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Complexity Science and Management




M Mitchell Waldrop: Complexity, Penguin, 1994, 359pp, £8.99pb

John Casti: Complexification, Abacus, 1994, 320pp, £7.99pb

Paul Ormerod: The Death of Economics, Faber and Faber, 1994,230pp, £6.99pb

Ralph Stacey and David Parker: Chaos, Management andEconomics: The Implications of Non-Linear Thinking, IEA HobartPaper 125, 1994, 112pp, £9.00pb

H Richard Priesmeyer: Organisations and Chaos, Quorum Books,1992, 253pp

Kevin Kelly: Out of Control, 4th Estate, 1994, 666pp, £8.99pb

Complexity - a word to send shivers up the spine of thehard-pressed manager. Is the world a complex place? You bet itis. Not at all like the case studies in books, or in your MBAprogramme. So much to take in, and so little time to decide whatto do.....Thoughts like this surely enter many heads at varioustimes. Is there insight just around the corner?

There is a growing interest in business circles in thedeveloping field of complexity science, often described in termslike "The emerging world between order and chaos".Practitioners from arenas as diverse as economics, physics,biology, mathematics, linguistics and philosophy are comingtogether to re-examine the way in which we treat and evaluate theworld around us. The results challenge the conventional axiomaticframework which science and much of the rest of human knowledgehas inhabited since Newton. It is a cousin of chaos theory, andis oft mistaken for that branch of mathematics.

Books are appearing which start to present the conclusions ofthe pioneering workers in complexity to a wider audience. Some ofthese are related to business areas explicitly, others are aimedat a more general educated audience. Conferences have been heldin San Francisco and London in the first half of 1995, looking at"Complexity and Strategy". The London School ofEconomics is about to commence a major research project into howcomplexity is handled by businesses, and how complexity ideas canhelp strategists and managers in their endeavours.

In this Essay Review, I want examine some books so farpublished and find out whether complexity has a part to play indeveloping approaches to management, strategy, leadership andother business-related fields. Do these books lead us to suchapproaches, directly or indirectly? What hopes are there forfuture developments? And who stands to gain from theirapplication?

There are a number of meanings to the word"complexity" around, and it will be as well to be clearabout how we're using it here. We do not mean simply"complicatedness". A system or artefact can becomplicated or intricate without have any Complexity attributes.Peter Senge makes the point well in drawing the distinctionbetween "detail complexity" (for instance highlyintricate machines or management systems) and "dynamiccomplexity" (where inter-relationships between elements in asystem are based on feedback loops, and are many and varied).

What is Complexity?

In this context, the Complexity we refer to is similar toSenge's dynamic complexity, common to a series of developments inscientific thinking which has occurred over the past ten years orso. There are some attributes which are associated with ComplexSystems. Such systems are self-referential (ie their elementsinteract in a systemic fashion) and contain elements of bothpositive and negative feedback. They are non-linear, so that asmall change can lead to much larger effects in other parts ofthe system and at other times. Systems which display these traitshave some interesting properties:

? They are non-deterministic. Wholly accurate predictions of future states cannot be made, however well the current and past states are known.

? They show emergent properties - patterns which result from the overall action of all the elements of the system.

Perhaps surprisingly, Complex Systems can be made up of manyrelatively simple parts. An example might be ants in a nest,molecules of air, birds in a flock, people in an organisation, orelements in a computer program. It has been shown, however, thateven if all the details of the individual parts are known(as has been demonstrated using certain types of computerprogram), the overall system can still be Complex andnon-deterministic, and can produce effects which are real andobservable, but cannot be determined by examining a singleelement out of context.

These results are rather counter-intuitive to those of usbrought up on the reductionist assumption that knowing all aboutthe parts will enable us to understand the whole. In a complexsystem, the whole shows behaviours which cannot be gleaned byexamining the parts alone. The interactions between theparts are crucial, and produce phenomena such asself-organisation and adaptation. One example in the businessworld might be the ways that certain patterns of behaviour (knownby some as "corporate culture") emerge in anorganisation, despite the fact that no one individual wants them,or set out to design them.

Watching a Complex System develop over time is akin towatching crystals grow, clouds form or stock markets move. Theirfutures seem to emerge from the present in a seamless way, whichis nonetheless unpredictable in detail. The kinds ofthings that happen can be discovered by observation, but theprecise future remains hidden until it appears.

Some of you may be thinking that this description isreminiscent of "chaos theory". Some authors havereferred to Complexity as "the edge of chaos", and thediagram below (Figure 1) may illustrate why. Computationalresearch into certain types of complex systems such as cellularautomata have indicated that there is a range of general types ofbehaviour which a system can go through as a particular parameter(illustrated in the figure as lambda) is varied. These are:

1. Stability - the system remains frozen in a certainconfiguration.

2. Periodicity - the system shows periodic motion, but stillcannot change or develop.

3. Chaos - where the system changes in a random fashion,showing no structure.

4. Complexity - the system develops in a way which shows bothsome continuity and also some novelty.

(Figure 1)

Figure 1: Complexity and the edge of chaos (from Trisoglio,1995)

If all this sounds rather theoretical, some examples ofComplex Systems might help to illustrate the point. Stock marketsare a good case in point. The market moves in a way that dependson the actions of a large number of agents. There are patternswithin the movements, and both positive feedback (rising marketsleading to further increases as traders leap aboard a perceivedbandwagon, or falling prices leading to a collapse) and negativefeedbacks (rising prices stemmed by profit taking, or heavyselling being stabilised by buyers entering the market) arepresent. The market movements are not random, and yet are notwholly predictable either. The market's future seems to emerge astime passes.

These systems have one thing in common - they do not followthe simple "machine-based" paradigm from which ourcustomary ideas on organisation, structure and strategy arederived. Rather than attempting to simplify the complex world inorder to understand it, they tend to examine how the complexitycan be used to advantage. Rather than aim for a perfectequilibrium, new approaches seek to generate novelty and movementfrom which new possibilities can emerge. For an audience ofmanagers attempting to produce change in their organisations,this sounds as if it might be useful! So, how do these six bookslight the way ahead?

The various books which we will examine in this article allset out to discuss the ways that Complexity science has developedand is relevant. Only two of them (Priesmeyer and Parker &Stacey) are explicitly aimed at a business audience, and thosetwo cover relatively small parts of this large and excitingtopic.

Science Overviews

Mitchell Waldrop's "Complexity" offers a highlyreadable account of development of Complexity science over thelast ten years. Waldrop focuses on the people involved, theirvarious specialisms and views (often regarded as faintlyheretical in some circles), and their coming together at theSanta Fe Institute. The SFI was set up as a world centre forComplexity research in the mid 1980s, and most of the leadingdevelopers in the field have spent time there.

Waldrop starts his explorations with the story of BrianArthur, an economist who had long suspected that conventionaleconomics, with its assumptions of equilibrium and rationalagents, was not the best possible description of the real world.Arthur was interested in "increasing returns", orpositive feedback effects, a phenomenon which could not happenunder the assumptions of classical economics. Arthur's researchhad led him to examine the ways in which these increasing returnsdid appear. The struggle between VHS and Betamax video formatsseemed a good example - the more people had VHS, the more demandthere was for pre-recorded tapes in this format, the more tapesthe film-hire shops stocked - leading to yet further increases indemand for VHS machines! Arthur's work showed that such systems,with two competing players, cannot be predicted but the ultimatevictor is determined by small advantages accrued early on in theprocess. The small advantages then amplify until the point whereVHS is the dominant format. Arthur identified other examples ofthis phenomenon, including the 12-hour clockwise rotating clockface (which had trounced its rivals, including a 24 houranti-clockwise version) in the 14th century.

Waldrop goes on to relate the stories behind Arthur's arrivalat Santa Fe, and his encounters with the other researchers there.He comes across John Holland, whose interest in how complexsystems such as economies and organisms adapt is a source offascination. Holland's observation that organisms andorganisations are not in equilibrium with their environments -the two are continually evolving and changing - is an interestingthought-provoker for the manager attempting to arrive at the"best" five-year strategy for his business unit. Whereconventional thinking in marketing has companies discoveringniches to fill, Holland remarks that the niches and the companiesare co-evolving, and new niches are being created all the time.Holland warns that an organism in equilibrium with itsenvironment isn't just stable - it's dead!

"Complexity" (unlike most of the other booksdiscussed here) is actually a splendid yarn. Waldrop tells hisstory with a good pace and doesn't get bogged down in thetechnical details of the science involved. There are many pointsof interest, including a good summary of the various attemptswhich have been made to understand some simple interactionalsystems, such as John von Neumann's Prisoners Dilemma. Thevarious ideas which von Neumann proposed is his development ofgame theory are often to be found in discussions of Complexity,being relatively simple examples of systems where no single partycan determine the overall outcome - the result depends on theinteractions between all the players.

Organisations are also considered briefly by Waldrop. Hediscusses the spectrum of organisations that might be found alongthe order - chaos axis in Figure 1 of this article. At the"ordered" end are machine-like organisations, whereeach job is highly specified and the amount of latitude given toindividuals is low. The aim of this kind of organisational designis to produce a consistent and predictable functioning, and as weall know there is a degree of success to be had from that.However, the amount of learning and change in a completelyorganised system is very small. At the chaotic end of thespectrum we might envisage an "organisation" actingalmost randomly, with the various agents having no contact witheach other and working at cross purposes. Somewhere in betweenmight be considered to be the point at which the"fitness" of the organisation, its ability to produceresults and evolve, is maximised.

Waldrop give many glimpses of the work of the SFI. While hiseasy style may leave some wanting more information, this book isaccessible to general readers and is a good place to startfinding out about the overall range and impact of the field. Thisbook was originally published in 1992 in the USA, which mayexplain why the bibliography is short and consists of referencesto technical scientific literature. However, as an overview ofthe whole field in all its forms, this work still takes somebeating.

John Casti's recent paperback "Complexification" isa slightly different attempt to produce a lay person's guide toComplexity science. As such, he succeeds well. Casti subtitleshis work "Explaining a paradoxical world through the scienceof surprise", and focuses on a number of areas whereComplexity leads to results which are surprising or unexpected toour minds schooled in the logical thinking styles of Aristotleand Newton. He explores the various counterexamples to the"commonsense" approach, focusing on scientific andmathematical examples.

This is another good popular science exposition. Only in thefinal chapter does the author pull these points together andstart to address, sadly briefly, the impact on our world ofpeople and organisations. His conclusions: Simple systems havepredictable behaviour, few interactions and feedback loops,centralised control and are easily dismantled into smallerworking parts, whilst Complex systems have unpredictablebehaviour, lots of interactions and feedback, diffusion ofauthority and are irreducible. A live rabbit cut into two halvesis not two live half-rabbits! Casti's list of further reading isalso good, and this book will be of interest to those for whomscience has been a friend rather than a matter of dread.

Both of these books give excellent accounts of the range ofideas and phenomena which are grouped under the Complexitybanner. They are both thought provoking for business leaders andorganisational developers. However, there are no specificdevelopments of business related topics here.

Complexity and Economics

A more specific account of the impact thatComplexity may have on business, and specifically economics, isgiven by Paul Ormerod. "The Death of Economics" is asplendidly accessible account of Ormerod's disenchantment withclassical economics, with its assumptions of equilibrium,rational agents, continuums (ie infinite numbers) of traders andfancy mathematics. Ormerod is an economist and writer who isclearly familiar with his subject, yet his writing is if anythingeven more accessible to the educated reader than Waldrop. Heexamines the roots of economics in the machine-age science of the18th and 19th centuries, and its development into a branch oftheoretical mathematics in the 20th century. The originalassumptions, such as diminishing returns of scale and rationalagents acting to maximise their welfare, do not bear up whencompared with the real world, says Ormerod. They do, however,give the benefit of producing equations which are soluble usingrelatively simple calculations.

Ormerod goes into some detail in his dismantling of theframework within which (he would have us believe) economistsfunction. He is particularly scornful of the kind of economicswhich immerses itself in complex maths and explores the netherregions of unreal worlds, which bear no relation to our own. Thisis in contrast to the kinds of assumptions made by, for example,physicists or engineers - which may be sweeping, but producetangible results which are checkable against reality.

Central to Ormerod's thesis is the point that the interactionsbetween individuals in an economy are not only significant butcrucial. While each individual is making decisions based on someexpectation of the future, that future will be the result of theactions of all the individuals. The self-referential template isan example of the kind of system that Complexity seeks toexamine. The conclusions - that such systems are non-linear, arenot determinate, and that the interactions between the parts arecrucial in the way that the system's future emerges - seem tooffer a better description of economies. Ormerod seizesparticularly on the question of interactions between economicagents, making the point that "there is such a thing associety". The economy evolves the way it does preciselybecause people are influenced by other people, not making theirdecision in a vacuum.

Ormerod's statement of the "problem" - the failureof economics to provide useful answers to questions of policy anddecision making - is first rate. His suggestions for solutionsare, sadly, less far-reaching. He suggests that a more pragmaticapproach be taken, and latches on to one of the developmentswhich mathematical chaos theory has provided, the analysis of theeconomy in terms of attractors. Basically a way of presentingdata to emphasise its periodic and cyclical nature, attractorshave been around for some years. However, they are found inpractice to be far from robust. There are a number of novelcomputer-based methods for examining Complex systems, includingneural networks and evolutionary programming, which Ormerod doesnot consider. Perhaps such methods are to come to the fore in thequest for an economics of the 21st century?

There is also another issue which Ormerod does not mention; Ifa prediction could be made, then there would be changes toactions in the future resulting from the prediction, which wouldchange the future. This element of self-sabotage (orself-fulfilling prophesy?) is not at all easy to handle in anypredictive situation. However, Ormerod's book is a good read -anyone who uses data from their economics department to makemajor decisions could read this and save themselves some worry.

Analysis Again

The subject of analysis of complex systems in terms ofattractors is, unfortunately, the main subject considered by HRichard Priesmeyer. His book "Organisations and Chaos"has obviously been inspired by previous work on chaos theory, andas such is a potentially interesting addition to the bookshelf.His subtitle - "Defining the Methods of Non-LinearManagement" - is very bold, and sadly unjustified.

This book is actually hardly about organisations (at least inthe way that organisational theorists and developers would relateto that term). It is about analyzing data. More specifically, itis about analyzing data in terms of attractors and limit cycles.As Macnamara (1994) has pointed out, this book is detailed andcompetent. It provides numerous examples of ways to use the toolof limit cycle plotting to analyze various situations, andsuggests that such functions could usefully be programmed intospreadsheet applications. All of this is legitimate comment. IfPriesmeyer had subtitled his book "An interesting way toexamine non-linear data", he would have been telling thetruth. However, in terms of defining THE methods of non-linearmanagement, this book is way off target. Attractors may well be auseful alternative to linear analysis and may serve to bringaspects of pattern in an organisation to the eyes of itsmanagers. With the latest views of attractors in the stockmarkets as things which can provide useful guidance for no morethan a few hours at a time, Priesmeyer's suggestions of usingfive years of annual data to make decisions seems rather askew.Also, Priesmeyer may be still fighting against a basic truth ofcomplex systems - they are indeterminate, and so their attractors(called "strange" because of their intertwined andirregular qualities) are not amenable to prediction, even iftheir past is known.

Management and Chaos

David Parker and Ralph Stacey's "Chaos, Management andEconomics" tackles this very issue head on. This isdifferent to the books above in two ways. Firstly it is writtenfor an audience already familiar with the basics of managementand organisation, and is very much a business book rather than ascience book. Secondly, it is clearly subtitled "TheImplications of Non-Linear Thinking" and addresses thataspect specifically. One rather confusing aspect is that whilstall the other authors here use "complexity" to describea specific part of the order/chaos spectrum, Parker and Staceyreverse these definitions and talk about the science ofcomplexity as the whole and "chaos" as the interestingpart in the middle where the future emerges in a neitherpredictable nor random way. Once the reader has realised this,there is much of interest here.

Parker and Stacey give a good account of how positive andnegative feedbacks in combination give rise to complex systems,and of how organisations and economies may be seen to act assuch. They set alongside this Chris Argyris's models of singleand double loop learning, with single loop (error correction) asa negative feedback activity, whilst double loop learning isassociated with changing mental models and the norms within whichsingle loop learning occurs. Flexibility is a key requirement ina successful organisation, with the ability to be"self-changing". Parker and Stacey challenge the notionin much of management literature that an "adaptive fit"between organisation and environment is the goal with managersstaying in control and realising long-term intentions. Rather,organisations stumble because they only adapt to thepresent rather than seek to create flexibility, and they do notrealise long term intended outcomes because it is impossible todo so. Having critiqued the "rational" model ofmanagement (and thereby classical strategic planning as well),they set about the "excellence" model (taking intoaccount Brian Quinn's logical incrementalism as well as Peters& Waterman) whereby a vision is set by a leader who persuadesthe rest of the organisation to come along. Progress is made bytrial and error experiments which are fed back to move theorganisation towards the vision. This is again characterised bymanagers being in control.

Parker and Stacey then examine the effects of positivefeedbacks in organisations, building up a rather complicatedmodel of management by self-organisation to take account of this.They describe well, however, the positive effect that creativetension can have in being a driver for change. Their conclusionshere are that policies which do not permit differences betweenpeople to flourish are blockers to adaptation, that organisationswhich are sufficiently flexible to adapt continuously will do soby not being centrally controlled and will head into anunknowable future rather than someone's vision, and thatdestabilising information plays a critical role in promotingchange and must not be filtered out. Destruction has creativepossibilities too!

Presumably it is Parker and Stacey's view that this is apotential future way for organisation - their bold statements donot refer to the fact that businesses have been making money fora long time without (consciously, anyhow) knowing all this. Andif the future is indeed unknowable, how is it that the activityof planning has carried on for so long, and that so manyorganisations have apparently found enough benefit from such aspurious enterprise that they persist in doing it? Whilst Isupport their conclusions fully, there is more that needs to beaddressed in this area, and there is much here to challenge themanagement thinker.

Parker & Stacey conclude with remarks about economics notdissimilar to Paul Ormerod, and draw attention to the"Austrian" school of economics. This species focus onthe ways in which imperfect information and non-equilibrium movesthe economy along an evolving path, with entrepreneurship andmarkets manning the engine-room. Whereas in neo-classicaleconomics there is little scope for making profits, the"Austrians" (a school of thought rather than ageographic tradition) put this aspect at the head of the marketeconomy. Any thoughts that governments can plan economies, orshould be intervening in them, are out of the window. Perhapsthis conclusion is unsurprising given the provenance of thispaper (the Institute for Economic Affairs), but Parker &Stacey are interesting in the way that complexity is brought tosupport this position.

Overall, Parker and Stacey have set out to address certainaspects of complexity, and do so provocatively. There iscertainly scope for examining their conclusions further, and fordeveloping them. As far as the practising manager is concerned,this book is mainly written at a philosophical level, and furtherdevelopments are required. There are, however, a multitude ofother ways in which complexity science could influence businessin the years to come. For that, we turn to Kevin Kelly.

Evolution, adaptation and control

"Out Of Control" is a massive book in several ways.It is 600 pages long, and roams around a huge terrain of ideas,experiments and possibilities relating to complex systems and theways in which interactions between multiple agents (be theymachine, people, plants or whatever) to produce emergent order.Subtitled "The New Biology Of Machines", this book maynot appear at first glance to be relevant to managers andorganisational developers. However, hiding within the apparentfocus on computers, networks and living creatures is the mostsustained effort yet to pull together material from many of thefrontiers of human endeavour in search of adaptability andevolving systems. It starts out by considering a hive of bees asnot just a lot of bees but, via the ways the bees interact, as aunitary system, almost an organism in its own right. This themeof "swarm control", of many relatively simple butdifferent agents interacting to create a bigger and effectivewhole which can evolve without a central control system, ismaintained throughout.

Kelly takes many fascinating detours on his trip though thedevelopments appearing in the late 1990s. He describes a robotwith six legs, each of which has some simple instructions foroperating and knows what the other legs are doing. There is,however, no central "control" system. This robot canclimb over obstacles effectively, and has developed ways of usingits legs together to walk, without them ever being programmedexplicitly into it. Here is an example of emergence at work.

Kelly examines the ways in which networks of interactingelements can lead to high-level emergent structures. He discussesthe co-evolution of "systems" with their environments(and the extremely widescale connectedness which results, givinglarge and unknowable consequences to small changes), and relatesthis in part to the impact of the Internet on ways of doingbusiness. Kelly's reports that there are optimal levels ofconnectedness to a network of computers (or of people) - too fewconnections lead to slow response, and too many lead to gridlock,overload and the freezing out of adaptation. At some interimlevel, the connections facilitate adaptation of the system alongwith its environment. For those dedicated to "improving thelevels of communication in organisations" (and who isn'tthese days?), this is an interesting revelation.

There is a whole area of Complexity of relevance to businesswhich Kelly, alone of these authors, addresses. Where problemscan be described algorithmically, in terms a computer can handle,there exists a range of methods which allow the computer toevolve solutions. These methodologies have only become availablein the last ten years or so, because of the fall in the cost ofcomputing power, and often take their cue from the way that DNAis passed on and modified in the process of reproduction andevolution. It may now prove more effective for a computer tostart with random numbers and evolve a solution to, say, a designproblem or a control program, than to pay highly trained peopleto design the same solution from scratch. The power ofevolutionary programming can be compared to setting out to findone individual in the world, starting at random, and finding themafter talking to only four or five others. The range ofpossibilities from which the final solution is chosen is vast,and the speed at which it is discovered so rapid, that thesemethods are starting to revolutionise software design and otherareas.

Kelly also looks at the possibilities for prediction using newcomputer-based methods. The use of neural networks andcombinations of nets and evolutionary programming seems to offerpossibilities of finding order amongst the noise of change. Thesehave been found to be useful in some cases, such as moneymarkets, particularly over short timescales. So what furtherpossibilities exist to help business people? And how does theincreased use of such mechanisms fit alongside the idea that aComplex system is non-deterministic?

Kelly ends his long and fascinating voyage with a look at someprinciples he has devised for "producing somethings out ofnothings". These include ideas about the importance ofdistributed decision making and bottom up control, seekingincreasing returns (positive feedback and virtuous circles),growing by setting up new small units, each of which works on itsown, and using diversity as a source of innovation andresilience. He stresses the value of maintaining disequilibrium,and harks back to the cybernetics workers of decades past inexplaining how these kinds of systems have self-changing rules asthese rules emerge from the bottom-up interactions.

"Out Of Control" is a book which overflows withpossibilities, new ideas, and old ideas given a refreshing newtwist. It is not written to address business issues, and yetaddresses a wide range of the areas where leaders and managershave an interest. Again, there is a great deal of work to be donein discovering the bridges between these ideas and principles andthe very real and challenging world of management.

Where next?

To summarise - complexity is a fascinating area, and seems tooffer a very useful lens for examining business andorganisations. The books discussed in this article offer a rangeof insights into the areas of inquiry which Complexity offers us.With the exception of David Parker and Ralph Stacey, none of themset out to provide assistance for managers who are concerned withpeople, money and results. We are not yet at the stage wherethese ideas have been considered and tested, and there is adanger in rushing to loose and untenable analogies betweensystems in computers and real warm-bodied organisations. However,there seems to be hope that Complexity could produce some usefuland interesting new ways to examine organisational issues, andsome exciting new approaches to dealing with them. Indeed, thereare already signs of activity on this front (Trisoglio, 1995,Stacey, 1995). Those who seek to take this field forward mightseek to answer these questions:

? What is the relationship between the natural state of flux and indeterminacy of Complex systems, and the everyday experience of managers in "knowing what's going to happen"?

? How can organisations use the phenomena known as Complexity to help them get where they want to go? Can small changes be designed to deliberately produce large effects?

? Is it possible to know where to go in a complex world? What is the role of planning? Which planning tools will help or hinder? How do prediction and expectation affect the situation?

? What does it mean to to lead an organisation? If high adaptability comes as a package with "out of control", are investors, leaders and workers ready for it?

? What is the future role of the "manager"? If planning, directing and controlling resources aren't so useful, what is?

? What are the implications for "change management"? Does it become "stability prevention"?

? What structures and organisational forms might be able to use the Complex world rather than attempt to go against it.

? What parts do communication and language play in Complex systems? How can we use them to advantage?

? What forms and degress of connectedness and communication facilitate adaptation in organisations? Where is the point at which communications becomes a hindrance?

? How can the new availability of computer power be used to help in the task of making progress in a complex world? What future is there for prediction mechanisms?

And finally, in a world which is emerging, uncertain andindeterminate, is this the time for Long Range Planning to adapt its name?


Macnamara T, Long Range Planning 27,152 - 154 (October 1994)

Stacey RD, The Science of Complexity: An alternativeperpective for strategic change processes, Strategic ManagementJournal, 16, 477 - 495 (1995)

Trisoglio A, "ManagingComplexity", LSE Strategy and Complexity Seminar WorkingPaper 1, (1995)

"Complexity Science and Management - What's in it for business?", Long Range Planning 29, pp 721 - 727(1996)