the new dynamics of strategy: sense-making in a complex and complicated world

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8/3/2019 The new dynamics of strategy: Sense-making in a complex and complicated world http://slidepdf.com/reader/full/the-new-dynamics-of-strategy-sense-making-in-a-complex-and-complicated-world 1/22 The new dynamics of strategy: Sense-making in a complex and complicated world by C. F. Kurtz D. J. Snowden In this paper, we challenge the universality of three basic assumptions prevalent in organizational decision support and strategy: assumptions of order, of rational choice, and of intent. We describe the Cynefin framework, a sense-making device we have developed to help people make sense of the complexities made visible by the relaxation of these assumptions. The Cynefin framework is derived from several years of action research into the use of narrative and complexity theory in organizational knowledge exchange, decision-making, strategy, and policy-making. The framework is explained, its conceptual underpinnings are outlined, and its use in group sense-making and discourse is described. Finally, the consequences of relaxing the three basic assumptions, using the Cynefin framework as a mechanism, are considered. Overthepastseveralyears,ourgrouphasbeencon- ducting a program of disruptive action research us- ing the methods of narrative and complexity theory to address critical business issues. 1  Action research has been defined as grounding theory in contextual exploration,emphasizingparticipation,andembrac- ing change. We started work in the areas of knowledge manage- ment,culturalchangeandcommunitydynamics,then expanded into product development, market cre- ation and branding, and in recent years have been  working increasingly in the area of national and or- ganizational strategy. Some of this work has been directly funded by the U.S. government through DARPA (Defense Advanced Research Project  Agency)aswell asbyothergovernment agencies(in particularinSingapore)which areinterestedinnew approaches to supporting policy-making. The cen- tral element of our approach is the Cynefin frame-  workforsense-making.Inthis paperwedescribethe framework and its conceptual basis, and we detail someofitsusesforsense-makingtosupport decision- making in varied dynamical contexts. Conceptual approach. Webeginbyquestioningthe universalityofthreebasicassumptions that pervade the 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 underlying relationships between cause and effect in human in- teractionsandmarkets,whicharecapable ofdiscov- ery and empirical verification. In consequence, it is possibleto produceprescriptiveandpredictive mod- els and design interventions that allow us to achieve goals. This implies that an understanding of the causallinksin past behaviorallowsustodefine “best practice” for future behavior. It also implies that there must be a right or ideal way of doing things. The assumption of rational choice: that faced with a choicebetween oneormore alternatives,humanac- Copyright 2003 by International Business Machines Corpora- tion. Copying in printed form for private use is permitted with- outpaymentofroyaltyprovidedthat(1)eachreproductionisdone  without alteration and (2) the Journal reference and IBM copy- right notice are included on the first page. The title and abstract, but no other portions, of this paper may be copied or distributed royalty free without further permission by computer-based and other information-service systems. Permission to republish any other portion of this paper must be obtained from the Editor. KURTZ AND SNOWDEN 0018-8670/03/$5.00 © 2003 IBM IBM SYSTEMS JOURNAL, VOL 42, NO 3, 2003 462

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Page 1: The new dynamics of strategy: Sense-making in a complex and complicated world

8/3/2019 The new dynamics of strategy: Sense-making in a complex and complicated world

http://slidepdf.com/reader/full/the-new-dynamics-of-strategy-sense-making-in-a-complex-and-complicated-world 1/22

The new dynamics of

strategy: Sense-makingin a complex and

complicated world

by C. F. Kurtz

D. 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 changeandcommunitydynamics,thenexpanded into product development, market cre-ation and branding, and in recent years have been working 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 Project Agency) 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 the

universality 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 “best

practice” 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-

Copyright 2003 by International Business Machines Corpora-tion. Copying in printed form for private use is permitted with-outpayment of royaltyprovidedthat (1)each reproduction is done without alteration and (2) the Journal reference and IBM copy-right notice are included on the first page. The title and abstract,but no other portions, of this paper may be copied or distributedroyalty free without further permission by computer-based andother information-service systems. Permission to republish anyother portion of this paper must be obtained from the Editor.

KURTZ AND SNOWDEN 0018-8670/03/$5.00 © 2003 IBM IBM SYSTEMS JOURNAL, VOL 42, NO 3, 2003462

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tors will make a “rational” decision based only on

minimizing painor maximizing pleasure; and, in con-sequence, their individual andcollective 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” weseeisa “ wink,” and act accordingly.We accept that we do things by accident, but assumethat others do things deliberately.

This paper contendsthat 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 of Tiamat, the mother of all things. In Tiamat’s world,“none bore a name, andno 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 fi xed.He ordained the year and into sections he divided

it;For the twelve months he fi xed 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 “fi xed,” “ordained,” “divided,” “de-termined,” “err,” and “astray.” Control (in the first

four terms) and an absolute knowledge of right and

 wrong (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 andmalcontents suchas Bacchus, Loki, Coyote, the Monkey King, Anansi,and Hermes. The forces of order and chaos danced with each other throughout ancient times.

Science, order, and epiphenomena. Aristotle de-fined four types of cause: the material (what you aremade of, your musclesand organs), theef ficient (how you came to be, the fact that your parents gave birthto you), the formal (your type, your species), and thefinal (yourfunction, 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 ef ficient 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 andextendedover many disciplines. For example, sociology grewout of philosophy partly in an attempt to create a“science of society” thatcould 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 similarto those of physics whichcouldexplain thebehaviorof people in societies. Thegrowth of technology and the dominance of engi-neering-based approaches arising from the need for

automation 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 Trilogy 4

builds on the character of Hari Seldon, the founderof psychohistory, whose mathematics permits theprediction of human behaviorand 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

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ordered; it was just a matter of time and resources

before the relationships between cause and effectcould be discovered. 6 The case study approach of many 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 forordercan even lead people to accept completely ab-horrent working conditions and political structuressimply to avoid “chaos” (a tendency exploitedby dic-tators from Pisistratus to Hitler and beyond). All of these approaches andperceptions do not accept thatthere are situations in which the lack of order is nota matter of poorinvestigation, inadequate resources,or lack of understanding, but is a priori the case—and not necessarily a bad thing, either.

Complexity science. A newawareness of theancientcounterpart 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 of many entities. Emergent order has been found inmanynaturalphenomena: bird-flocking behavior canbe simulated on a computer through three simple

rules 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 of emergent 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 dif ficult 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). Ourgroup has

been 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 of research 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 theemergenceof 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 peopleand knowledge. Thereare at least threeimportant contextual differencesbetween human or-ganizations and those of ant colonies that make itmore dif ficult 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 human

complex 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 andgroup be-havior is explained by the concept of “norms.” 24 Butidentity goes deeper than norms—it determines notonly reactions but perceptions and patternings of experience. A second solution is to model groups asagents, but much internal diversity and patterningis suppressed in this approach. It also makesassump-tions about intent and predictability that are dif fi-cult to sustain. The third solution to the unit-of-anal- ysis problem is to consider theruleor idea or “meme”as the unit of analysis, 25 but again we find that in-suf ficient 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 encompass

multiple dynamic individual and collective identitiesacting simultaneously and representing all aspectsof perception, decision-making, and action.

 Humans are not limited to acting in accordance with

  predetermined rules. We are able to impose struc-ture on our interactions (or disrupt it) as a result of collective 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 Itisdif ficult 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 of previously unambiguous messages, the deliberatecreation of ambiguity, inadvertent disclosure, cha-risma, cults, and pathologies) within a rule-basedsimulation. Social simulations have addressedissuessuch as cooperation, reputation, gossip, lying, andtrust,26 but always within an artificial framework which 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 represent

a 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 ispossiblethat a middle ground between the belief that

all human behavior can be simulated and the belief 

that 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 onecircle of influence foreach 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 of locally aware agents.

We call our practice of keeping the human contextforemost in our considerations phenomenological ormore commonly “contextual complexity.” It means

mainly that whenwe use agent-based simulation(and we do, in certain circumstances), we use it as a toolfor the exploration of possibility and generation of ideas, not as a tool for recommending courses of ac-tion.

Order and un-order. To avoid much repetition of thelongerterms“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 own way. Here we deliberately use the prefi x “un-” notin its standard sense as “opposite of ” but in the less

common sense of conveying a paradox, connotingtwo things that are different butin 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 prefi x 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 of human existence. . . .” Thus by our use of the term

 We are capable of shifting

a system from complexity

to order and maintaining it therein such a way that

it becomes predictable.

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“un-order,” we challenge the assumption that any

order 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” andwould 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 andun-order intertwine and interact. Kostof 32

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 inef ficient bureaucracy is an ef ficient 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 mightlike thingsto 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 applying

methods designed for orderand 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 played war 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 andconstantlychanging environment, it is possible to pattern un-order but not to assume order.

In another case, a group of West Point graduates were asked to manage the playtime of a kindergar-tenasa 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 are very clever, they seed the space so that the patternsthey want are more likely to emerge.

In the ordered domain we focuson ef ficiencybecausethe nature of systems is such that they are amenableto reductionist approaches to problem solving; the whole 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 thenature 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-

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thing we actively, not passively, create, as Mary Dou-

glas36

so well pointed out:

. . . whateverwe perceive is organizedintopatternsfor 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 this

 well. 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? Theskinheadmust 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 of money, as the man conforms to the stereotype of a 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 of money, 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 and when to stand still. A choice must be made betweenallowing the entrained patterns of past experienceto facilitatefast 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 af filiations, the sense that we

all, individually and collectively, have many roots,cultural, religious, geographic, tribal, and so forth.We can never be fully aware of the nature of thoseaf filiations, 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 both with 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

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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 of oldways of thinkingand to considerintractable 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 are

often 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 of such 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 framework

has fi ve 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 and

space in chains that are dif ficult 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 confused with complexity theory.18 In the knowable domain,experiment, expert opinion, fact-finding, and scenar-io-planning are appropriate. This is the domain of 

methodology, 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 accordance with 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 retrospectand do not repeat

Pattern management

Perspective filters

Complex adaptive systems

Probe-Sense-Respond

CHAOS

No cause and effectrelationships perceivable

Stability-focusedintervention

Enactment tools

Crisis management

 Act-Sense-Respond

KNOWN

Cause and effect relationsrepeatable, perceivableand predictable

Legitimate best practice

Standard operatingprocedures

Process reengineering

Sense-Categorize-Respond

KNOWABLE

Cause and effectseparated over timeand space

 Analytical/ Reductionist

Scenario planning

Systems thinking

Sense- Analyze-Respond

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can lead to a false conclusion that is dif ficult 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 collectiveiden-tity is of interest at the time. If I look up my orga-nization’s policy on travel to Iceland, I may not know what 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 phenomenon

 retrospective 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 mayin-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 itself disrupt the patterns). Thus, relying on expert opin-ions based on historically stable patterns of mean-ing will insuf ficiently prepare us to recognize and actupon unexpected patterns.

The decision model in this space is to create probes

to 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 those we 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 are

particularly 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 of ability, one that is uncannily mysterious, sometimeseven to its owner. Canny people tend to succeed intheir own lifetimes; uncanny people tend to be rec-ognized andappreciated only centurieslater, because

during 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 multiple

interventions 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 makerslooking 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 contexttheyare considering, but disagree on more subtle differ-

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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 capabilitiesand 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) and what 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 of those states. We are currentlyengaged 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 of order, 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, andemergent 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,STRONGDISTRIBUTED

CHAOS

WEAK CENTRAL,WEAKDISTRIBUTED

KNOWABLE

STRONG CENTRAL,STRONGDISTRIBUTED

KNOWN

STRONG CENTRAL,WEAKDISTRIBUTED

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they destroy flexibility and also capitalizes on the

freedom and renewal afforded by weak connections without 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 fi ve domains andwhat 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 the whole space of the framework. For example, groupsmight use the Cynefin framework to gain newinsightson 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 entrainedabstract 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 diverse ways, andby 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 allows

patterns of experience rather than opinion or belief to 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 of the 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-rectlyfrom 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. Forexample,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 or without preparatory material) is the use of alterna-tive histories. In this method, we ask people to de-scribethe 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

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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) withfictional timelines

to 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 withtheir assembled sense-makingitems, per-haps derived from multiple processes, and discussesthe extremes (not the domains) of the Cynefin space.They consider the corner where everyone knows the

right answer, the corner where an expert could beexpected to know the right answer, the corner wherethe situationonly 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-tinctionsmeaningful 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 also

be used to negotiate meaning between contexts, butthat use is beyond the scope of this paper.)

 After the extreme situations are considered, all of the 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 fourcorners, 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 wallsand hexagonal stickynotes; it canbe 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 af finity diagrams, in which people are asked to refrain from speaking.42

In our experience, although the proponents of af-finity diagrams are correct that silence equalizes the verbal contributionsof those who speak up andthose who hold back, the placement of items is not equal-

ized by silence: often people just watch very care-fully what the bossis 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-peciallyfor tacklingdif ficult management issues. An-other significant element of the placement of itemsis that, as in the group construction of af finity dia-grams, we encourage people to consider all items to-gether and to keep moving any items they like until

the patterns they have produced make sense.

When all the items are placed, as shown in Figure3B, lines are drawn between hexagons thatare 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

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 At this point, the characteristics of each domain and

boundary—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 are

consideringand about their purpose, goals, and iden-tity. For example, one group completed their Cyne-fin framework and reviewed it. They had done al-ternative historiesto 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’twe?” Theparticipant meant that they hadonlybeen willing to consider wholly chaotic situations when they had been forced to add accidents to thelist.

This increased awareness (reflected in many other

such 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 language with which the members of the decision-makinggroup can discuss situations, perspectives and pos-sible actions. This newlanguage is unique to the con-cerns of the groupand abstract enough to cover manyparticulars,but resonant with meaning so thatit 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 havecreatedtheir owncontextualized frameworks canusethem as artifacts for negotiation of common mean-ing. For example, if one group placed “theinfluenceof the Internet on globalization” in complex space

and 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 theCynefin framework to support people mak-ing decisions and crafting strategies. As part of the work we are doing for public-sector and private-sec-tor bodies, including the government, we are design-

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ing computer software that uses the Cynefin frame-

 work as a sense-making mechanism in tandem withmassive narrative databases of world historyand 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 several years, 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 recent

papers,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 arepossibly 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 how you look at it, any gradient can be a boundary andany boundary can be a gradient, so there is always

room 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 of  what 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 byanyone at any

place, and thus control over crossing is dif ficult 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 of boundary. 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 when you 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 canbe built, demolished, andcontrolled at will.It isnot easyto tellwhen 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 thesite. 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 that you have crossed the boundary until it is too late and you 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 know

 where you will come out. (Those fans of certain sci-ence fiction programs will recognize this type of boundary in transportation devices, which offer theenticing possibility of putting yousomewhere youhadnot 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, of course, times when a high-plateau boundary is just what you need: to confuse an adversary, to promoteinnovation (in limited circumstances), or to disruptold patterns that have become limiting.

Boundaries are possibly the

most important elements,

in sense-making, because they

represent differences among

or transitions between the

patterns we create in the

  world that we perceive.

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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 spacesby 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 levelsof 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 adversary while 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 andpersonalities, seem to ben-efit from different uses of boundaries. People whoare used to classifying items into categories benefitfrom removing boundaries, as takes place in thestan-dard contextualization exercise described earlier.However, people who are used to thinking in a morefluidway—about gradients rather thanboundaries—seem to benefit more by constructing boundariesthan by removing them.

For example, when the workshop is large enough or when we feel that it is required, we often hold a par-allel session of contextualization in which people are

asked 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 a

stronger 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 and where 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 dynamicsWhen 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, oneof thefunctions of theCynefin 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 if treated 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

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

The final stage before the break point is witnessed

frequently in history. A good example is the trial of Galileo, in which the Catholic Church accepted thatthe earth went round the sun for the purpose of mathematic 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 withbehavior longafter its utility, perceivedfrom a different perspective, is exhausted (Boisot 44

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 thefact that those models are outdated, andthey will 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 situationis so catastrophicthat people accept what would have previously been

unacceptable as theprice of order. Theproblem with

this 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-orderis involved in most scientific work (forexample, hunches, analogies, networks, local prac-tices, and shared beliefs). This boundary is fluid andpermits much traf fic as people go about the businessof building technologiesandpursuing lines of inquiry.

  Incremental improvement (Item 3 in Figure 4) is

movement 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 of choice. 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

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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. One

study of actual practice in IBM Global Services 34 in-dicated some 50 – 60 of ficial 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 just

cited, the 50– 60of ficial communities areable 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 maintainingstock 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 back

to 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 dif ficult to delineate. In nature, sys-tems move back and forth across this boundary of-ten. In that sense, traf fic 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 dif ficult to cross,but a vertical transition across the more permeableboundary between chaos andcomplexity 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 thatrelies on local knowledge only, thanto shout out “come towards the back of the theatre,”an ordered trigger that relies on global knowledge which 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 movements within 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.

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 Divergence-convergence (Item 7 in Figure 4) is amovement from the complexto the chaotic andback,repeatedly. The active disruption of a complex sys-tem to precipitate its move to chaos is less of a change

than 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 askedto 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 of patterns 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 commonapproachto disrupt the entrained thinking of experts who, in ourexperience, tend to be themost 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 can

be used to create and validate newsources andstruc-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 pointwhere 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

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For an organization, sharing strategies involve a pro-

cess of letting go, of creating freedom within heu-ristic boundaries to allow newpatterns andnew lead-ership to emerge. One of the techniques we use inthis area is Social Network Stimulation,39 which aimsto stimulate the interactions of agents(orrather 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 dif ficult. This isone of the most threat-ening of transitionsto entrenched managers, butoneof 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 the

great 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 lonely woman’s lifeto 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-nizationbecause 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, usinganthropological techniques

developed 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 sciencefiction and fantasywrit-ers. Members of the organization then seek to col-onize the planet in a managed war game. They facetheir ownorganization 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 known

to be forgottenandrequire seeking; newgenerationsfilledwithcuriosity begin new explorations thatques-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 andnarrative is about change. We mayask people to consider a situation in the past and what 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

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 As we said at the beginning, these assumptions are

 valid 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 briefl y 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 cansafely assume that pat-terns will form, unpredictable in their details butusually recognizable in their basic forms, and that with practice we can learn to detect these formingpatterns, stabilize or disruptthemdepending 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—that we 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 areef ficient 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 interventionsto encourage desirable

behavior 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 fromIndia 52 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 perspectiveof hisaudience, whoare operating in the space where things are boundby tradition and thus known, he appears to be act-ingchaotically, becausethey canconceive 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 andother 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 on

perspective. It means asking not, “What did they havein mind when they did that?” but, “What does itmean thatthis 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 letters were winks but of different actors (Khruschev andthe Politburo, respectively). The different authors of the letters probably saw their actions from the com-plex space of the Cynefin framework because theyunderstood the internal politics that produced them.

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To Kennedy, however, receipt of the two letters

plunged him into chaotic space, where he could con-ceive of no sensible intention to send such contra-dictory letters—to confuse, perhaps, or to delaywhilethe missiles were being prepared. It was only afterscrutiny by linguists that the Kennedy administra-tion was able to understand that the intentions be-hindthe 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 of a 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, both

in 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 ef ficiencyand effectiveness. Human groupsneed to be effective; machines and structured hu-man interactions (such as manufacturing processesor the application of rules of engagement) need tobe ef ficient.

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 Accepted for publication April 24, 2003

Cynthia F. Kurtz IBM Global Services LotusDevelopment, 1 Rog- ers St., Cambridge, MA 02142 ([email protected]). Ms. Kurtz isPrincipal Researcherfor IBM’s Cynefin Centrefor organizational

complexity. Shereceivedher B.S. degreein biology from ClarionUniversity of Pennsylvania in 1986 and her M.A. degree in ecol-ogyand evolutionfromthe State Universityof New York at StonyBrook in 1990 (after completing fi ve years of Ph.D.-level grad-uate work studying theevolution andcomplexity of socialbehav-ior). From 1992 to 1998 she co-owned a small software business,and is the co-creator of two internationally distributed and widelyreferencedenvironmental education simulatorson plantgrowth,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-rativein organizations,including thecreationof an XMLschemafor describing stories and storytelling contexts. She moved to theInstitute for Knowledge Management in 2001 to work on bothnarrative programs and complexity programs beforehelping foundthe Cynefin Centre in 2002. She is currently leading work on the

use 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 thedirectorof 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 andan M.B.A.degreefrom MiddlesexUniversity 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 Cynefin

Centre 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.