the attractor, and which is determined by the structure of the attractor, but which appears to be random, and does not repeat itself. The most famous example is the so-called butterfly attractor reproduced below (reproduced from Gleick, J (1987) Chaos : Making a New Science New York : Penguin p28). The point about this attractor is that one cannot be sure just which path the system will follow, and in fact if we try to take the system back to a point where it originally started, we will find that the path followed will diverge more and more from what appears to have been an identical starting position.

6


Figure 1: The Lorenz Attractor

In the example used above, such an attractor might represent the behaviour of a group of students, whose progress depends on their knowledge of each other from previous experiences in the class, and their interest in the subject. The group then progresses along any one of what may appear to be different paths, all of which lie in a single attractor. The essence of the attractor metaphor is that there are many paths in a strange attractor, that the precise path depends on the initial conditions and sometimes small variations in those initial conditions can make major differences to the path followed, and that the path itself does not ‘appear’ to be ‘attracted ‘ to anything. In addition, it is impossible to be certain in which attractor the group are progressing: it may be the ‘let’s work together to define which question we are going to answer’ attractor – they may actually be drawn to the ‘I don’t know what he wants us to do’ attractor or the ‘I’ve had a busy day at work and can’t concentrate’ attractor. My interventions are intended to have the effect of confirming students’ progress if they are on the right track, and of helping them away from the attractor towards the correct one. Some groups will focus in on the task because of the strong leadership of one individual. This is especially likely to occur when the class has met several times and such leaders have emerged and been accepted as such. This person may then take a lead and organise the group to address the question set, perhaps by overriding those who aren’t clear on the question. Another group, perhaps in a class where the groups have not formed so clearly may spend much more time working out how it will function as a group (we will look at self-organisation later), and may therefore appear to make little progress. Arguably, this process may yield much better insights than a leadership approach. Each of these strategies will set off a chain of events over the next two or three hours which may end up in any one of several ways: the students may address a Research Memorandum • 46 • The University of Hull Business School

7

relevant question, but fail to organise their thoughts, or they may start a wide ranging discussion about issues which are interesting but not necessarily relevant to the question. The crucial point to make is that at this stage, I as the teacher cannot be sure whether the group is behaving in a way that will lead to a desirable outcome, or whether it will lead elsewhere, and I am not even sure that I know which attractor they are circling. It is worth emphasising that the idea of an attractor is not that the observer can see which attractor is being circled, but rather that the steps taken appear to be random (without any structure). In fact if there really is an attractor than the steps are chaotic, but spotting the difference (by techniques explained by Dooley and van de Ven 1999) will take much more data than I at any rate can observe. The progress of the group may depend very much on the initial view that it takes of the assignment: if it finds the material in the case study relevant or exciting, then it may progress down a clear path towards some insightful comments, whereas a similar case which does not catch their attention will result in a very turgid discussion. The difference might just be something apparently unimportant like the way in which the case is introduced, or its timing. Again, the unpredictable nature of the path does not mean that one can be sure that a case study is doomed – the main lesson of the attractor metaphor is that one cannot be sure of the detailed steps which will be taken : I hope that after some time, I can be rather more confident which attractor is actually in play. This example illustrates another concept, that the landscape is always changing : my intervention may be seen as altering the shape of the attractor. I am not implying that actors can always predict the result of their actions (although they might like to present this as being the case), I am trying to indicate that the inherent unpredictability in a strange attractor is increased when the structure of that attractor is itself changing. Left to their own devices, a group of students will settle down into an attractor, which we will assume will be relatively stable, and around which (even if it appears to be random) the discussion will progress. My own intervention will be based on a judgement whether that attractor is an appropriate one (by which I mean one which will inform the students). However the next part of the attractor metaphor is that the attractor itself is not necessarily permanent – it depends on the attitudes of the students involved, and it will be changing as the students are forming their group. If the group appears to be progressing around an appropriate attractor (in my judgment) well and good, but if they are heading for a less desirable one (say ‘I don’t know what he wants us to do’ or ‘I’ve had a busy day and can’t concentrate’) then I will intervene and will either try to jog the group out of that attractor, or to get involved with a process of altering the attractor, or perhaps discovering that they aren’t in the attractor I thought they were. My interim conclusion is that the attractor metaphor helps us with several imperatives for management educators.

8


1

As teachers, we cannot be sure which attractor a group of students is progressing in, or in other words, what approach they are taking to the case study.

2

We cannot predict the steps that will be taken around an attractor, or whether their approach will turn out to be fruitful, because progress may be very sensitive to the students and the situation in the class.

3

The attractor itself will be formed by the students and the teacher, and can be changed, so that it may be necessary to jump to a new attractor (and change the approach completely), but it may also be possible simply to change the shape of the attractor (by modifying the approach).

4

The teacher is manipulating the situation in order to get a desirable outcome (in my judgement) for the students.

FITNESS : ACHIEVING THE OPTIMUM The metaphor of fitness originates with Kauffman (1993,1995) who sees organisations as climbing ‘fitness peaks’. He has developed several models which spell out some of the issues of moving to increasing levels of fitness. The fitness levels depend on the interactions between the students taking part. In this view, we might see a peak of fitness or success as being where a student appreciated the model, and was able to use it in order to improve the business in which she was employed. An even higher peak might be the student realising that the concept can be used as a debating tool in order to advocate her product or project. A lower peak, or even a trough might be a student failing to grasp the point and being pilloried at work for trying to mislead his/her colleagues. Kauffman (1995: 257) has provided a fanciful picture which appears as Fig 2 with permission. A key issue is what constitutes the success criterion which makes a peak high and therefore desirable. In my classes, I describe it as being some sort of combination of theory and practice, leading to some well-justified conclusions. The balance between these three elements will have the effect that if one becomes too strong, then the group will find itself on a minor peak or perhaps plateau. Altering the balance between theory and description will tend to take the group up a peak, and providing a good justification will increase the height still further.


9

Figure 2: An energy landscape showing a system trapped on a poor, high-energy local minimum.

One of the dangers of such a landscape is that the group may get itself up a peak which doesn’t lead to anywhere higher, say because a good balance between theory and practice is actually addressing an irrelevant question. This points out the metaphor that in optimising one’s efforts, it is possible to reach a point from which progress can only be made by going downhill (say by rethinking one’s approach to a problem), before making any more progress. Kaufman’s analysis points out that one can be trapped on a lower peak, and that the only way to get higher is to go down hill and then go up again. In the same way, students need to realise that reaching the point where they understand and can apply a management model to a practical situation may need to be unlearned if they are going to use that model in a context where it will be used as part of political debate. For example, one may present the concept of the BCG matrix (Fig 3 from Johnson, G and Scholes, K (1999) Exploring Corporate Strategy, 5th edition : Hemel Hempstead : Prentice Hall) as an objective approach to classifying the products being sold by a company, and their relative calls on funding for product investment. However, one may also use the model as a set of concepts to justify a course of action in which a product champion is presenting a very subjective (and political) appeal for more investment in her pet project. The issue of the fitness of a network is an alternative metaphor. Marion (1999) discusses the organisation as a network of individuals who are more or less tightly coupled to one another by positive and negative feedback loops. The behaviour of one individual is strongly affected by another to whom she is tightly coupled, and only slightly affected by loose coupling.

10


Market share High

Low

High

Stars

Question Marks

Low

Cash Cows

Dogs

Market growth

Figure 3: The original Boston Consulting Group Matrix (BCG)

A system consisting of tightly coupled elements will tend to react very quickly to an outside influence, and will either respond to the influence in the desired way (that is the way it was designed to do) or it will go dramatically off track, since it has limited ability to absorb unexpected inputs. Thus a student who takes a very rigid view of strategy may well solve the problem in the case study quite effectively (by precisely analysing the positions of several competing products on the BCG Matrix), or perhaps not see the point of the exercise if, apparently, not enough information is given about market growth and share. On the other hand, a loosely coupled system will tend to deal with inputs by damping down their effect, and only responding in a non linear way, or if it is very loosely coupled, by not responding at all. Such students will tend to address the issue by looking at a problem as an exercise of pleasing the teacher by going through the motions required by the case study, or may even not be motivated to discuss the problem at all. I am trying to teach students to ask the right questions (as well as giving the right answers), and I would suggest that the appropriate response is to analyse the problem from several points of view, or accept that a student’s view would reflect his own interests, for example, a marketing manager might characterise his own projects as ‘Stars’ which require marketing investment at the expense of someone else’s ‘Cash Cow’. A complexity view would characterise this discussion as the need for a system to adopt a position where it is ‘fit’ to deal with the problem context: in certain situations a tightly coupled / rigid approach is what is required, and in other situations a looser approach with more questioning is what is needed. The tightly coupled approach in a group tends to manifest itself on the basis that there is a clear answer to every problem. This may be caused by the fact that many of my students (like myself) have a technical education, but it also reflects


11

(I presume) the classic approach to management which writers like Stacey are trying to question. Such a tightly coupled approach is entirely appropriate for solving problems within a paradigm (as Kuhn [1972] would put it). In such a case students (and professionals) are supposed to apply well defined and proven techniques to problems which make sense in that paradigm, and which can then be comprehensively solved. I am thinking here of how a chemical engineer might design a plant for a well known process where the design might consist in little more than a copy of existing plants. This is not to minimise their skill, but it is to emphasise that a team of chemical engineers, coupled together by their discipline, might work together on different elements of the design, and in so doing produce the result very quickly. If however in the design, a major problem arose – the plant is not allowed to undertake a particular part of the process for local environmental reasons – then the group may not be able to deal with the issues of negotiating with local managers and the community to resolve the problem. At the other end of the scale, a very loosely coupled group might be appropriate where great creativity was required – say in designing a major presentation, and where the different elements (or at least the key elements) needed to communicate their intrinsic value rather than all ‘fit together’ as a whole. In addressing the type of case study that I am setting, I am expecting students to strike a balance between the theory that I have taught them (and that they have learned on other modules) and the practical situation with which they are dealing. The ‘best’ answer is the one that shows these two elements and then goes on to use the analysis to justify some practical conclusions. As in other sections, it is worth setting out some further imperatives 1

When we see a group as forming a network, it is clear that the extent of coupling between its members (and indeed between its members and other groups) will affect the approach taken to the sort of case study questions set.

2

There are different opinions as to the number of interactions or couplings which should be considered in computing the level of fitness. Some follow Kauffman and consider a small number (say two or three) as appropriate, while others tend to consider larger numbers – I tend to favour groups of four, five or six students for this sort of work.

3

The fitness of a peak or a network will be determined by the extent to which its level of coupling is appropriate to the challenges facing it. This fitness may be viewed in a very mechanical way or with a more organic approach.

12


4

Ultimately, it is the teacher who decides what are the success criteria for the fitness peak or network, since it is he who controls the assessment of the students.

SELF ORGANISATION : WHAT THE GROUP DOES FOR ITSELF The paper by MacIntosh and MacLean (1999) makes the distinction between seeing a complex system as a dissipative structure, and seeing it as a system which is able to adapt and self-organise on the ‘edge of chaos’ . It is interesting to look at these two different approaches in relation to a group given a problem that it is having difficulty solving. The dissipative approach to complexity takes account of the idea that the group reaches a bifurcation point (an example appears as Fig 4 from their paper with permission), at which it can continue along its old ways, or start to do something new. The continuation would involve taking the ‘learning by rote’ approach, and some groups will realise that this is not the appropriate way when I am the teacher. Some groups may not realise this, and they will then continue to take an approach of representing the textbook material and/or the facts of the case.

Figure 4: The Bifurcation Diagram

The authors describe the process as one of a system moving, or being made to move, from an equilibrium state to a chaotic one, and then becoming ordered again (by an input of energy required by the second law of thermodynamics) on the basis of underlying laws. Using this approach, we may see the group getting together and trying to address the problem. The group will demonstrate complex adaptability by even consulting the teacher where appropriate and by approaching the question in a way which will meet the group’s interests. Perhaps the students may recognise the bifurcation point when they feel they are on a trajectory which is in fact leading them nowhere, and so they ask themselves ‘what does he want us to do ?’


13

At the bifurcation point there are two alternatives. The group can continue along its current path, which will mean that students will continue to seek the ‘right’ answer by simply quoting from the textbook and describing the facts of the case. Alternatively, it can be set off on a different path, by adopting a more critical approach. The group might be given some further input (I will go across to a group who are rather quiet, and ask them whether they have a problem). I can then tell them not to worry about getting the ‘right’ answer but rather to set out on their own. After a few false starts, the students discover a different way of looking at the problem. In doing this they (or we) will have altered the ‘deep structure’, the rules which govern the ‘success’ of their activity. MacIntosh and MacLean (1999) see this process as disturbing a comfortable equilibrium, and requiring the new rules to be relearned. The group gets an insight (either from itself or more likely by an intervention by the teacher), and then reorganises itself according to some very basic underlying principles (perhaps the need to make a presentation to the class within the next two hours). The importance of this view of self organisation is that the group receives a stimulus from outside, which pushes it far from equilibrium. This seems to justify the role of the teacher in intervening when a group seems to be getting too comfortable. Sometimes the stimulus may come from a member of the group talking to another group. As a result of the stimulus which might give the group the sense that it is completely lost, it then reorganises itself and proceeds to use the new rules. We may see the whole process of learning as being an edge of chaos phenomenon. The idea of the edge of chaos is that a system in equilibrium is essentially one which is moribund, and that for creativity and innovation, it is necessary that the system should move away from equilibrium, and adopt some elements of chaos and unpredictability. If it goes too far it will become chaotic and unmanageable, but if it can maintain a balance between order and chaos, it will be in a creative state where it will absorb new ideas, and be able to take them into practical application. The ‘edge of chaos’ position is where the teacher stimulates the students’ thoughts by being reasonably challenging, and where the students (or at least enough of them) are inspired to explore the ideas. In this view, the teacher creates an environment where the situation is balanced between presenting the material in a way which is so accessible to the students ‘spoonfeeding’ that they remain in what complexity calls the stable state, or presenting the material in so esoteric a way that they completely fail to obtain any inkling of what is intended. In this situation, the group of students with the unstructured problem may be expected to adapt its knowledge and experience, and to organise itself to deal with what it decides the problem will be. In this situation, the wise teacher will let the group get on with it. I at least feel that the process of doing a case study is as important as the result, which I check anyway by asking students to do a

14


presentation of their findings. The ‘successful’ group of students will be the one which is fit enough to keep a balance between stability (perhaps in terms of offering to do a presentation) and the chaotic experience of all group members wanting to contribute their ideas. Anderson’s (1999) view of the essence of complexity is that the students have their own agendas, and each will behave in a way that suits his or her objectives, and that the group will self-organise itself by importing energy. His further point is that the group, if it is truly to succeed, will coevolve to the edge of chaos, where it strikes a balance between being so rigid that it just goes through the motions of the case, and being so creative or lateral, that it goes off and discusses something irrelevant to the case. As a teacher, I am trying to allow my students to explore the relevance of a number of concepts which are new and where the case study gives the freedom to explore outside the framework of day to day pressures. I see this as balancing on the edge of chaos between taking a very positivist approach to the models presented (getting the answer right) and getting used to a more interpretivist process of questioning the models, and indeed using them as a language with which to discuss business problems. What concerns me here is to discuss how a group will organise itself to achieve this balance. The self-organisation takes many forms, including the emergence of a leader who essentially Organises the group, but also to some interesting situations where the leadership (or at least the talk) seems to rotate around several members of the group. The edge of chaos metaphor may then be applied as the group deliberately keeping itself away from the stable state where students try to give the right answer (either by demonstrating an understanding of the models they have been taught, or by demonstrating that they have grasped the factual details of the case). A group which restricts itself to this position is losing (at least in my view) any opportunity to think laterally – it is frozen in a stable state, where its learning simply repeats the well trodden paths of absorbing facts so that they can be reproduced when necessary for example in assignment questions or examinations. There is nothing wrong with such an approach when a student is learning a technical subject – it seems to be me much less desirable when a student is trying to understand something as complex as organisational behaviour. Clearly a group can go too far. Creative discussion of the most recent football match seems to me to give a limited insight into the questions I want raised – this is the area of chaos within which it is not possible to manage the learning process. This is the sort of situation where students might ask why a company in a case study even wants to stay in business – this may be entirely appropriate in


15

the work situation itself (assuming some sort of available exit strategy) but rather misses the point of the case study. Indeed, Dooley and van de Ven (1999) might even argue that this area becomes one of random behaviour rather than chaos – the essence of chaos is that there is an attractor around which the group is progressing. My view is that a position on the edge of chaos appears to be one where the system is poised between a stable attractor (order), and a strange one (chaos). What I am therefore looking for is a questioning attitude where students do critically review the options open to the organisation featured in the case, and get used to the idea that they apply the knowledge from the course to practical situations. The ideal outcome here is that the group organises itself to produce these sorts of outcomes, and in so doing increases its depth of learning, and hopefully lets each member take away some insights that they might have missed by just reading the textbook. But a further point is that this is an essentially risky business – there is always the danger that the group (or individual students who just opt out) will revert to studying the ‘factual’ material only (going back to the stable safe region), or not be able to get into the debates about what should be done (and go off into the chaotic area – a form of denial). Indeed, it is this author’s experience that one person’s creative idea is another person’s ‘off the wall’ point of view, so that the maintenance of a position on the edge of chaos is very much a matter of judgment. The test of the correct balance is discussed in Anderson’s paper (1999) and depends, as is discussed in networks section of this paper, on an appropriate balance with the environment. The imperatives for management educators prompted by these two approaches are as follows. 1

The ideal learning experience represents a balance between looking at learning by rote (doing things right) and creative and critical insights into situations (doing the right things). A dissipative view sees the need for an intervention which jolts the group into a different mindset, while an edge of chaos view sees this balance falling between stability and chaos.

2

The group will require an external stimulus, and will organise itself on the basis of deep rules. Alternatively, the group will organise itself to maintain the position at the edge of chaos, on the basis of the individual agenda of its members – this process will be more or less successful in maintaining the balance required in 1 above.

3

In both cases, some form of openness to the environment is required, through which energy can flow to maintain the order in the group. The flow

16


may be as a result of group members being open to the external stimulus (dissipative) or the environment (edge of chaos). 4

The process of management education is to teach students where the ‘edge of chaos’ may be found.

CONCLUSION In this paper, I have set out a number of ways in which the new metaphors drawn from catastrophe, chaos and complexity theory should provoke and stimulate teachers of management. The area of what Rosenhead (1998) terms ‘management complexity’ is growing at a great rate. In spite of his concern that complexity has yet to demonstrate that it works in organisational situations, or even that it generates new insights, it is nevertheless an area where many academics are spending considerable energy, and are making claims for the value of using complexity to encourage managers to adopt what is often termed a non-linear approach to their problems. Perhaps this paper is the first in the area of ‘management learning complexity’ or even ‘management education complexity’. As such, it suggests that complexity provides some very useful metaphors for practical management educators. The first conclusion to draw is that the metaphors seem to be very appropriate in deepening our understanding of the process of management education. These insights from complexity provide a rich source of metaphor, and they are summarised below. The idea of an attractor (especially a strange attractor) is a useful one, partly because of the (apparently random) progress around the attractor, but also about the fact that an observer cannot be sure which attractor is operative. This point seems critical to the learning process, where the teacher is not in a position to tell students what the ‘right’ answer is. Furthermore, progress along a trajectory in the attractor may not even seem like progress – the path taken is unpredictable, but doesn’t necessarily ‘reach’ the attractor itself: this seems to mirror many learning experiences, where students can learn almost in spite of the formal procedures. Finally, although the teacher may try to influence where learning will occur, the result of a potential intervention will not be predictable. The concepts of fitness peaks and the fitness of a network, link in well with the need to blend theory and practice. Too rigid an approach will have the effect of a very limited learning experience, or the destruction of the group itself. Too relaxed an attitude will mean that the appropriate effort is not expended. I see myself as encouraging students to look at management problems as situations where they have some (in certain cases significant) ability to construct the problem. I am also trying to get them to think beyond a simple cause and effect


17

approach (many of them tend to come from rather ‘linear’ backgrounds like science, engineering and accounting) and to explore the possibility that there are many ways of addressing such problems The idea of self-organisation and the way it may manifest itself (as a dissipative structure or the edge of chaos) clearly gives insights (perhaps even normative insights) into the way groups work in the classroom (and elsewhere). I am conscious that in my own description in this paper I have wavered between the dissipative approach – ‘there are a number of identifiable possible paths down which the case study can proceed, and if the students don’t hit on one, it is my job to encourage them to find one’ – and an edge of chaos approach – ‘the group usually works out how to use the case and all I have to do is provide them with encouragement and some feedback'. In both cases it is clear that the group needs to remain open to external influences, either to the energy required from an external source to keep a dissipative system in play, or to the group itself bringing in the learning which enables it to maintain itself between chaos and order. My second conclusion is that as a teacher, I have to be prepared to take a complexity approach, because I don’t know what is going to turn up, and there may well be a problem in assuming I know how ‘students’ behave. Some form of openness to the environment is required, through which energy can flow to maintain the order in the group. The flow may be as a result of group members being open to the environment (edge of chaos) or the external stimulus (dissipative) brought in by their desire to share their views and experiences with group members. In accepting the unpredictability of the process, I am not suggesting that the teacher just sits back and watches it all happen. The self-organisation of the group may be helpful or unhelpful from my standpoint, and I am therefore going to intervene to achieve what I judge to be a desirable outcome for the students. Whether I succeed in doing this will depend on the interrelations between myself and the group (the edge of chaos view) and the extent to which the ground rules are altered (the dissipative view). My third conclusion is that the process of management education conveys the value of complexity metaphor just as well as the content of the education. If management were linear (cause and effect) we could teach it in a disciplined way like chemistry or accounting, where the education process is self-contained. It is in fact complex (as well as complicated), and therefore requires much more open ended teaching techniques. I have tried to show that complexity provides a valuable metaphor for understanding the process of individual learning through management education. From this perspective, it gives insights to teachers as to how they might structure their material, balancing ‘facts’ with more critical ideas. I suggest that the process of management education may in some cases transfer

18


as much learning as the content. The insights gained into the learning process may well be of value in the transfer of learning from the process and content of classroom studies into practical management situations. My experience of practical management convinces me that the process (how one gets things done) of management is just as complex as the content (what should be done). My approach to teaching is intended to convince students that the insights into process provided by classroom exercises may be carried over into their work as managers. Finally, I can’t be sure that the use of complexity isn’t just a clever form of manipulation. It may be that the insight from complexity that management education is not simply cause and effect, but rather includes complex feedback loops is not itself only seeing part of the problem. I am concerned that complexity may just be a more subtle way of manipulating a class to achieve the ‘right’ outcome, which I have described above. The paper has only hinted at this issue, which I believe complexity theory has to address if it is to contribute anything to organisational analysis or to management learning beyond the rich source of metaphor I have discovered above.


19

References Anderson, P. (1999). Complexity theory and organisation science, Organisation Science, 10(3) 216-232. Aram, E. and Noble, D. (1999). Educating prospective managers in the complexity of organisational life, Management Learning, 30(3) 321-342. Dooley, K.J. and Van de Ven, A. (1999). Explaining complex organisational dynamics , Organisation Science, 10(3) 358-371. Gleick J. (1987) Chaos : Making a New Science, New York, Penguin p28 Johnson, G. and Scholes, K. (1999) Exploring Corporate Strategy, 5th edition, Hemel Hempstead, Prentice Hall. Kauffman, S. A. (1995). At Home in the Universe: The Search for Laws of Complexity. Oxford University Press, New York. Kauffman, S. A. (1993). The Origins of Order: Self Organisation and Selection in Evolution. Oxford University Press, New York, Kelly, K. (1994). Out of Control: The New Biology of Machine. Addison Wesley, New York. Kuhn, T. (1972). The Structure of Scientific Revolutions. University Press, Chicago. Lengnick-Hall, C. A. and Wolff, J. A. (1999). Similarities and contradictions in the core logic of three strategy research streams, Strategic Management Journal, 20 1109-1132 McAndrew, D. (1997). Chaos, complexity and fuzziness: Science looks at teaching english, English Journal, 86(7) 37-43. McKenna, S. (1999). Learning through complexity, Management Learning, 30(3) 301-320. MacIntosh, R. and MacLean, D. (1999). Conditioned emergence: A dissipative structures approach to transformation, Strategic Management Journal, 20 297-316. Marion, R. (1999). The Edge of Organisation. Sage, London. Morgan, G. (1997). Images of Organisations, 2nd edition, Sage, London. Murray, P.J. (1998). Complexity theory and the fifth discipline, Systemic Practice and Action Research, 11(3) 275-293. Murray, P.J. (2000). A complexity model of strategy process, International Journal of Applied Management, 1(2) 87-104. Murray, P.J. (2002). Constructing futures in strange attractors, University of Hull Business School Working Paper, 33. Rosenhead, J. (1998). LSE OR Working Paper, London School of Economics. London. Stacey, R. D. (1993,1996,1999). Strategic Management and Organisational Dynamics. Pitman, London. Stacey, R. D. (1995). The science of complexity : An alternative perspective for strategic change process, Strategic Management Journal, 16(8) 477-495. Stewart, I. (1989). Does God Play Dice? The New Mathematics of Chaos. Basil Blackwell, Oxford.

20


Deleted: *L

Previously published Business School Research Memorandum Series Please note that some of these are available at: http://www.hull.ac.uk/hubs/research/memoranda 45 44 43

42 41 40 39 38

37 36

35 34 33 32

31 30

29 28 27

Hon. Dr. Diodorus Kamala (2004). The Voices of the Poor and Poverty Eradication Strategies in Tanzania Michael R. Ryan (2003). Vertical Integration Results and Applications to the Regulation of Supermarket Activity Michael A. Nolan and Felix R. Fitzroy (2003). Inactivity, Sickness and Unemployment in Great Britain: Early Analysis at the Level of Local Authorities Keshab R Bhattarai (2003) An Analysis of Interest Rate Determination in the UK and Four Major Leading Economies Keshab R Bhattarai (2004) Macroeconomic Impacts of Consumption and Income Taxes: A General Equilibrium Analysis Juan Paez-Farrell (2003) Business Cycles in the United Kingdom: An Update on the Stylised Facts Juan Paez-Farrell (2003) Endogenous Capital in New Keynesian Models Philip Kitchen, Lynne Eagle, Lawrence Rose and Brendan Moyle (2003). The Impact of Gray Marketing and Parallel Importing on Brand Equity and Brand Value Marianne Afanassieva (2003). Managerial Responses to Transition in the Russian Defence Industry José-Rodrigo Córdoba-Pachón and Gerald Midgley (2003). Addressing Organisational and Societal Concerns: An Application of Critical Systems Thinking to Information Systems Planning in Colombia Joanne Evans and Richard Green (2003) Why did British Electricity Prices Fall After 1998? Christine Hemingway (2002). An Exploratory Analysis of Corporate Social Responsibility: Definitions, Motives and Values Peter Murray (2002). Constructing Futures in New Attractors Steven Armstrong, Christopher Allinson and John Hayes (2002). An Investigation of Cognitive Style as a Determinant of Successful MentorProtégé Relationships in Formal Mentoring Systems Norman O'Neill (2001). Education and the Local Labour Market Ahmed Zakaria Zaki Osemy and Bimal Prodhan (2001). The Role of Accounting Information Systems in Rationalising Investment Decisions in Manufacturing Companies in Egypt Andrés Mejía (2001). The Problem of Knowledge Imposition: Paulo Freire and Critical Systems Thinking Patrick Maclagan (2001). Reflections on the Integration of Ethics Teaching into the BA Management Degree Programme at The University of Hull Norma Romm (2001). Considering Our Responsibilities as Systemic Thinkers: A Trusting Constructivist Argument


21

26

25 24 23 22 21 20 19 18 17

22

L. Hajek, J. Hynek, V. Janecek, F. Lefley, F. Wharton (2001). Manufacturing Investment in the Czech Republic: An International Comparison Gerald Midgley, Jifa Gu, David Campbell (2001). Dealing with Human Relations in Chinese Systems Practice Zhichang Zhu (2000). Dealing With a Differentiated Whole: The Philosophy of the WSR Approach Wendy J. Gregory, Gerald Midgley (1999). Planning for Disaster: Developing a Multi-Agency Counselling Service Luis Pinzón, Gerald Midgley (1999). Developing a Systemic Model for the Evaluation of Conflicts Gerald Midgley, Alejandro E. Ochoa Arias (1999). Unfolding a Theory of Systemic Intervention Mandy Brown, Roger Packham (1999). Organisational Learning, Critical Systems Thinking and Systemic Learning Gerald Midgley (1999). Rethinking the Unity of Science Paul Keys (1998). Creativity, Design and Style in MS/OR Gerald Midgley, Alejandro E. Ochoa Arias (1998). Visions of Community for Community OR


Centre for Economic Policy Research Papers prior to merging with the Business School in August 2002

283 Naveed Naqvi, Tapan Biswas and Christer Ljungwall (2002). Evolution of Wages and Technological Progress in China’s Industrial Sector 282 Tapan Biswas, Jolian P McHardy (2002). Productivity Changes with Monopoly Trade Unions in a Duopoly Market 281 Christopher Tsoukis (2001). Productivity Externalities Tobin’s Q and Endogenous Growth 280 Christopher J Hammond, Geraint Johnes and Terry Robinson (2000). Technical Efficiency Under Alternative Regulatory Regimes: Evidence from the Inter-War British Gas Industry 279 Christopher J Hammond (2000). Efficiency in the Provision of Public Services: A Data Envelopment Analysis of UK Public Library Systems 278 Keshab Bhattarai (2000). Efficiency and Factor Reallocation Effects and Marginal Excess Burden of Taxes in the UK Economy 277 Keshab Bhattarai, Tomasz Wisniewski (2000). Determinants of Wages and Labour Supply in the UK 276 Taradas Bandyopadhay, Tapan Biswas (2000). The Relation Between Commodity Prices and Factor Rewards 275 Emmanuel V Pikoulakis (2000). A “Market Clearing” Model of the International Business Cycle that Explains the 1980’s 274 Jolian P McHardy (2000). Miscalculations of Monopoly and Oligopoly Welfare Losses with Linear Demand 273 Jolian P McHardy (2000). The Importance of Demand Complementarities in the Calculation of Dead-Weight Welfare Losses 272 Jolian P McHardy (2000). Complementary Monopoly and Welfare Loss 271 Christopher Tsoukis, Ahmed Alyousha (2000). A Re-Examination of Saving – Investment Relationships: Cointegration, Causality and International Capital Mobility 270 Christopher Tsoukis, Nigel Miller (2000). A Dynamic Analysis of Endogenous Growth with Public Services 269 Keshab Bhattarai (1999). A Forward-Looking Dynamic Multisectoral General-Equilibrium Tax Model of the UK Economy 268 Peter Dawson, Stephen Dobson and Bill Gerrad (1999). Managerial Efficiency in English Soccer: A comparison of Stochastic Frontier Methods 267 Iona E Tarrant (1999). An Analysis of J S Mill’s Notion of Utility as a Hierarchical Utility Framework and the Implications for the Paretian Liberal Paradox 266 Simon Vicary (1999). Public Good Provision with an Individual Cost of Donations 265 Nigel Miller, Chris Tsoukis (1999). On the Optimality of Public Capital for Long-Run Economic Growth: Evidence from Panel data


23

264 Michael J Ryan (1999). Data Envelopment Analysis, Cost Efficiency and Performance Targetting 263 Michael J Ryan (1999). Missing Factors, Managerial Effort and the Allocation of Common Costs

24
