The new dynamics of strategy: Sense-making in a complex ...alumni.media.mit.edu/~brooks/storybiz/kurtz.pdf · The new dynamics of strategy: Sense-making in a complex and complicated

The new dynamics ofstrategy: Sense-makingin a complex andcomplicated world

by C. F. KurtzD. J. Snowden

In this paper, we challenge the universality ofthree basic assumptions prevalent inorganizational decision support and strategy:assumptions of order, of rational choice, and ofintent. We describe the Cynefin framework, asense-making device we have developed tohelp people make sense of the complexitiesmade visible by the relaxation of theseassumptions. The Cynefin framework isderived from several years of action researchinto the use of narrative and complexitytheory in organizational knowledge exchange,decision-making, strategy, and policy-making.The framework is explained, its conceptualunderpinnings are outlined, and its use ingroup sense-making and discourse isdescribed. Finally, the consequences ofrelaxing the three basic assumptions, usingthe Cynefin framework as a mechanism, areconsidered.

Over the past several years, our group has been con-ducting a program of disruptive action research us-ing the methods of narrative and complexity theoryto address critical business issues.1 Action researchhas been defined as grounding theory in contextualexploration, emphasizing participation, and embrac-ing change.

We started work in the areas of knowledge manage-ment, cultural change and community dynamics, thenexpanded into product development, market cre-ation and branding, and in recent years have beenworking increasingly in the area of national and or-ganizational strategy. Some of this work has been

directly funded by the U.S. government throughDARPA (Defense Advanced Research ProjectAgency) as well as by other government agencies (inparticular in Singapore) which are interested in newapproaches to supporting policy-making. The cen-tral element of our approach is the Cynefin frame-work for sense-making. In this paper we describe theframework and its conceptual basis, and we detailsome of its uses for sense-making to support decision-making in varied dynamical contexts.

Conceptual approach. We begin by questioning theuniversality of three basic assumptions that pervadethe practice and to a lesser degree the theory of de-cision-making and policy formulation in organiza-tions. These are:

The assumption of order: that there are underlyingrelationships between cause and effect in human in-teractions and markets, which are capable of discov-ery and empirical verification. In consequence, it ispossible to produce prescriptive and predictive mod-els and design interventions that allow us to achievegoals. This implies that an understanding of thecausal links in past behavior allows us to define “bestpractice” for future behavior. It also implies thatthere must be a right or ideal way of doing things.

The assumption of rational choice: that faced with achoice between one or more alternatives, human ac-

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tors will make a “rational” decision based only onminimizing pain or maximizing pleasure; and, in con-sequence, their individual and collective behavior canbe managed by manipulation of pain or pleasure out-comes and through education to make those con-sequences evident.

The assumption of intentional capability: that the ac-quisition of capability indicates an intention to usethat capability, and that actions from competitors,populations, nation states, communities, or whatevercollective identity is under consideration are the re-sult of intentional behavior. In effect, we assume thatevery “blink” we see is a “wink,” and act accordingly.We accept that we do things by accident, but assumethat others do things deliberately.

This paper contends that although these assumptionsare true within some contexts, they are not univer-sally true. We also believe that in decision-makingat both policy-making and operational levels, we areincreasingly coming to deal with situations wherethese assumptions are not true, but the tools andtechniques which are commonly available assumethat they are.

Order and chaos in antiquity. The human distinc-tion between order and chaos goes back to an abun-dant presence in mythology, in which order arisesout of (and thus requires) and then vanquishes (andthus destroys) the mysterious forces of chaos. Forexample, in the Enuma Elish,2 the Babylonian epicof creation, the world began under the reign ofTiamat, the mother of all things. In Tiamat’s world,“none bore a name, and no destinies were ordained.”After several generations, Tiamat’s god-children ap-pointed a champion to seize control. Marduk notonly defeated his ancestor, but “split her up like aflat fish into two halves” that became heaven andearth. He then proceeded to order the universe infiner and finer detail:

He [Marduk] made the stations for the great gods;The stars, their images, as the stars of the Zodiac,

he fixed.He ordained the year and into sections he divided

it;For the twelve months he fixed three stars. . . .He founded the station of Nibir [the planet Ju-

piter] to determine their bounds;That none might err or go astray . . .

Note the words “fixed,” “ordained,” “divided,” “de-termined,” “err,” and “astray.” Control (in the first

four terms) and an absolute knowledge of right andwrong (in the last two) are the salient points of Mar-duk’s new world. Of course Tiamat was never en-tirely vanquished; forces of chaos appear in all tra-ditions in the form of tricksters and malcontents suchas Bacchus, Loki, Coyote, the Monkey King, Anansi,and Hermes. The forces of order and chaos dancedwith each other throughout ancient times.

Science, order, and epiphenomena. Aristotle de-fined four types of cause: the material (what you aremade of, your muscles and organs), the efficient (howyou came to be, the fact that your parents gave birthto you), the formal (your type, your species), and thefinal (your function, your life itself, your place in theuniverse). He believed that to understand an eventor entity, one had to consider all of these factors inthe particular, the mysterious as well as the ordered.As others have pointed out,3 the focus of Westernthinking post Kant on efficient cause only is to thedetriment of knowledge.

Since the birth of enlightenment science, the distinc-tion between order and chaos has held a prominencethat has profoundly influenced conceptual and prac-tical thinking. Kant separated things that we canknow empirically from things that are the provinceof God, and thereby helped to section off all but ef-ficient causes to epiphenomena that could be safelyignored. This concept of ordered science triggereda massive growth in human knowledge and extendedover many disciplines. For example, sociology grewout of philosophy partly in an attempt to create a“science of society” that could duplicate the advancesbeing made in physics and biology through system-atic observation and causal explanation. It was ar-gued, mainly by Comte, that it was theoretically pos-sible to discover laws similar to those of physics whichcould explain the behavior of people in societies. Thegrowth of technology and the dominance of engi-neering-based approaches arising from the need forautomation and scalability reenforced the desire forand the assumption of order. In popular literature,the belief that all things can be known (in a New-tonian sense) persisted well into this past century.Asimov’s classic science fiction Foundation Trilogy4

builds on the character of Hari Seldon, the founderof psychohistory, whose mathematics permits theprediction of human behavior and social change cen-turies into the future.

The development of management science, from stop-watch-carrying Taylorists5 to business process reengi-neering, was rooted in the belief that systems were

IBM SYSTEMS JOURNAL, VOL 42, NO 3, 2003 KURTZ AND SNOWDEN 463

ordered; it was just a matter of time and resourcesbefore the relationships between cause and effectcould be discovered.6 The case study approach ofmany M.B.A. programs and the desire for preciserecommendations from policy teams and externalconsultants perpetuate the underlying assumptionof universal order. Good leadership is linked to cer-tain competences that (it is claimed) can be mappedand identified, and then replicated. The desire fororder can even lead people to accept completely ab-horrent working conditions and political structuressimply to avoid “chaos” (a tendency exploited by dic-tators from Pisistratus to Hitler and beyond). All ofthese approaches and perceptions do not accept thatthere are situations in which the lack of order is nota matter of poor investigation, inadequate resources,or lack of understanding, but is a priori the case—and not necessarily a bad thing, either.

Complexity science. A new awareness of the ancientcounterpart to order began over a century ago withPoincare and several others, and has surged in re-cent decades.7–10 In fact there is a fascinating kindof order in which no director or designer is in con-trol but which emerges through the interaction ofmany entities. Emergent order has been found inmany natural phenomena: bird-flocking behavior canbe simulated on a computer through three simplerules 11; termites produce elegant nests through theoperation of simple behaviors triggered by chemi-cal traces12; each snowflake is a unique pattern aris-ing from the interactions of water particles duringfreezing.13 The patterns that form are not controlledby a directing intelligence; they are self-organizing.14

The new science of complexity spawned by thesefindings is interdisciplinary, touching fields frommathematics to evolution to economics to meteo-rology to telecommunications.15 In the domain ofemergent order, the goal “to predict (and therebycontrol) the behavior of systems not yet studied (butsimilar to those that have been studied) under con-ditions not yet extant and in time periods not yet ex-perienced” 16 is difficult if not impossible toachieve—but other goals are achievable.

Awareness of emergent order has as yet had com-paratively little influence on mainstream theory andpractice in management and strategy, though someauthors have been exploring these topics with somesuccess.17–21 We are sorry to say that in our opiniontoo many of the books written for a popular busi-ness audience on the subject have been marred bymisunderstandings, misapplications, and most of allmisplaced zeal (some even falling into pseudo-sci-

entific and pseudo-religious thinking). Our group hasbeen using ideas based on complexity science in ouraction research work for the past several years, andthe work we will describe here benefits from that in-fluence.

Contextual complexity. A considerable amount ofresearch and some early practice is taking place us-ing complex system principles, mainly using comput-ing power to simulate natural phenomena throughagent-based models.12 Well-known examples includerouting optimization of airfreight and telecommu-nication signals based on large volume data mod-eling in which each agent is programmed to operateon simple rules, the result of which is the emergenceof complex patterns of behavior.22 We believe thatsuch tools are valuable in certain contexts, but areof more limited applicability when it comes to man-aging people and knowledge. There are at least threeimportant contextual differences between human or-ganizations and those of ant colonies that make itmore difficult to simulate them using computer mod-els. In a sense, because we have not seen these is-sues addressed as fully as we would like, we put themforth as challenges to agent-based simulation of hu-man behavior.

Humans are not limited to one identity. In a humancomplex system, an agent is anything that has iden-tity, and we constantly flex our identities both indi-vidually and collectively. Individually, we can be aparent, sibling, spouse, or child and will behave dif-ferently depending on the context. Collectively, wemight, for example, be part of a dissenting commu-nity, but in the face of a common threat, we mightassume the identity of the wider group. Accordingly,it is not always possible to know which unit of anal-ysis we are working with.

There are generally three solutions to this problemof the unit of analysis in the social simulation liter-ature.23 First, individuals are modeled and group be-havior is explained by the concept of “norms.”24 Butidentity goes deeper than norms—it determines notonly reactions but perceptions and patternings ofexperience. A second solution is to model groups asagents, but much internal diversity and patterningis suppressed in this approach. It also makes assump-tions about intent and predictability that are diffi-cult to sustain. The third solution to the unit-of-anal-ysis problem is to consider the rule or idea or “meme”as the unit of analysis, 25 but again we find that in-sufficient to capture the dynamics of multiple iden-tities. We would like (but do not expect) to see sim-

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ulations of human behavior able to encompassmultiple dynamic individual and collective identitiesacting simultaneously and representing all aspectsof perception, decision-making, and action.

Humans are not limited to acting in accordance withpredetermined rules. We are able to impose struc-ture on our interactions (or disrupt it) as a result ofcollective agreement or individual acts of free will.

We are capable of shifting a system from complex-ity to order and maintaining it there in such a waythat it becomes predictable. As a result, questionsof intentionality play a large role in human patternsof complexity.3 It is difficult to simulate true free willand complex intentionality (for example, retrospec-tive elaboration, duplicity, groupthink, rumor, self-deception, manipulation, surprise, confusion, inter-nal conflict, stress, changes in the meanings ofpreviously unambiguous messages, the deliberatecreation of ambiguity, inadvertent disclosure, cha-risma, cults, and pathologies) within a rule-basedsimulation. Social simulations have addressed issuessuch as cooperation, reputation, gossip, lying, andtrust,26 but always within an artificial frameworkwhich allows only limited numbers of options andconsiders limited numbers of phenomena operatingat once. It is interesting that searching the Internetfor “simulation” and most of the terms listed abovebrings up instances of simulations with which a userinteracts to explore patterns.27 This may representa gap between agent-based simulation and humanbehavior similar to that found by the “strong arti-ficial intelligence (AI)” school of the 1970’s whosegoal was to reproduce human intelligence.28 We donot mean to say that there is no value to simulationof human behavior, but we do think we should notexpect it to succeed any time soon in predicting whatpeople will do in any particular circumstance.

Eventually the concept of “intelligent augmenta-tion”29–30 grew in popularity and could be said tobridge the gap between strong AI and reality. It ispossible that a middle ground between the belief that

all human behavior can be simulated and the beliefthat the very effort is questionable will be found inthe use of simulation not to explain or imitate butto support human decision-making.

Humans are not limited to acting on local patterns.People have a high capacity for awareness of large-scale patterns because of their ability to communi-cate abstract concepts through language, and, morerecently, because of the social and technological in-frastructure that enables them to respond immedi-ately to events half a world away. This means thatto simulate human interaction, all scales of aware-ness must be considered simultaneously rather thanchoosing one circle of influence for each agent. Thereis also the matter of simulating the interaction (con-flict, reinforcement) between local and globalawareness. Many of the emergent patterns we seein nature depend critically on the limited (that is,local) ability of activators to diffuse through a vis-cous medium.13 We have not yet seen addressed howthese issues cause complex patterns in human so-cieties to differ from complex patterns in systems oflocally aware agents.

We call our practice of keeping the human contextforemost in our considerations phenomenological ormore commonly “contextual complexity.” It meansmainly that when we use agent-based simulation (andwe do, in certain circumstances), we use it as a toolfor the exploration of possibility and generation ofideas, not as a tool for recommending courses of ac-tion.

Order and un-order. To avoid much repetition of thelonger terms “directed order” and “emergent order,”we call emergent order “un-order.” Un-order is notthe lack of order, but a different kind of order, onenot often considered but just as legitimate in its ownway. Here we deliberately use the prefix “un-” notin its standard sense as “opposite of” but in the lesscommon sense of conveying a paradox, connotingtwo things that are different but in another sense thesame. Bram Stoker used this meaning to great ef-fect in 1897 with the word “undead,” which meansneither dead nor alive but something similar to bothand different from both. According to R. D. Cure-ton, e. e. cummings also used the prefix this way inhis poetry. Says Cureton,31 “In normal usage, beingand existing are stative concepts. They are not ac-tions which a person must consciously perform, en-gage in, create. Words such as unbe and unexist, how-ever, force the reader to see the dynamic nature ofhuman existence. . . .” Thus by our use of the term

We are capable of shiftinga system from complexity

to order and maintaining it therein such a way that

it becomes predictable.


“un-order,” we challenge the assumption that anyorder not directed or designed is invalid or unim-portant.

Keep the baby, lose the bathwater. Let us sound aquick warning about running into the trap of believ-ing that everything is complex. Some recent popu-lar books on complexity in business and managementhave been full of breathy enthusiasm for the “edgeof chaos” and would have businesses maintain them-selves as far from equilibrium as possible, regard-less of context or purpose. We think this is throwingout the baby with the bathwater. We cannot simplygo from saying “things are ordered” to saying “thingsare un-ordered” and leave it at that; things are bothordered and un-ordered at once, because in realityorder and un-order intertwine and interact. Kostof32

puts it well in his description of cities: “. . . the twoprimary versions of urban arrangement, the plannedand the ‘organic,’ often exist side by side. . . . Mosthistoric towns, and virtually all those of metropol-itan size, are puzzles of premeditated and sponta-neous segments, variously interlocked or juxta-posed. . . .” In other words, it is useful to artificiallyseparate order and un-order so that we can under-stand the different dynamics involved, but we shouldnot expect to find one without the other in real life.In many organizations, for example, formal com-mand structures and informal trust networks sup-port (while simultaneously competing with) eachother.33–34 The joke that “the only thing worse thanan inefficient bureaucracy is an efficient bureaucracy”has some ground in reality.

Methods for un-ordered space

Ordered-systems thinking assumes that through thestudy of physical conditions, we can derive or dis-cover general rules or hypotheses that can be em-pirically verified and that create a body of reliableknowledge, which can then be developed and ex-panded. As we have mentioned, this assumption doesnot hold in the domain of un-order.

In practice, all decision makers know this: howevermuch they might like things to be ordered, they knowthat there are also circumstances in which “culturalfactors,” “inspired leadership,” “gut feel,” and othercomplex factors are dominant. All of these are pat-terns, which arise through the interaction of variousentities through space and time. In the space of un-order the seeds of such patterns can be perceived,and new ways of thinking can emerge. In fact, learn-ing to recognize and appreciate the domain of un-

order is liberating, because we can stop applyingmethods designed for order and instead focus on le-gitimate methods that work well in un-ordered sit-uations. Tom Stewart35 references the case of a groupof marines taken to the New York Mercantile Ex-change in 1995 to be taught and to play with sim-ulators of the trading environment. Naturally thetraders won each time. But when the traders visitedthe Marine Corp’s base in Quantico and playedwar games against the marines, they won yet again.What they realized is that the traders were skilledat spotting patterns and intervening to structurethose patterns in their favor. The Marines, on theother hand, like most business school graduates, hadbeen trained to collect and analyze data and thenmake rational decisions. In a dynamic and constantlychanging environment, it is possible to pattern un-order but not to assume order.

In another case, a group of West Point graduateswere asked to manage the playtime of a kindergar-ten as a final year assignment. The cruel thing is thatthey were given time to prepare. They planned; theyrationally identified objectives; they determinedbackup and response plans. They then tried to “or-der” children’s play based on rational design prin-ciples, and, in consequence, achieved chaos. Theythen observed what teachers do. Experienced teach-ers allow a degree of freedom at the start of the ses-sion, then intervene to stabilize desirable patternsand destabilize undesirable ones; and, when they arevery clever, they seed the space so that the patternsthey want are more likely to emerge.

In the ordered domain we focus on efficiency becausethe nature of systems is such that they are amenableto reductionist approaches to problem solving; thewhole is the sum of the parts, and we achieve op-timization of the system by optimization of the parts.In the domain of un-order, the whole is never thesum of the parts; every intervention is also a diag-nostic, and every diagnostic an intervention; any actchanges the nature of the system. As a result, we haveto allow a degree of sub-optimal behavior of eachof the components if the whole is to be optimized.

Pattern entrainment

Humans use patterns to order the world and makesense of things in complex situations. Give a childa pile of blocks, and he or she will build patterns outof them. Give an adult a daily commute, and he orshe will build patterns within it. Patterns are some-


thing we actively, not passively, create, as Mary Dou-glas36 so well pointed out:

. . . whatever we perceive is organized into patternsfor which we the perceivers are largely responsi-ble. . . . As perceivers we select from all the stim-uli falling on our senses only those which interestus, and our interests are governed by a pattern-making tendency, sometimes called a schema. Ina chaos of shifting impressions, each of us con-structs a stable world in which objects have rec-ognizable shapes, are located in depth and havepermanence. . . . As time goes on and experiencebuilds up, we make greater investment in our sys-tems of labels. So a conservative bias is built in.It gives us confidence.

Visually, we hold in sharp focus at any one instanta mere tenth of a percent of our visual range, so eventhe process of seeing is one of putting together manydisparate observations.37 We fill in the gaps to cre-ate an experience-based pattern on which we act.This aspect of human decision-making is a greatsource of power, but it also brings limitation.

A television advertisement for a liberal broadsheetnewspaper in the United Kingdom illustrates thiswell. The advertisement is set in a terraced inner citystreet. It is dusk; litter blows down the street; over-all, a threatening environment.

Scene One: The camera points down the street andpicks up a skinhead who comes around the cor-ner. A police car stops beside the skinhead, whoimmediately runs towards the camera. Pattern en-trainment of decision-making: what do we as-sume? The skinhead must be running from the po-lice.

Scene Two: The camera now changes its perspec-tive; it is now behind the skinhead, and we see thathe is running towards a well dressed man who isclutching a briefcase—which must be full ofmoney, as the man conforms to the stereotype ofa rent collector. We can also see that the man isterrified in the face of the rapidly approachingskinhead. Pattern entrainment of decision mak-ing: what do we assume? The man is going to bemugged.

Scene Three: The camera changes perspective forthe final time; we are now looking down on thestreet from above, and we see the skinhead grab

the man and pull him into the portico of a build-ing just before a crate of building material wouldhave fallen on his head and killed him.

The unspoken message of a brilliant advertisementis, “See things from a different perspective; read thenewspaper.”

Most of the time if you are standing in a run-downinner city area at dusk carrying a briefcase full ofmoney, and a skinhead suddenly runs towards you,it is not a good idea to stand there and say “Ah, Imay be about to be rescued from a crate of fallingbuilding material”; you should run for your life. Theissue in decision-making is to know when to run andwhen to stand still. A choice must be made betweenallowing the entrained patterns of past experienceto facilitate fast and effective pattern application andgaining a new perspective because the old patternsmay no longer apply. We will address these differ-ences in the following section.

The Cynefin framework

The name Cynefin is a Welsh word whose literaltranslation into English as habitat or place fails todo it justice. It is more properly understood as theplace of our multiple affiliations, the sense that weall, individually and collectively, have many roots,cultural, religious, geographic, tribal, and so forth.We can never be fully aware of the nature of thoseaffiliations, but they profoundly influence what weare. The name seeks to remind us that all humaninteractions are strongly influenced and frequentlydetermined by the patterns of our multiple experi-ences, both through the direct influence of personalexperience and through collective experience ex-pressed as stories.

The Cynefin framework originated in the practiceof knowledge management as a means of distinguish-ing between formal and informal communities, andas a means of talking about the interaction of bothwith structured processes and uncertain conditions.It has now outgrown its application in knowledgemanagement, having been in use by our group forseveral years in consultancy and action research inknowledge management, strategy, management,training, cultural change, policy-making, product de-velopment, market creation, and branding. We arenow beginning to apply it to the areas of leadership,customer relationship management, and supply chainmanagement, with other topics to come. It has alsobeen used by third parties.38


We consider Cynefin a sense-making framework,which means that its value is not so much in logicalarguments or empirical verifications as in its effecton the sense-making and decision-making capabil-ities of those who use it. We have found that it givesdecision makers powerful new constructs that theycan use to make sense of a wide range of unspec-ified problems. It also helps people to break out ofold ways of thinking and to consider intractable prob-lems in new ways. The framework is particularly use-ful in collective sense-making, in that it is designedto allow shared understandings to emerge throughthe multiple discourses of the decision-making group.

We make a strong distinction here between sense-making frameworks and categorization frameworks.In a categorization framework, four quadrants areoften presented in a two-by-two matrix (for exam-ples, pick up any management textbook or analystreport). Typically, it is clear (though often unstated)that the most desirable situation is to be found inthe upper right-hand quadrant, so the real value ofsuch a framework is to figure out how to get to theupper right. In contrast, none of the domains we willdescribe here is more desirable than any other; thereare no implied value axes. Instead, the frameworkis used primarily to consider the dynamics of situ-ations, decisions, perspectives, conflicts, and changesin order to come to a consensus for decision-mak-ing under uncertainty.

As can be seen in Figure 1, the Cynefin frameworkhas five domains, four of which are named, and afifth central area, which is the domain of disorder.The right-hand domains are those of order, and theleft-hand domains those of un-order.

Ordered domain: Known causes and effects. Here,cause and effect relationships are generally linear,empirical in nature, and not open to dispute. Re-peatability allows for predictive models to be cre-ated, and the objectivity is such that any reasonableperson would accept the constraints of best practice.This is the domain of process reengineering, in whichknowledge is captured and embedded in structuredprocesses to ensure consistency. The focus is on ef-ficiency. Single-point forecasting, field manuals, andoperational procedures are legitimate and effectivepractices in this domain. Our decision model hereis to sense incoming data, categorize that data, andthen respond in accordance with predeterminedpractice. Structured techniques are not only desir-able but mandatory in this space.

Ordered domain: Knowable causes and effects.While stable cause and effect relationships exist inthis domain, they may not be fully known, or theymay be known only by a limited group of people. Ingeneral, relationships are separated over time andspace in chains that are difficult to fully understand.Everything in this domain is capable of movementto the known domain. The only issue is whether wecan afford the time and resources to move from theknowable to the known; in general, we cannot andinstead rely on expert opinion, which in turn createsa key dependency on trust between expert advisorand decision maker. This is the domain of systemsthinking, the learning organization, and the adap-tive enterprise, all of which are too often confusedwith complexity theory.18 In the knowable domain,experiment, expert opinion, fact-finding, and scenar-io-planning are appropriate. This is the domain ofmethodology, which seeks to identify cause-effectrelationships through the study of properties whichappear to be associated with qualities. For systemsin which the patterns are relatively stable, this is bothlegitimate and desirable.

Our decision model here is to sense incoming data,analyze that data, and then respond in accordancewith expert advice or interpretation of that analysis.Structured techniques are desirable, but assumptionsmust be open to examination and challenge. This isthe domain in which entrained patterns are at theirmost dangerous, as a simple error in an assumption

Figure 1 Cynefin domains

COMPLEX

Cause and effect are onlycoherent in retrospect and do not repeat

Pattern management

Perspective filters

Complex adaptive systems

Probe-Sense-Respond

CHAOS

No cause and effect relationships perceivable

Stability-focused intervention

Enactment tools

Crisis management

Act-Sense-Respond

KNOWN

Cause and effect relations repeatable, perceivable and predictable

Legitimate best practice

Standard operating procedures

Process reengineering

Sense-Categorize-Respond

KNOWABLE

Cause and effect separated over time and space

Analytical/Reductionist

Scenario planning

Systems thinking

Sense-Analyze-Respond


can lead to a false conclusion that is difficult to iso-late and may not be seen.

It is important to note here that by known and know-able we do not refer to the knowledge of individ-uals. Rather, we refer to things that are known tosociety or the organization, whichever collective iden-tity is of interest at the time. If I look up my orga-nization’s policy on travel to Iceland, I may not knowwhat I will find there, or even how I will find it, butI know I can find something, because I know it isknown to the organization. If I want to know howfish sleep, I may not know how or where to find out,but I have a hunch that somebody knows.

Un-ordered domain: Complex relationships. This isthe domain of complexity theory, which studies howpatterns emerge through the interaction of manyagents. There are cause and effect relationships be-tween the agents, but both the number of agents andthe number of relationships defy categorization oranalytic techniques. Emergent patterns can be per-ceived but not predicted; we call this phenomenonretrospective coherence. In this space, structuredmethods that seize upon such retrospectively coher-ent patterns and codify them into procedures willconfront only new and different patterns for whichthey are ill prepared. Once a pattern has stabilized,its path appears logical, but it is only one of manythat could have stabilized, each of which also wouldhave appeared logical in retrospect. Patterns may in-deed repeat for a time in this space, but we cannotbe sure that they will continue to repeat, because theunderlying sources of the patterns are not open toinspection (and observation of the system may itselfdisrupt the patterns). Thus, relying on expert opin-ions based on historically stable patterns of mean-ing will insufficiently prepare us to recognize and actupon unexpected patterns.

The decision model in this space is to create probesto make the patterns or potential patterns more vis-ible before we take any action. We can then sensethose patterns and respond by stabilizing those pat-terns that we find desirable, by destabilizing thosewe do not want, and by seeding the space so that pat-terns we want are more likely to emerge. Under-standing this space requires us to gain multiple per-spectives on the nature of the system. This is the timeto “stand still” (but pay attention) and gain new per-spective on the situation rather than “run for yourlife,” relying on the entrained patterns of past expe-rience to determine our response. The methods,tools, and techniques of the known and knowable

domains do not work here. Narrative techniques areparticularly powerful in this space. We have de-scribed elsewhere a range of methods designed tostimulate emergent patterns in complex knowledgeinteractions by increasing the number of perspec-tives available to a decision maker.39

Un-ordered domain: Chaos. In the first three do-mains we have described, there are visible relation-ships between cause and effect. In the chaotic do-main there are no such perceivable relations, andthe system is turbulent; we do not have the responsetime to investigate change.8 Applying best practiceis probably what precipitated chaos in the first place;there is nothing to analyze; and waiting for patternsto emerge is a waste of time. The chaotic domain isin a very real sense uncanny, in that there is a po-tential for order but few can see it—or if they can,they rarely do unless they have the courage to act.In known space it pays to be canny, that is, to knowhow to work the system in all its intricacies (cannymeaning not only shrewd but safe). But in chaoticspace, a canny ability gets you nowhere (there is nosystem to be worked). You need a different type ofability, one that is uncannily mysterious, sometimeseven to its owner. Canny people tend to succeed intheir own lifetimes; uncanny people tend to be rec-ognized and appreciated only centuries later, becauseduring their time their actions appeared to be eitherinsane or pointless. Each of these styles has a uniqueability to succeed in a particular space, and each isnecessary.

The decision model in this space is to act, quicklyand decisively, to reduce the turbulence; and thento sense immediately the reaction to that interven-tion so that we can respond accordingly. The trajec-tory of our intervention will differ according to thenature of the space. We may use an authoritarianintervention to control the space and make it know-able or known; or we may need to focus on multipleinterventions to create new patterns and therebymove the situation into the complex space. Chaosis also a space we can enter into consciously, to openup new possibilities and to create the conditions forinnovation.

The domain of disorder. The central domain of dis-order is critical to understanding conflict among de-cision makers looking at the same situation from dif-ferent points of view. Often in a group using theCynefin framework, people agree on what the ex-tremes of the four domains mean in the context theyare considering, but disagree on more subtle differ-


ences near the center of the space. As a result, in-dividuals compete to interpret the central space onthe basis of their preference for action. Those mostcomfortable with stable order seek to create or en-force rules; experts seek to conduct research and ac-cumulate data; politicians seek to increase the num-ber and range of their contacts; and finally, thedictators, eager to take advantage of a chaotic sit-uation, seek absolute control. The stronger the im-portance of the issue, the more people seem to pullit towards the domain where they feel most empow-ered by their individual capabilities and perspectives.We have found that the reduction in size of the do-main of disorder as a consensual act of collabora-tion among decision makers is a significant steptoward the achievement of consensus as to the na-ture of the situation and the most appropriate re-sponse.

The apple-orange problem

People are often confused by the apple-orange na-ture of the four Cynefin domains: they say, “Whynot known, knowable, somewhat knowable and un-knowable?” or, “Why not simple, complicated, com-plex and chaotic?” The distinction is intentional. TheCynefin framework is a phenomenological frame-work, meaning that what we care most about is howpeople perceive and make sense of situations in or-der to make decisions; perception and sense-mak-

ing are fundamentally different in order versus un-order. The framework actually has two largedomains, each with two smaller domains inside. Inthe right-side domain of order, the most importantboundary for sense-making is that between what wecan use immediately (what is known) and what weneed to spend time and energy finding out about(what is knowable). In the left-side domain of un-order, distinctions of knowability are less importantthan distinctions of interaction; that is, distinctionsbetween what we can pattern (what is complex) andwhat we need to stabilize in order for patterns toemerge (what is chaotic). Thus we often draw theframework with the vertical boundaries strong andthe horizontal boundaries weak, denoting their rel-ative importance in sense-making.

The Cynefin framework is based on three ontolog-ical states (namely, order, complexity and chaos) anda variety of epistemological options in all three ofthose states. We are currently engaged in further con-ceptual and experimental work to more strongly de-velop the separation of ontological from epistemo-logical aspects of the framework in order to root theframework in a variety of scientific disciplines whilemaintaining the essential interweaving of ontologyand epistemology, which appears to be an essentialaspect of human sense-making in practice.

Connection strengths of Cynefin domains

Another way to look at the Cynefin framework is inthe types of component connections that are mostprevalent in each domain (Figure 2). On the side oforder, connections between a central director andits constituents are strong, often in the form of struc-tures that restrict behavior in some way—for exam-ple, procedures, forms, blueprints, expectations, orpheromones. On the side of un-order, central con-nections are weak, and attempts at control throughstructure often fail from lack of grasp or visibility.In the complex and knowable domains, connectionsamong constituent components are strong, and sta-ble group patterns can emerge and resist changethrough repeated interaction, as with chemical mes-sages, acquaintanceship, mutual goals and experi-ences. The known and chaotic domains share thecharacteristic that connections among constituentcomponents are weak, and emergent patterns do notform on their own.

In any of these domains, a reasonable strategy cap-italizes on the stability afforded by strong connec-tions without allowing them to harden so much that

Figure 2 Connection strength of Cynefin domains

COMPLEX

WEAK CENTRAL,STRONG DISTRIBUTED

CHAOS

WEAK CENTRAL,WEAKDISTRIBUTED

KNOWABLE

STRONG CENTRAL,STRONG DISTRIBUTED

KNOWN

STRONG CENTRAL,WEAKDISTRIBUTED


they destroy flexibility and also capitalizes on thefreedom and renewal afforded by weak connectionswithout allowing them to permanently remove use-ful patterns.

How the Cynefin framework is used

In our engagements with clients, we use the Cynefinframework at several different levels, depending onthe context and purpose of the project. Several com-plementary exercises and programs help people tointernalize and make use of the framework. Somegroups consider only the five domains and what sortsof situations or problems can be found there; someconsider distinctions between extreme and equivo-cal conditions within domains; some consider mul-tiple perspectives and how they can be resolved orused to advantage; some talk about boundary tran-sitions, boundary sensing, and boundary manage-ment; some talk about dynamics ranging over thewhole space of the framework. For example, groupsmight use the Cynefin framework to gain new insightson a contentious issue, plan interventions to movea situation from one domain to another, considerhow they should approach or manage different for-mal and informal communities, or differentiate theirstrategies for knowledge retention based on multi-ple contexts of knowledge exchange.

Contextualization. This is a critical exercise that en-ters into nearly every Cynefin project. Contextual-ization is also a good example of how the Cynefinframework concentrates on collective sense-makingas a consequence of discourse. We will describe atypical contextualization session here. The sessionbegins with the collection of many items throughstructured brainstorming. The items might be com-munities, products, actions, motivations, forces,events, points of view, beliefs, traditions, rituals,books, metaphors, anecdotes, myths, and so on: theyare any items that are important to the sense-mak-ing process. The items are related to one theme orissue of concern, which should be broad but not in-finitely so. Whatever sorts of items are chosen (andmultiple types are permissible), they should be di-verse and concrete in nature: diverse to allow mul-tiple perspectives to emerge, and concrete to moveaway from existing entrained abstract beliefs. We as-sure diversity by giving different groups of peopledifferent directions, by giving directions that are de-liberately ambiguous and so can be taken in diverseways, and by changing group compositions frequentlyso that people do not fall into entrained thinking.To keep items concrete, we rely heavily on narrative

methods. These provide a rich context that allowspatterns of experience rather than opinion or beliefto emerge.

We use an array of different methods to help peopleprepare a contextually meaningful field of items forsense-making, including:

Narrative database. We might prepare in advance anarrative database of relevant stories surroundingthe issue, drawn from oral histories, collected an-ecdotes, published reports, historical documents, andthe like.40 Workshop participants might be asked toreview the material in advance and answer somesense-making questions about it. In the first part ofthe workshop, we may ask people to talk about theirthoughts on the material and the narratives whichthey found most compelling. From these discussionsa list of such items as situations, actors, events, andforces might be generated.

Convergence methods. Rather than pulling items di-rectly from anecdotes discussed, we might go throughone of several convergence methods in order to in-tegrate much disparate material and achieve a stron-ger set of sense-making items. For example, we mightask people to construct composite fables from an-ecdotes by using one of a variety of fable templates,working from either the narrative database or theirown experiences as source material. 41 This exerciseis especially useful when we need to bring peopleinto the realm of fiction so that they can more freelyexpress their true opinions on sensitive subjects. Itis also a useful integrator of diverse sources. In aroom of 50 people constructing fables in smallgroups, several hundred anecdotes may be consid-ered as material for creation of each group’s fable.Items are then drawn from aspects of the integratedfables (characters, events, situations) for sense-mak-ing.

Alternative history. Another useful method (with orwithout preparatory material) is the use of alterna-tive histories. In this method, we ask people to de-scribe the history of an organization, society, or event,always working backwards from the present (to anystarting time they think is appropriate). We ask themto determine turning points (moments when smallevents caused large changes), write them simply onhexagonal sticky notes, and array them on a wall. (Weprefer hexagonal notes because people tend to clus-ter them in beehive shapes, while people tend to cat-egorize square notes.) When the factual history iscomplete, we then ask people to choose two extreme


states, one positive and one negative; each of thesemust be utterly inconceivable. They then work back-wards (always backwards, to avoid entrained “whatusually comes next” thinking) with fictional timelinesto reach points on the factual timeline. These con-nection points are not determined in advance, butemerge from the growing reverse fiction. The turn-ing points may then be considered and described,listing, for example, actors, communities, and fac-tors in play during those moments. These becomethe sense-making items.

Next, as shown in Figure 3A, the group comes to-gether with their assembled sense-making items, per-haps derived from multiple processes, and discussesthe extremes (not the domains) of the Cynefin space.They consider the corner where everyone knows theright answer, the corner where an expert could beexpected to know the right answer, the corner wherethe situation only becomes clear retrospectively, andthe corner in which there is no right answer. If pos-sible, items are selected from the set that exemplifythat dynamical extreme in the context of the issueor events being considered. This is an important step,because it begins to build the framework. We say“build the framework” because the Cynefin frame-work is created anew each time it is used, with dis-tinctions meaningful to the current context. To someextent, it does not even exist in the way we describeit here, devoid of context, but is always used to en-

able sense-making in a particular setting. (It can alsobe used to negotiate meaning between contexts, butthat use is beyond the scope of this paper.)

After the extreme situations are considered, all ofthe sense-making items are placed within the over-all Cynefin space—without boundaries—where theitems seem to fall, using dynamic placement. (Wesometimes ask people to think of it as though theitem they are placing has four elastic bands connect-ing it to the four corners, and to find the place whereit comes to rest depending on how hard the differ-ent bands pull on the item. We then ask them tocheck the placing of each item in relation to others.)Clusters are allowed to form where items seem sim-ilar in the space, but are not required. This is oftendone in person using large walls and hexagonal stickynotes; it can be done electronically, but must be donesocially.

It is important to mention at this point that discus-sion is encouraged during the placement of items.This is unlike the methods of affinity diagrams, inwhich people are asked to refrain from speaking.42

In our experience, although the proponents of af-finity diagrams are correct that silence equalizes theverbal contributions of those who speak up and thosewho hold back, the placement of items is not equal-ized by silence: often people just watch very care-fully what the boss is doing. In a sense this only drivespower differences underground rather than remov-ing them. We find it is better to remove large powerdifferences before contextualization; in fact, we havefound that comparing the patterns made by peopleat different levels of management working on sep-arate contextualizations can be of great value, es-pecially for tackling difficult management issues. An-other significant element of the placement of itemsis that, as in the group construction of affinity dia-grams, we encourage people to consider all items to-gether and to keep moving any items they like untilthe patterns they have produced make sense.

When all the items are placed, as shown in Figure3B, lines are drawn between hexagons that are clearlyin one domain or another, leaving a possibly largecentral area of disorder. Then, as shown in Figures3C and 3D, the boundary lines are “pulled in” tomake the distinctions between domains more com-plete. Hexagons that lie on the new lines are bifur-cated, trifurcated or quartered, forming new clus-ters of hexagons on either side of the boundaries.This stage involves much discussion, as consensushas to be reached.

Figure 3 Cynefin sample contextualization session

A B

DC


At this point, the characteristics of each domain andboundary—as they pertain to the context at hand—can be considered using the sense-making items inplace.

Use of the contextualized framework. After theCynefin framework has been created, we may moveon to other exercises in which the items in specificareas (for example, near the boundaries or at theextremes) are considered in more detail—or con-versely, in which the entire contextualized frameworkis used to describe the changing dynamics in a his-torical case or a contemporary situation, possiblyfrom different points of view.

We should point out here that though we draw theframework as four simple areas in two-dimensionalspace (because it is quick to draw and grasp), thisis only a quick reference for discourse, and that sim-ple drawing expands into something more multidi-mensional in use. For example, we might ask peopleto consider different aspects of or perspectives ona single situation that might be located in differentareas or moving in different directions. In this sense,all sense-making exercises transcend the simple rep-resentation of the framework at some point. We con-sider the framework to be a “jewel of contempla-tion” that has many facets, like a geographicalinformation system, in which many layers of in-formation are overlaid so that they can be inte-grated or separated at will; but the ultimate re-ality is that every representation (including theentire framework itself) is created for a purpose.

The value of the completed contextualized frame-work lies in two main benefits. First, nearly every con-textualization exercise we have seen has ended withexpressions of surprise from those participating.They often see, for the first time, patterns that over-turn their entrained beliefs about the issue they areconsidering and about their purpose, goals, and iden-tity. For example, one group completed their Cyne-fin framework and reviewed it. They had done al-ternative histories to derive their sense-making items,and they had been asked to provide at least one ac-cident in each fictional time line. On their Cynefinframework, the only items in the chaos domain werethose (color-coded) accidents. One participantlooked at them and said, “We are being complacent,aren’t we?” The participant meant that they had onlybeen willing to consider wholly chaotic situationswhen they had been forced to add accidents to thelist.

This increased awareness (reflected in many othersuch stories) is the highest achievement of the com-pletion of the contextualization exercise: that thegroup should accomplish Descriptive Self-Aware-ness, or a greater understanding of their own biasesand potentials. This is also our goal in helping peo-ple go through the process, because it is our placeto enable clients to achieve self-awareness ratherthan to provide “expert” advice, which has a muchlower value in practice.

The second benefit of the contextualized Cynefinframework is that it provides a new shared languagewith which the members of the decision-makinggroup can discuss situations, perspectives and pos-sible actions. This new language is unique to the con-cerns of the group and abstract enough to cover manyparticulars, but resonant with meaning so that it tendsto be brought up spontaneously when issues are dis-cussed. It can be used to talk about interpretationsof current conditions based on gathered data, to eval-uate strategic interventions, and to constructivelymanage conflict and bring about consensus, withoutremoving conflict. Also, multiple groups who havecreated their own contextualized frameworks can usethem as artifacts for negotiation of common mean-ing. For example, if one group placed “the influenceof the Internet on globalization” in complex spaceand another group placed it in knowable space, bothgroups would learn something about their respec-tive perspectives. We have been helping groups touse such frameworks to guide discussion among dif-ferent government branches, for example.

We previously contrasted Cynefin as a sense-mak-ing framework with categorization frameworks. Wedo sometimes use the contextualized Cynefin frame-work for categorization within a particular context,meaning that the terms used are not generic but spe-cific. Categorization in context has some excellentuses: for example, for training in standard operat-ing procedures, for aligning perspectives and objec-tives among groups (for example, strategic and op-erational), or for initiation of new people into thegroup.

Wider implications

As we mentioned previously, the contextualizationexercise is just one of several elements involved inusing the Cynefin framework to support people mak-ing decisions and crafting strategies. As part of thework we are doing for public-sector and private-sec-tor bodies, including the government, we are design-


ing computer software that uses the Cynefin frame-work as a sense-making mechanism in tandem withmassive narrative databases of world history and con-temporary events, in order to support policy-mak-ing and decision-making at both the operational andstrategic levels in government and industry.

Other elements of our work over the past severalyears, those having more specifically to do with theuse of narrative to enable multi-perspective under-standing in the complex domain, are also heavily in-volved in this work, but we do not have the space

to describe them here. They are described in recentpapers,40–41,43 and we plan to feature them stronglyin an upcoming book on the subject. Instead, we willdelve a little more deeply into some more advancedtopics related to using the Cynefin framework.

Cynefin boundaries

Boundaries are possibly the most important elementsin sense-making, because they represent differencesamong or transitions between the patterns we cre-ate in the world that we perceive. Depending on howyou look at it, any gradient can be a boundary andany boundary can be a gradient, so there is alwaysroom for interpretation. We distinguish betweentypes of boundaries on an experiential basis, in thesense of: How does the essence of this boundary, asI perceive it, affect my sense of the situation and ofwhat I should do? In that sense, the boundaries weconsider are more like phase changes than physicalboundaries (though they could be physical bound-aries, if those boundaries coincide with phasechanges).

We use a range of metaphor sets to create an un-derstanding of boundaries. One of the most effec-tive is a geographical set, as follows:

1. The shallow river can be crossed by anyone at anyplace, and thus control over crossing is difficult toachieve. However, it is easy to tell when one hascrossed it (or when others have) because one’s feetget wet. Most of the important events of our lives(e.g. birth, marriage, parenthood, death) are shallow-river boundaries, because anyone can go throughthem and they “mark” us with the change. Ritualtends to be strongly associated with this type ofboundary. An organizational example might be thetransition from a new employee to someone whoknows the inside stories of the organization. Main-taining shallow-river boundaries is most useful whenyou want to encourage as much diverse exchangeover the boundary as possible, but still retain the ca-pacity to monitor and intervene.

2. The deep chasm can be crossed only at bridges,which can be built, demolished, and controlled at will.It is not easy to tell when one has crossed the bound-ary, but such a marker is not required because onlysome are allowed through. An example of a deep-chasm boundary might be the front page of a com-munity Web site that requires visitors to register withtheir names and addresses in order to participate,but does not record individual movements duringregular visits to the site. This type of boundary is mostuseful when the exchange is too important or dan-gerous to be left open to all possible movements. Theselectively permeable barrier found in our cells is aboundary of this type.

3. The high plateau is the boundary with the mostpotential danger, because you may not be aware thatyou have crossed the boundary until it is too late andyou drop off the other side. One of us once volun-teered on a mountain rescue team. The worst placeto get lost was on a plateau—there are often heavymists on high plateaus, and people lose their senseof direction and head directly off a cliff. When youare on such a plateau, it is nearly impossible to knowwhere you will come out. (Those fans of certain sci-ence fiction programs will recognize this type ofboundary in transportation devices, which offer theenticing possibility of putting you somewhere you hadnot meant to go.) An organizational example of ahigh-plateau boundary might be the transition thathappens during a corporate restructuring, whengroups are wandering around looking for supportand no one knows who will survive. There are, ofcourse, times when a high-plateau boundary is justwhat you need: to confuse an adversary, to promoteinnovation (in limited circumstances), or to disruptold patterns that have become limiting.

Boundaries are possibly themost important elements,

in sense-making, because theyrepresent differences among

or transitions between thepatterns we create in the

world that we perceive.


When we are using the Cynefin framework as con-textualized by a group to their context and purpose,we ask them to consider the boundaries betweenCynefin spaces by using metaphorical types of bound-ary. We explain that each boundary might have a dif-ferent form in one direction or the other, and thisis where we must break away from the two-dimen-sional drawing somewhat. In addition, one bound-ary might have different forms for different people,whose perceptions or circumstances make their expe-rience of the boundary different. Generally, we findthree basic levels of sophistication in the use of Cyne-fin boundaries for sense-making. First, one consid-ers an awareness of crossing the boundary, so thatone can respond quickly to new conditions after onehas arrived on the other side. Second, one considersan awareness of approaching the boundary, so thatone can sense when change is incipient and respondbefore the boundary is crossed (perhaps to cross itpurposefully, perhaps to avoid it). Third, one con-siders managing the boundary and the perceptionssurrounding it, so that one can, for example, put adeep-chasm boundary in place for one’s adversarywhile maintaining a shallow-river boundary for one’sown use.

One thing we have found in using boundaries as partof the Cynefin framework is that different people,with different training and personalities, seem to ben-efit from different uses of boundaries. People whoare used to classifying items into categories benefitfrom removing boundaries, as takes place in the stan-dard contextualization exercise described earlier.However, people who are used to thinking in a morefluid way—about gradients rather than boundaries—seem to benefit more by constructing boundariesthan by removing them.

For example, when the workshop is large enough orwhen we feel that it is required, we often hold a par-allel session of contextualization in which people areasked to distribute their sense-making items alonga line, ranging from the most tractable items to themost intractable items. After the line has been com-pleted (and there are many negotiations to placeitems in relation to each other), we ask people tofind places along the line at which they feel that theunderlying dynamic has shifted. In other words, weask them to create boundaries along gradients. Wethen pull the line into a rainbow curve and place iton the Cynefin framework, with the most tractableitems in the known domain and the most intractableitems in chaotic space. This produces an alternatecontextualization, with the same ultimate effect of

creating the Cynefin framework anew, but with astronger emphasis on the negotiation of whereboundaries are found. We sometimes ask people tonegotiate boundaries as though they were represen-tatives of the different domains, coming up with amutual agreement on what the boundary means andwhere it is placed.

The boundary issue is one on which we continue topursue a strong research agenda (although of coursethe entire framework is a work in progress), espe-cially with regard to its use for strategic decision sup-port.

Cynefin dynamics

When people use the Cynefin framework, the waythey think about moving between domains is as im-portant as the way they think about the domain theyare in, because a move across boundaries requiresa shift to a different model of understanding and in-terpretation as well as a different leadership style.Understanding the differences among the differentmovements in the framework increases the sophis-tication of the response of a decision-making groupto rapid change. We describe here some of the pat-terns of movement which we use to help groups con-sider historical, contemporary, and future change.In general, one of the functions of the Cynefin frame-work is to increase awareness of the upper domainsof the framework and their potential to create sus-tainable change; several of these movements are de-signed to make the upper domains more accessible.

Movement at the known-chaos boundary. Thisboundary is the strongest of the four, in which a per-fectly working machine operates inches away froma devastating fire. For that reason, this boundary isthe most dangerous—and the most powerful iftreated with respect.

Asymmetric collapse (Item 1 in Figure 4) is move-ment from the known to the chaotic, disastrously.We have seen a tendency for organizations to os-cillate between the domains of the known and thechaotic, avoiding the upper domains. Organizationssettle into stable symmetric relationships in knownspace and fail to recognize that the dynamics of theenvironment have changed until it is too late. Thelonger the period of stability and the more stable thesystem, the more likely it is for asymmetric threatsor other factors to precipitate a move into chaos. Thedecision makers in the system don’t see things thatfall outside the pattern of their expectation, and they


continue not to see them until finally the systembreaks and they find themselves in chaos.

The final stage before the break point is witnessedfrequently in history. A good example is the trial ofGalileo, in which the Catholic Church accepted thatthe earth went round the sun for the purpose ofmathematic calculation, provided no one said it wasactually the case. In retrospect, this was an unten-able position, which only delayed and made worsethe inevitable collapse. This phenomenon of grasp-ing at order is common in people, governments, aca-demia, and organizations of all shapes and sizes. Of-ten the strongest dominant player in a market willcontinue with behavior long after its utility, perceivedfrom a different perspective, is exhausted (Boisot44

uses IBM as an example of this). Also, senior deci-sion makers and their policy advisors will find waysof fitting reality into their existing models rather thanface the fact that those models are outdated, and theywill punish dissent (the history of science and bus-iness provide examples). Galileo is tried afresh inmodern organizations on a regular basis.

Imposition (Item 2 in Figure 4) is movement fromthe chaotic to the known, forcefully. The conse-quence of asymmetric collapse is chaos, and the con-sequence of chaos is frequently Draconian imposi-tion of order, in which the situation is so catastrophicthat people accept what would have previously been

unacceptable as the price of order. The problem withthis dynamic is that it introduces a new stability thatin turn becomes more rigid until the new orderbreaks in its turn. A familiar example in organiza-tional life is the cyclic reorganization of authority byindustry, then by function, then by industry, and soon in an endless cycle; or the fact that well-inten-tioned revolutionaries sometimes put into place bu-reaucracies even more stifling than those they over-threw. However, we do not mean to imply that allsuch transitions are pathological. When order is wellaligned with needs, it can bring needed savings andcalm. Anyone who has seen a talented teacher takecontrol of a frantic classroom through authority andrespect, or a policeman calm a panicked crowd, canunderstand the utility of imposed yet well-placed or-der.

Movement at the known-knowable boundary. Thisis the boundary where the scientific method is be-lieved to operate, though in practice most agree thatsome un-order is involved in most scientific work (forexample, hunches, analogies, networks, local prac-tices, and shared beliefs). This boundary is fluid andpermits much traffic as people go about the businessof building technologies and pursuing lines of inquiry.

Incremental improvement (Item 3 in Figure 4) ismovement from the knowable to the known andback, repeatedly. This type of movement is the best-known and accepted of the types we list here. Formany situations, this remains the movement ofchoice. In a sense, the cyclic flow of informationacross this boundary is the engine of technologicalgrowth. However, it can become pathological if cy-clic movements between known and knowable de-part ever further from observed reality (as with, forexample, the epicyclic models of the solar system orthe “science” of phrenology). This sort of movementshould be linked occasionally with one of the largermovements we mention later.

Movement at the knowable-complex boundary. Theboundary between the knowable and the complexcan be a fruitful one for science, and in practice com-plements the known-knowable border as an engineof new ideas. It is not as permeable as the known-knowable boundary because transitions must trans-late between two systems of order and from one setof rules to another.

Exploration (Item 4 in Figure 4) is movement fromthe knowable to the complex, selectively. This move-ment is often mentioned in the literature on com-

Figure 4 Cynefin dynamics

3 INCREMENTAL IMPROVEMENT

7 DIVERGENCE- CONVERGENCE

1 COLLAPSE

2 IMPOSITION

6 SWARMING

X

X

5 JUST-IN-TIME TRANSFER

4 EXPLORATION


plexity as exploration versus exploitation.17 Explo-ration is an opening up of possibilities by reducingor removing central control without a total disrup-tion of connections. In organizations, explorationtakes many forms, but trust is key in this movement.One is, in effect, taking a risk by allowing constit-uent connections to form and strengthen at the ex-pense of central control, and that requires not onlygood planning and awareness of the “shadow” side

of the organization, but also careful (but unobtru-sive) monitoring of the situation. In most organiza-tions there is a strong and often untapped resourceto be found in exploratory moves such as this. Forexample, informal communities, which may rangefrom public to secret in their profile, provide a richand fertile source of knowledge and learning that istoo large and complex to be formally managed. Onestudy of actual practice in IBM Global Services34 in-dicated some 50–60 official knowledge areas, com-plemented by many tens of thousands of private ar-eas. By providing spaces in which members of theorganization could naturally share with people theytrust, a fertile source of learning was created.

Just-in-time (JIT) transfer (Item 5 in Figure 4) ismovement from the complex to the knowable, se-lectively. This movement is often called exploitationin the complexity literature, and it involves the se-lective choice of stable patterns in complex space forordered representation. In the IBM example justcited, the 50–60 official communities are able to drawon information coming out of the informal trust-based communities as long as they refrain from dis-turbing their delicate balance. Knowledge can bemoved into the formal space on a just-in-time basis:knowledge is made available when it is needed. Tech-niques to achieve this include subject-matter flag-ging and privacy-ensured searching of content. Theissues here are those which gave rise to JIT techniquesin manufacturing some decades ago: organizationsrealized that the cost of maintaining stock on the fac-tory floor was out of all proportion to the benefits,with high levels of wastage over and above stock hold-

ing costs. In consequence, stock holding shifted backto the suppliers, entering the factory just in time.43

Movement at the complex-chaotic boundary. Thisboundary, like the known-knowable boundary, isfluid and in fact difficult to delineate. In nature, sys-tems move back and forth across this boundary of-ten. In that sense, traffic across this boundary mir-rors that across the known-knowable boundary: oneis an engine for technological and scientific order,and the other is an engine for organic order. In thesocial sphere, we can use the engine of complexityto enable emerging patterns that prove useful.

Swarming (Item 6 in Figure 4) is movement from thechaotic to the complex, to the knowable; first, in anemergent manner and then, selectively. Draconianimposition of order is most appropriate in symmet-ric conditions and partial remediations, but underasymmetric conditions, or when whole-system inter-ventions are required, we need to move from chaosto the complex, not to the known. The boundary be-tween chaos and order is a chasm difficult to cross,but a vertical transition across the more permeableboundary between chaos and complexity is inherentlymore manageable. A transition from the chaotic tothe complex is a matter of creating multiple attrac-tors, or swarming points, around which un-order caninstantiate itself, whereas a transition from the cha-otic to the known requires a single strong attractor.For example, if one were trying to evacuate a pan-icked crowd in a theater on fire, it would make moresense to shout out “the blinking orange lights areabove the exit doors,” which is a complex swarming-point trigger that relies on local knowledge only, thanto shout out “come towards the back of the theatre,”an ordered trigger that relies on global knowledgewhich may be unavailable.

After we have achieved the shift from chaos to thecomplex, then we have the possibilities of many pat-terns forming around the new attractors; those wefind desirable we stabilize through a transfer to theexploitable domain of the knowable; those that areundesirable are destroyed. We have found in sev-eral recent engagements that the contrast of swarm-ing with imposition provides a new language for ex-ecutives and appears to provide new perspectives oncrisis management. We will be studying actual be-havior and creating more “subjects” in this field overthe next year as our use of dynamic movementswithin the Cynefin framework develops.

Informal communities,which may range from public

to secret in their profile, providea rich and fertile source

of knowledge and learning.


Divergence-convergence (Item 7 in Figure 4) is amovement from the complex to the chaotic and back,repeatedly. The active disruption of a complex sys-tem to precipitate its move to chaos is less of a changethan moving it to either of the ordered domains, andthis is easier to manage across a permeable bound-ary. In knowledge management, for example, infor-mal communities that occupy the complex domainare more resilient when asked to undergo radical dis-ruption in an innovation program than the expertcommunities of the knowable domain. 39 Smallstart-up companies handle disruption better thanlarge bureaucratic ones, but even within large bu-reaucratic organizations, there are small groups thatcan act in the role of start-ups, and they can increasethe adaptability of the organization.

Our complexity-inspired workshop techniques, as ex-plained above, make intensive use of the boundarybetween the complex and the chaotic, in effect cy-cling between the dynamics of the two states as asort of pattern generator to create a rich variety ofpatterns among which to choose—to stabilize andto disrupt—in order to facilitate sense-making.

Visiting chaos

There are some good reasons to move deliberatelyfrom order to chaos. There are times when it is nec-essary to break rigid structures in precipitation of a

natural collapse (as one approaches the boundary),so that the transition can be managed more care-fully; and there are times when a strong disruptionis the only mechanism that will break up a strongbut unhealthy stability. The last three movementtypes we will consider use the chaotic space for tem-porary disruption of all connections (possibly withina restricted context) as a stimulant to new growth.

Entrainment breaking (Item 8 in Figure 5) is move-ment from the knowable to the chaotic to the com-plex, periodically. In entrainment breaking, we movefrom the knowable to chaos and thus stimulate thecreation of new complex systems as the system re-bounds into the complex domain. This is a commonapproach to disrupt the entrained thinking of expertswho, in our experience, tend to be the most conserv-ative when it comes to radical new thinking. Themove to complex space is not radical enough to dis-rupt those patterns; we need to challenge at a morebasic level the current assumptions of order. By us-ing the complex space as a staging post, we createa more fertile space of interactions from which wecan select stabilization points for the movement tothe knowable. A knowledge management exampleis the creation of formal communities by clusteringand swarming informal activities from existingtrusted relationships.39 In strategy, this method canbe used to create and validate new sources and struc-tures for decision-making.

Liberation (Item 9 of Figure 5) is movement fromthe known to the complex to the knowable, period-ically. Organizations tend to assume that they candesign the nature of new systems. For example, anorganization that needs new expertise in an areamight commission a university to carry out a study,recruit specialist staff, or identify individuals withinthe organization and assign them new responsibil-ities. This is a successful and effective strategy whenthe conditions are suitable for ordered approaches.However, if the situation is uncertain, it is more use-ful to shift the problem from the domain of theknown to the complex. Organizations need to in-crease both internal and external levels of contactto the point where new patterns can emerge. Boisot44

makes the point that companies need to use bothhoarding strategies, in which they place defensivebarriers around what they know and focus on exploi-tation, and sharing strategies, where knowledge isshared within and outside the organization with theintent of increasing the volume of opportunities, withthe strategic advantage shifting to speed of exploi-tation of knowledge.

Figure 5 Cynefin dynamics using chaos

8 ENTRAINMENT BREAKING

9 LIBERATION

10 IMMUNIZATION


For an organization, sharing strategies involve a pro-cess of letting go, of creating freedom within heu-ristic boundaries to allow new patterns and new lead-ership to emerge. One of the techniques we use inthis area is Social Network Stimulation,39 which aimsto stimulate the interactions of agents (or rather iden-tities) within systems to allow the emergence of newcoalitions, alliances, and leadership. To use a met-aphor, we cast seeds (ideas, deliberately ambiguousgoals), which are cheap, across a broad landscapeand see where growth occurs. As soon as growth isevident, we respond quickly to shift the newly emer-gent idea or leaders or coalition into the knowable.We have called this movement liberation because itbreaks the entrainment of bureaucracy—but like allletting go, it is difficult. This is one of the most threat-ening of transitions to entrenched managers, but oneof the most important.

Immunization (Item 10 of Figure 5) is movementfrom the known to the chaotic, temporarily. Immu-nization in chaos is a smaller “visit” to chaotic spacethat shakes up “the way things are” enough to causereflection but not enough to destabilize the entiresystem. Immunization serves two purposes. First, itinures people to the devastating force of chaos sothat they will be better prepared to face those forcesin the future. A perfect example: it is said that thegreat director Buster Keaton was able to craft hisdeath-defying stunts (such as a house falling aroundhim, a rescue from a drenching waterfall, amazingpratfalls, and so on) because as a toddler he was liftedout of bed by a tornado and set down unhurt in thestreet.45 Second, immunization brings new perspec-tives, which cause radical disruptions in stable pat-terns of thought and lead to new complex patterns.Examples of such events are scattered throughoutliterature, in the accident that changes a politician’scareer, or the chance encounter that causes a lonelywoman’s life to fill up with new meaning, or in manyother kinds of radical departures that make every-thing on which one had relied seem meaningless andrestricting.

Metaphors are particularly useful agents of immu-nization because they allow conversation about pain-ful things, enable disruptive and lateral thinking, pre-vent entrainment of attitudes, and clear out thecobwebs of stagnant ways. One technique we use forthis purpose is called the “Grendel game” (materialavailable from the authors, not yet published), whichcombines anthropological study, complexity theory,and managed war games to create an exciting andinnovative learning event. Here, following a study

of the organization, using anthropological techniquesdeveloped and proven within earlier research intoanecdote collection, a fictional planet is populatedby aliens selected to reflect the current culture andnew scenarios. This is done with a leading scientist,who in his spare time designs consistent alien en-vironments for use by science fiction and fantasy writ-ers. Members of the organization then seek to col-onize the planet in a managed war game. They facetheir own organization in a metaphorical setting thatallows more profound and meaningful learning.Newness is simulated without threat, and the par-ticipants are habituated to perspective shift and un-certainty.

Background movements

In any consideration of deliberate change, one mustconsider what is already going on. The forces of thepast tend to cause clockwise drift in the Cynefinspace: people living together and sharing mutualneeds lead to the emergence of ideas; convenienceleads to stabilization and ordering of the ideas; tra-dition solidifies the ideas into ritual; and sometimes,either lack of maintenance or the buildup of biasesleads to breakdown. The forces of the future pushdynamics to the counter-clockwise: the death of peo-ple and obsolescence of roles cause what is knownto be forgotten and require seeking; new generationsfilled with curiosity begin new explorations that ques-tion the validity of established patterns; the energyof youth breaks the rules and brings radical shifts inpower and perspective; and sometimes impositionof order is the result. In a sense, these two forces arealways pulling society in both directions at once, andthis is reflected in organizations as well. The oldguard is forgotten at the same time that its beliefsaffect newcomers in ways they cannot see. An aware-ness of these dynamics in the organization must pre-cede any deliberate attempt to affect it by deliber-ate change.

Use of Cynefin dynamics in practice

Our use of the boundary transitions described hererelies on narrative because boundaries are essentiallyabout change and narrative is about change. We mayask people to consider a situation in the past andwhat movements took place in it from different per-spectives, or we may ask people to envision fictionalnarratives about the past, present or future in whichselected movements form the backbone of the story.(Remember this is all done not in the abstract, butusing the contextualized Cynefin framework that


makes sense in the context of concern.) These nar-ratives of change are used in the sense-making pro-cess, in which they may be quickly created and dis-carded, or they may be saved and used to generatea shared language about change in much the sameway as cycles of folk tales long ago. They are not,however, allowed to stabilize into expectations; theymust remain fluid to be useful.

A critical distinction between this type of narrativegeneration and that of scenario planning46–47 is thatthe source of Cynefin-based narratives is not a setof expected ranges of expected variables, but a con-sideration of dynamics in which the variables andranges are sometimes unknown and perhaps evenunspecified. This creates a more diverse, flexible, andchangeable set of narratives that should be truly sur-prising. For example, a scenario-planning exercisedone by a police force might result in scenarios ex-ploring the space from high to low crime, corrup-tion, and terrorism. These scenarios are useful in con-sidering a future in which those axes are the mostimportant—but what about the situation where theyare overridden by a previously irrelevant factor? Nar-ratives generated using a contextualized Cynefinframework explore spaces in which the dynamic sit-uation arises from any source. Optimally, a widerange of diverse possibilities (chaos from a nuclearaccident, a coup, an epidemic, an alien invasion) isbest, even though some scenarios might be incon-ceivable or even nonsensical. Conceivability is notthe point: preparation for the unexpected is.

Note that we do not believe these methods shouldsupplant scenario-planning in all contexts, becausethat method works well in knowable space, whereits results are productive. We do believe, however,that these are the methods of choice in complex sit-uations where a wider range of possibility needs tobe explored. In fact, as we increase the number ofmethods available for the un-ordered domain, meth-ods that work well in the ordered domain get evenstronger because they are no longer used in situa-tions in which they have limited applicability.

Relationship to other frameworks

We do not pretend that all the basic ideas inherentin the Cynefin framework are new or unique. Theycan in fact be found floating around history for thou-sands of years. The distinction between order andun-order (and their interactions) is ancient, as wementioned, as well as being taken up by recent au-thors.48 The chaotic-complex distinction has been

much debated in recent years, with some saying com-plexity exists at the “edge of chaos,”10 some sayingthat the two phenomena have separate origins andcannot be placed together,19,49 and some even say-ing that the distinction is artificial and arbitrary.50

The distinction between known and knowable iswidespread and goes back to ancient philosophy. We

do claim originality for the development of the ideasbehind the framework in its full form (as we havedescribed it, and in some other aspects outside thescope of this paper) and for the methods we use tomake the framework useful in practice (though ofcourse they have their relationships with other ac-tion research and sense-making methods).

Courtney’s51 framework, in which he distinguishesbetween four states of increasing “residual uncer-tainty” (uncertainty that cannot be reduced by anal-ysis) questions universal assumptions about the useof known-space methods and tools. He does seemto believe, however, that the level of uncertainty canbe “defined”—that is, he has no domain of disorder(which is essentially a state of uncertainty about un-certainty). This, we suspect, may cause people togravitate to the domain they find most plausible, aswe have seen happen. Also, his “toolkits” of choicefor each level of uncertainty seem to cover only theknown and knowable spaces in the Cynefin frame-work, with a slight nod to narrative methods in com-plex space. In effect, he does not break out of therighthand side of the Cynefin framework. He alsodoes not seem to consider the possibility that a sin-gle circumstance may contain competing aspects andperspectives with different degrees of uncertainty orthat such differences can be used to strategic advan-tage. Certainly there is much to be gained from allattempts to diversify responses to differing contexts,however.

Returning to assumptions

To complete our circle, we should address the threeassumptions we identified at the start of this paper.

As we increase the numberof methods available for the

un-ordered domain, methods thatwork well in the ordered domain

get even stronger.


As we said at the beginning, these assumptions arevalid in some circumstances, but not in others. Letus examine each one again and consider how we canexpand these assumptions to a universally applica-ble set. We will also briefly speculate on emergingapplications of the Cynefin framework to manage-ment science and practice.

The assumption of order. Relaxing this assumptionis the basis of the Cynefin framework, which pro-poses instead two types of order, each with distinc-tions inside, and a recognition that uncertainty mayexist in distinguishing these types (the domain of dis-order). The assumption of order holds for orderedspace, the known and knowable, so we need new as-sumptions for the domains of un-order and disor-der. In complex space, we can safely assume that pat-terns will form, unpredictable in their details butusually recognizable in their basic forms, and thatwith practice we can learn to detect these formingpatterns, stabilize or disrupt them depending on theirdesirability, and seed desirable patterns by creatingattraction points. In chaotic space, we can assumethat all connections have been broken, that possi-bility reigns, that old patterns have been disrupted,and that the outcome is not predictable. In the spaceof disorder, we know something very valuable—thatwe do not know. We need to gain more understand-ing (in every way possible) so that we can find pat-terns and react to them.

In management, relaxing assumptions of ordermeans recognizing that not all effective solutions areefficient solutions. It does not mean that trust hasto be given blindly or that complex processes can-not be affected; it only means that when the meansmatch the context, less energy need be expended forthe same result. In a very real sense, managers havesuccessful models available in the domains of un-or-der in the way they manage their children; they useboundaries and interventions to encourage desirablebehavior but do not attempt to control it throughgoal-based direction. The use of these methods isopening some high-potential developments in man-aging organizations following mergers and in creat-ing the conditions for continuous learning and in-novation.

The assumption of rational choice. Relaxing this as-sumption means that context and perspective be-come as important as rationality. This is an impor-tant reason that the Cynefin framework is not about“objective” reality but about perception and under-standing; it helps us to think about the ways in which

different people might be perceiving the same sit-uation. For example, there is an old folk tale fromIndia52 in which a wise man decides that in order toescape an impossible royal demand, he will fake in-sanity in the king’s court. He is operating in com-plex space because he is using cultural shorthandsto provoke predictable reactions but is gambling thathis ruse will seed the pattern he wants to create. Heknows that from the perspective of his audience, whoare operating in the space where things are boundby tradition and thus known, he appears to be act-ing chaotically, because they can conceive of no otherreason for him to act this way in front of the king(who would surely behead him if he was faking). Thusby proving that he cannot be faking, he pulls off thefake. Understanding not only that there are differ-ent perspectives on an event or situation, but thatthis understanding can be used to one’s advantage,is the strategic benefit of relaxing this assumption.Narrative techniques are particularly suited to in-creasing one’s exposure to many perspectives on asituation.

In management, there is much to be gained by un-derstanding that entrained patterns determine re-actions. This realization has major implications fororganizational change and for branding and market-ing. Our own work on narrative as a patterning de-vice is gaining presence in this and other areas. Spec-ulating, one of the most significant possibleapplications of this understanding is a move awayfrom incentive-based targets and formal budgetingprocesses—both of which, we contend, produce asmuch negative as positive behavior. It is a truism tosay that any explicit system will always be open to“gaming.” Paradox and dialectical reasoning are keytools for managers in the un-ordered domains.

The assumption of intentional capability. The effectof relaxing this assumption is also one of consider-ing context, but more of context on action than onperspective. It means asking not, “What did they havein mind when they did that?” but, “What does itmean that this happened?” John F. Kennedy was pre-sented with such a dilemma when he received twoletters in rapid succession from the Soviets duringthe Cuban missile crisis, one conciliatory and onehard-line.53 Which letter was a wink and which wasa blink? It turned out, of course, that both letterswere winks but of different actors (Khruschev andthe Politburo, respectively). The different authors ofthe letters probably saw their actions from the com-plex space of the Cynefin framework because theyunderstood the internal politics that produced them.


To Kennedy, however, receipt of the two lettersplunged him into chaotic space, where he could con-ceive of no sensible intention to send such contra-dictory letters—to confuse, perhaps, or to delay whilethe missiles were being prepared. It was only afterscrutiny by linguists that the Kennedy administra-tion was able to understand that the intentions be-hind the two letters came from different sources. Thismoved his understanding into complex space wherehe could respond. It is only possible to consider al-ternative explanations for actions when one relaxesthe assumption that all actions are deliberate.

In management and in strategy, the issue of assump-tions about intentions can have pronounced effects.For example, one may assume that the rejection ofa new initiative by employees is intentional, when infact it is an accident of emergent patterns of inter-action. Treating the rejection as intentional may cre-ate exactly the reaction that the managers wished toavoid in the first place. The same is true of over-re-action to accidental competitor behavior that is pre-sumed to be intentional.

Conclusion

This paper outlines a new approach to strategy, bothin policy formation and in operational decision-mak-ing. While it is new, this approach also recognizesas critical the value of what has been done to date.As such, it starts to break the fad cycle that has be-devilled management science for several decades. Itrecognizes the progression of human knowledge, inthat something which has provided value is not ren-dered valueless by new thinking, but is bounded bynew insight and legitimized within boundaries, andthereby, made more, rather than less, effective. Thisapproach is, we think, unique in that it recognizesthe value and interaction of order and un-order. Assuch, it also allows us to make a critical distinctionbetween efficiency and effectiveness. Human groupsneed to be effective; machines and structured hu-man interactions (such as manufacturing processesor the application of rules of engagement) need tobe efficient.

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Accepted for publication April 24, 2003

Cynthia F. Kurtz IBM Global Services Lotus Development, 1 Rog-ers St., Cambridge, MA 02142 ([email protected]). Ms. Kurtz isPrincipal Researcher for IBM’s Cynefin Centre for organizationalcomplexity. She received her B.S. degree in biology from ClarionUniversity of Pennsylvania in 1986 and her M.A. degree in ecol-ogy and evolution from the State University of New York at StonyBrook in 1990 (after completing five years of Ph.D.-level grad-uate work studying the evolution and complexity of social behav-ior). From 1992 to 1998 she co-owned a small software business,and is the co-creator of two internationally distributed and widelyreferenced environmental education simulators on plant growth,soil science and evolutionary design. In 1999, she joined theKnowledge Socialization Group at the Thomas J. Watson Re-search Center, where she carried out pioneering work on nar-rative in organizations, including the creation of an XML schemafor describing stories and storytelling contexts. She moved to theInstitute for Knowledge Management in 2001 to work on bothnarrative programs and complexity programs before helping foundthe Cynefin Centre in 2002. She is currently leading work on theuse of narrative and complexity-informed techniques for gainingmulticultural perspective in decision environments, and is mainlyresponsible for the development of narrative database technol-ogy.

David J. Snowden IBM Global Services, 79 Staines Road West,Sunbury-on-Thames, TW16 7AN United Kingdom ([email protected]). Mr. Snowden is the director of IBM’s Cynefin Cen-tre shortly to be based in Cardiff University, Wales. He receivedhis B.A. degree in philosophy from the University of Lancasterin 1975 and an M.B.A. degree from Middlesex University in 1986.His early career was in the specification of decision support sys-tems for international companies, progressing to general man-agement and strategic marketing positions in Datascience priorto its acquisition by IBM in 1996. He was a director in IBM’s In-stitute for Knowledge Management before founding the CynefinCentre in 2002. He is an adjunct professor of knowledge man-agement at the University of Canberra, an honorary fellow inknowledge management at the University of Warwick, and hasreceived several awards for his work in knowledge management,including one from the Academy of Management in 2001 for hisoriginal contributions to the field.


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