the knowledge management puzzle: human and social factors...

The knowledgemanagement puzzle:Human and socialfactors in knowledgemanagement

by J. C. ThomasW. A. KelloggT. Erickson

Knowledge management is often seen as aproblem of capturing, organizing, and retrievinginformation, evoking notions of data mining, textclustering, databases, and documents. Webelieve that this view is too simple. Knowledge isinextricably bound up with human cognition, andthe management of knowledge occurs within anintricately structured social context. We arguethat it is essential for those designing knowledgemanagement systems to consider the human andsocial factors at play in the production and useof knowledge. We review work—ranging frombasic research to applied techniques—thatemphasizes cognitive and social factors inknowledge management. We then describe twoapproaches to designing socially informedknowledge management systems, socialcomputing and knowledge socialization.

Knowledge management (KM)—also known un-der rubrics such as organizational learning, or-

ganizational memory, and expertise management—has received increasing attention over the lastdecade. Indeed, it is fair to say that knowledge man-agement is well on the way to becoming a distinctfield, with its own theories, jargon, practices, tools,skills, and other accoutrements of an independentdiscipline. This paper is motivated by our concernthat the codification of knowledge management isproceeding a little too rapidly, and that we may endup with a conception of knowledge management thatis too neat and too simple to survive in the wilds ofthe workplace.

The dominant conception of knowledge manage-ment—particularly that which has spread beyond thecircle of researchers and practitioners into the mar-

ketplace—is overly tidy. Knowledge management isseen primarily as a problem of capturing, organiz-ing, and retrieving information, evoking notions ofdatabases, documents, query languages, and datamining. Knowledge is seen as passive, analytic, andatomistic: it is composed of facts that can be stored,retrieved, and disseminated, with little concern forthe context in which the facts were originally em-bedded, and little concern for the new and often quitedifferent contexts in which they will be used. In thisview, as one widespread advertisement recentlyclaimed, knowledge management is nothing morethan getting the right information to the right peo-ple at the right time.

This is a nice picture, but one with which we are notcomfortable. Whereas there is no denying the im-portance of factual knowledge and the usefulness ofinformation technologies, we believe that there aremany other issues that are of critical import. Ourgoal, therefore, is to bring forward a set of results—ranging from basic research findings to practical tech-niques—that we believe to be very relevant to knowl-edge management, even as they are at risk of beingleft out of the KM picture. Overall, our strategy inthis paper is to back away from a coherent pictureof knowledge management. We suggest that it ismore valuable to see knowledge management as apuzzle, especially if we focus on the puzzle pieces:our basic approach will be to add a number of new

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pieces to the puzzle, and to demonstrate that somevery different pictures of KM can be assembled fromthe richer, if less ordered, set.

In the next section, “Missing pieces: Cognitive andsocial research and techniques,” we begin by survey-ing the conceptual landscape that informs our workin knowledge management. This involves lookingclosely at some of the human and social factors thatare involved in the creation and communication ofknowledge. We discuss both research areas and ap-plied techniques that, we believe, have received in-sufficient attention in knowledge management. Wedo not attempt to provide a single, unified frame-work for knowledge management, an endeavor thatwe see as premature; rather, our goal is to broadenthe reader’s view of what is important and relevantfor KM. In the following section, “New pictures: So-cially informed knowledge management systems,” inlieu of offering a unified KM framework, we describetwo distinct projects that, each in its own way, drawupon some of the previously described research andtechniques to develop socially grounded approachesto knowledge management.

Missing pieces: Cognitive and socialresearch and techniques

One of the reasons we are dissatisfied with the dom-inant picture of knowledge management is that itpays little attention to human and social factors. Inour view, knowledge is bound up with human cog-nition, and it is created, used, and disseminated inways that are inextricably entwined with the socialmilieu. Therefore, we argue that knowledge man-agement systems must take both human and socialfactors into account. In this section we describe anumber of the research findings and applied tech-niques that motivate our work. We believe that thesepieces are vital parts of any picture of knowledgemanagement. At the same time, we acknowledge thatthere are undoubtedly other missing pieces to theKM puzzle, and that many distinct, but still valid, pic-tures of KM are possible.

The missing pieces we discuss are quite diverse. Theyare drawn from a variety of areas ranging from thecognitive and social sciences, to domain-focused dis-ciplines such as social studies of science and com-puter-supported cooperative work. These pieces re-veal the complexity and some of the subtletiesunderlying the mantra of “the right information tothe right people at the right time.” To show this moreclearly and to provide a bit of structure in what fol-

lows, we discuss our pieces in terms of knowledge(“the right information”), presentation and commu-nication of that knowledge (“. . . to . . . at the righttime”), and social context (“the right people”). Fol-lowing that, we turn to applied techniques that arerelevant to these areas.

Knowledge and intelligence. Until fairly recently, theprevailing view of science held that the world was,in principle, knowable and predictable; that the uni-verse, including human beings, consisted of essen-tially complex but analytically decomposable ma-chines.1,2 A common metaphor for knowledge, stillquite common in Western society, is that it consistsof separate little “beads” or factoids,3 and that theseknowledge “atoms” can be collected, stored, andpassed along. Views like this are what underlie thenotion that an important part of knowledge man-agement is getting access to the “right knowledge.”Although, obviously, it is important to find knowl-edge that is relevant to whatever problem is at hand,there is quite a lot of research that paints a consid-erably more complex picture of knowledge.

To begin with, let us take a look at some findingsfrom research in the area of human intelligence. Out-growths from the endeavor to test “intelligence” overthe last century have led to an understanding thatthere are different types of intelligence that work pri-marily on different forms of knowledge. Althoughthere are variants on this theme, the most popularrecent work, as well as one having a sound empiricalbase, is probably that of Sternberg.4,5 Perhaps themost ambitious and elegant theoretical frameworkwas developed by Guilford,6 who built a three-di-mensional model of mental processes. In this work,there were differently sized Products of mental op-erations: Units, Classes, Relations, Systems, Trans-formations, and Implications. There were differentOperations (processes) that could be performed:Cognition, Memory, Divergent Thinking, Conver-gent Thinking, and Evaluation. Finally, there weredifferent types of Content: Figural, Symbolic, Seman-tic, and Behavioral. While this system has largelyfallen out of favor as a basis for testing intelligence,it is an interesting framework for KM developers toconsider. All too often knowledge management sys-tems are designed with an implicit, unquestioned,and unacknowledged limitation on the varieties ofknowledge that are supported.

The field of intelligence testing is relevant to knowl-edge management in yet another way. Early devel-opers of intelligence testing failed to recognize the

THOMAS, KELLOGG, AND ERICKSON IBM SYSTEMS JOURNAL, VOL 40, NO 4, 2001864

extent to which their tests were measuring, not in-nate capability, but essentially the degree to whichsomeone had acquired socially sanctioned knowl-edge. Test developers struggled to develop “culture-free” IQ (intelligence quotient) tests and by and largefailed in the attempt, realizing at last that what con-stitutes intelligence is primarily determined by cul-ture. Perhaps the most telling example in this regardcomes not from the field of intelligence testing perse, but from the work of Tom Evans,7 an AI (arti-ficial intelligence) student of Marvin Minksy, whobuilt a program to solve figure analogies of the form“A is to B as C is to [D1, D2, D3, D4, or D5].” Evans’sprogram worked—too well. It could parse the fig-ures, construct rule components, and find a com-posed rule that made every answer correct! Fully halfthe work of the dissertation was essentially to gethis program to have the same ordering of “elegance”of rules that was socially agreed upon by the test mak-ers. As one example, the authors of the tests thoughtit more “elegant” to rotate a figure in the plane ofthe paper as opposed to out into three-dimensionalspace. In other words, even knowledge that couldeasily be thought of as factual or mathematical is infact strongly shaped by social and cultural assump-tions.

If even factual knowledge is not quite as objectiveas we might expect, it is not surprising to find thatother forms of knowledge are even more subjective.For example, one important early debate in psychol-ogy centered on introspectionism versus empiricism.This debate arose in part due to inconsistencies insubjects’ self-reports of experiences of perceptionand consciousness. At the time, the scientific com-munity reacted by declaring that only objectively ob-servable phenomena should be used in building areliable understanding of mental processes; today,in the wake of the failure of the behaviorist project,there is greater openness toward subjective formsof knowledge. Although it is clear that some kind of“self-knowledge” is essential for people to behaveintelligently (e.g., without knowledge of the limitsand capacities of our bodies we might continuallybe running into things), individuals differ on how suchknowledge is best viewed.

In addition, research has shown that there are a num-ber of important cases in which a person’s self-knowl-edge is inaccurate. In the “fundamental attributionfallacy” literature, studies show that the behavior ofan individual is highly influenced by context, and yetpeople give explanations for their behavior based ontheir own internal values. For example, bystander

studies consistently show that people are much morelikely to help a person in distress if they are alonerather than if they are with a large group, and yet,when asked whether they would respond differentlydepending on how many others are present, peopleclaim that it would make no difference.8 This hasimportant implications for modern knowledge man-agement practices. Not only are people very muchinfluenced by the social context, they may believethat they are not so influenced, when they in fact are.Although some have pointed out that the produc-tivity of both teams9 and large organizations10,11 ispervasively influenced by social context, we believethe impact is often underestimated, not only by sub-jects in social psychology experiments but also in ev-eryday business decisions about knowledge manage-ment.

Communication and learning. If knowledge is notso simple as our ways of talking about it assume, nei-ther is the process of communicating it to others. AsBrown and Duguid12,13 note:

The idea of a document as a carrier is an exampleof what Michael Reddy calls a “conduit” meta-phor. People regularly describe most communi-cation technologies in conduit terms, talking of in-formation as “in” books, files, or databases as ifit could just as easily be “out” of them. We askor are asked to put ideas “down on paper,” to“send them along,” and so forth.

However, there is quite a lot of research that sug-gests that it is not just a matter of getting the rightknowledge to people—people need to engage withit and learn it. One of us has argued that a more re-alistic and useful model of communication is a“design-interpretation” model. In this model, thespeaker uses knowledge about the context and thelistener to design a communication that, when pre-sented to and interpreted by the listener, will havesome desired effect.14 In the “design-interpretation”model, a knowledge worker would be viewed in anactive, constructionist role, consistent with a widevariety of empirical results.

There is quite a lot of research that is relevant tothis view. Theorists as disparate as Dewey,15 Vy-gotsky,16 and Piaget and Inhelder17 have consistentlyshown that the mere presentation of informationdoes not necessarily result in learning. People haveto become actively involved for behavior to change,for insight to occur, for problems to be solved. Vy-gotsky stressed that this learning and insight had a

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significant social component, even if the resultingknowledge was of a type we might classify as math-ematical or scientific. Yet, all too often, large orga-nizations come to believe that simply making moreinformation available more widely will “solve” knowl-edge management problems. By way of contrast,

within IBM much of the management training is donevia scenario-based training. In this technique, the in-dividual is asked to make choices in realistically por-trayed situations such as ones that managers face.These scenarios are based on an analysis of real sit-uations, and assume that when the individual makesa “mistake” in the simulator or is “surprised” by aresult, it motivates the person to read and under-stand the rationale.18 In the use of such simulators,even if the individual learner is sitting alone in frontof a computer console, learning is very much influ-enced by social context. It is the social context of thescenario that provides much of the motivation andinterest as well as guidance on what constitutes a“right answer.”

In addition to arranging interactions so that peopleactively engage with knowledge, there are other con-siderations from earlier work that are applicable toknowledge management systems. We know, for ex-ample, that people are better able to both distinguishand remember knowledge that is encoded on mul-tiple dimensions.19 However, in contrast to the va-riety of sensory cues that naturally occur in real-world“paper” systems, many current generation systemsprovide little in the way of differentiating cues. Giventhe processing power and memory of today’s com-puters, it would be quite feasible instead to providesensory “signatures” that are unique to various items.“Folders,” for instance, could easily be portrayed notonly in different colors, but also by different sizes andtextures. Indeed, small musical animations couldeven hint at the structure or content of a folder orits date of last access. Of course, a challenge in con-vincing organizations to adopt sensory-rich ap-proaches to laying out a knowledge space is that per-

formance improvements may only be observableafter extended usage.

A large number of indicators point toward the re-ality of an information-processing world movingtoward greater fidelity and multimodality. Over thelast four decades, user interfaces have evolved fromlights and toggle switches to keyboards, mice, icons,and speech I/O. In the entertainment industry, wenow see computer-generated full-length movies.Video games strive toward greater responsiveness,more modes of experience, and more detailed im-ages. Research laboratories continue to push theboundaries of multimodal I/O, including virtual re-ality and augmented reality,20,21 auditory icons,22 ki-netic typography,23 and so on. Yet, in a business con-text, knowledge management writings and practiceoften seem to focus on the content of systems whileignoring the method of presentation. Beyond con-siderations of cost, there sometimes seems to be al-most a puritanical business-culture ethic towardavoiding presentations that stimulate the senses andutilize the complete human brain.

Social context. Although it is difficult to argue thatknowledge management should not be concernedwith getting information to the “right people,” ourcommon definition of KM provides little insight intowhich people are the right people. Here we turn toa body of work—drawn primarily from the social sci-ences and domain-oriented disciplines like Comput-er-Supported Cooperative Work (CSCW)—that pro-vides some interesting views on the social contexts(both with and without technology) within whichknowledge work occurs, and the social factors thatseem to be important in supporting knowledge work.

In the field of Computer-Supported CooperativeWork, researchers have often made careful exam-inations of how people within organizations conducttheir work. One point that these studies make is thatknowledge work is not a solitary occupation, nor isit sufficient to say that knowledge work involves manypeople. Rather, in case after case, it becomes clearthat knowledge work involves communication amongloosely structured networks and communities of peo-ple, and that understanding it involves identifyingthe social practices and relationships that are oper-ative in a particular context. One of the best-knownconcepts to emerge from such studies is Lave andWenger’s notion of a community of practice. A com-munity of practice is defined by common tasks, meth-ods, goals, or approaches among a group of people.Lave and Wenger show how new workers come to

It is becoming clear that knowledgework is not a solitary occupation,

but it involves communicationamong loosely structured networks

and communities of people.


master a body of knowledge through a sort of ap-prenticeship or “legitimate peripheral participation”in the activities of a group of experienced workers.24

Wenger25 provides a detailed study of an insuranceclaims processing office, and shows the vital roles thatsocial relationships and processes play in enablingpeople to meet productivity targets while adheringto corporate policies. Orr’s26 study of photocopiertechnicians reveals that technical knowledge is so-cially distributed across a network of technicians, andthat it is tapped into and disseminated through oralprocesses such as storytelling.

Similarly, in reviewing ten years of field and labo-ratory studies of collocated and remote work, Ol-son and Olson27 point to a variety of social factorsthat affect the social context of knowledge manage-ment, and how these interact with technologies in-tended to support remote collaboration. In an in-teresting discussion of the role of common ground28

among collaborators, for example, the Olsons de-scribe how greater shared background and aware-ness of a coworker’s activities and mental state con-tribute to establishing and maintaining commonground. The Olsons also discuss the role of moti-vation in successful knowledge sharing:

Motivation has been established as one of the ma-jor sources of failure in adoption of groupware ingeneral. In Orlikowski’s classic study of the fail-ure to adopt Lotus Notes** in a consultancy, thefailure was attributed to the fact that individualswere compensated according to their competitivetalents.29 There was no incentive to share one’sbest ideas if they were then going to be seen ascommon, no longer unique. In other organizations,where incentives are aligned with how much oth-ers use the knowledge you make available to them,Notes and other jointly authored groupware sys-tems succeed.27

Churchill and Bly’s30 study of the use of a MUD (akind of text-based conversation environment) amonga group of scientists at Argonne National Labora-tory points to other social factors supporting knowl-edge sharing and collaboration:

As Huxor31 points out, however, “chance” encoun-ters do not occur entirely by chance. Social tiesand physical layout can have an effect on who con-tacts whom and how often. Hillier32 emphasizesthe effect of work environment design (whethervirtual or physical) on the establishment and main-tenance of “weak ties.” These are contacts that

one normally would not make through one’s cen-tral work practices. Arguably these “weak ties”have a strong role to play within an organization’sfunctioning. In this vein, the MUD provides a setof virtual places wherein one can “bump into” oth-ers or people can be actively sought. Our inter-viewees stressed the importance of such plannedand unplanned encounters.

Thus, we see that talking about knowledge manage-ment as though it involves delivery of informationto a person, or to a set of people, is missing quitea lot. Looking at the individual is, by and large, look-ing at the wrong level of granularity; instead, we needto shift our focus to the social context. That is, mostof the phenomena that have been identified as im-portant—relationships, awareness, common ground,incentives, and motivation—are network or socialphenomena. In the same way, the other “missingpieces” we discussed earlier are also characterizedby a shift in granularity: rather than knowledge asisolated, context-free facts that could be “in” doc-uments or databases, and straightforwardly trans-ferred into people’s heads, we see that knowledgeis bound up with human intelligence, shaped by so-cial assumptions, and requires active engagement onthe part of recipients if it is to be taken up. All ofthese findings, although just a small sampling of whatis contained in the HCI (human-computer interface)and CSCW literatures, demonstrate the pervasivenessof human and social factors in the realm of knowl-edge management.

Practical techniques for creating and communicat-ing knowledge. As practitioners of knowledge man-agement we have a repertoire of techniques that arealigned with the research we have discussed thus far.And, as designers of systems for managing knowl-edge, we have conducted a number of explorationson how to provide technological support for someof these techniques. Here we describe the most gen-erally useful techniques, and we examine the waysinformation technology (IT) could support them. Tobegin with, we turn to an area that, in our view, hasreceived remarkably little attention: the creation ofnew knowledge. The lack of attention may be be-cause Western culture has a long tradition of treat-ing creativity as tantamount to magic. Nevertheless,there is now a large body of scientific literature deal-ing with such issues as creativity, problem solving,and design (see Shneiderman33 for a nice review).While the state of the science and art is not at thepoint where we can duplicate the accomplishmentsof a Shakespeare or Einstein on demand, we can craft


technological and methodological support to in-crease the creation of new knowledge, both by in-dividuals and by groups. Tools can be designed tohelp with various processes in the creation of newknowledge. We examine several examples of creativeprocesses that could be feasibly supported by tech-nology including: dialog,34 the use of metaphors,35

the use of strategies,36 and the use of stories.37

Bohm Dialogue. In a Bohm Dialogue,38 a group ofpeople work together to build new knowledge. Thisprocess differs from a typical business meeting in sev-eral ways. First, continued inquiry is balanced withstriving for an answer. We know from studies of hu-man problem solving that people’s natural tendency(at least in American culture) is to jump on the firstformulation of a problem and try to solve it, ratherthan exploring alternative formulations. Second, thedialog is noncompetitive. People ask questions andmake observations but are asked to “suspend” theirthoughts; that is, not to own or push for their spe-cific idea to be adopted by the group as the correctone. Third, the actual conversation is not bound byan analytic agenda that deals with pieces of a prob-lem one by one. Rather, a “container” binds the con-versation; that is, there is some focus to the conver-sation—it does not wander aimlessly over any topic—but everything said is related to the overall systemthat the group is attempting to understand. Fourth,the rhythm of the Bohm Dialogue is different fromthe typical meeting, in which everyone begins men-tally critiquing the speaker and rehearsing a counter-argument before the speaker is even finished speak-ing. Instead, one person speaks and others listen.After listening, everyone reflects on what was justsaid before someone else speaks. Bohm, a physicist,likened this “cooler” pace to superconductivity.Whether we accept such a metaphor or not, someremarkable breakthroughs have come from using theBohm Dialogue.38

Tools have been developed to support Bohm Dia-logue, in face-to-face settings as well as in remotecollaborations. Fischer and his colleagues at the Uni-versity of Colorado have built a collaboration spacethat includes both a horizontal, computerized actionspace—where collaborators literally design and build“in the center”—and a large-screen, large-scale re-flection space39 where material designed to help par-ticipants reflect on their activity is displayed. It is clearthat for Bohm Dialogue to work as a process, how-ever, both formal organizational mechanisms and in-formal cultural aspects of a situation must lend them-selves to the process. If people are operating in a

highly competitive culture in which there are higherintrinsic and extrinsic rewards for having their ownidea adopted rather than for, as a group, reachinga breakthrough, dialog will just be seen as a slow,inefficient way to run a meeting. Similarly, in orderto be effective, the participants will probably needto have at least some minimal familiarity with sys-tems thinking; otherwise, there will be little moti-vation to attempt to understand the whole ratherthan attack the parts piecemeal.

Systematic use of metaphor. Another creative processthat can be supported with information technologyis the systematic use of metaphor, as suggested byGordon,35 Mattimore,40 and others. Earlier re-search41 described a technique for improving per-formance in problem solving and design tasks. In oneexperiment, a group of subjects spent an hour cre-ating a design for converting an abandoned churchinto a restaurant. Another group spent 20 minutesdesigning, 20 minutes looking at a word list designedto evoke concepts from a wide range of domains, andanother 20 minutes designing. The latter group pro-duced designs that fulfilled significantly more of thefunctions of a restaurant. In another experiment, sub-jects given an arbitrary word list exhibited more in-sightful solutions to problems, despite constant timeon task. These results suggest that word lists specif-ically crafted to evoke different metaphors in themind of a problem solver can aid open-ended de-sign and problem-solving tasks, and that such met-aphor techniques could be extended and improvedwith today’s interactive software. Preliminary ex-plorations of what such tools might be like can befound in the demonstration prototypes available atwww.research.ibm.com/knowsoc/.

How such a tool might work is illustrated in the fol-lowing fictitious scenario.

Joe is stuck. He has what he thinks is a great ideafor making the next version of the ThinkPad* eas-ier to use. But he is getting nowhere with the proj-ect manager who refuses to consider hardwarechanges at this late date. He logs on to the au-tomated metaphor tool and engages in a struc-tured interaction that encourages him to breakdown the elements of his problem, rearrange them,make his implicit assumptions explicit, and play“what-if” games with some of these assumptions.He gets a “funny” feeling when he turns the def-initions of hardware and software upside down,but still has no solution. However, later that day,as he is driving home, he realizes that what he


wanted to include in modified hardware could alsobe provided as software. Fulfillment would nothave to be done through the PC division, per se,but could be downloaded via the company Website or sent as a CD in response to a call to an 800number. As a result, PC sales increase dramaticallyonce word gets out that IBM has a very easy-to-use system.

Strategy mapping. Recent work at IBM Research hasfocused on developing a comprehensive compen-dium of strategies for enhancing creativity andknowledge creation. Although there have alwaysbeen books about strategies for problem solving inparticular domains (e.g., war, diplomacy, chess, bus-iness), we believe that people within a particular com-munity of practice often develop a common set ofstrategies that are then taken more or less for grantedwithin that community. There may be strategies,however, from a totally different domain that mightbe successfully applied, if only the practitioners knewabout the existence of these strategies. Gordon36 hascollected strategies from a large number of dispar-ate domains and developed an abstract planning lan-guage in which all the strategies can be described.Since it is generative, the abstract planning languagemight be used to articulate potentially novel strat-egies as well as to help practitioners in one domainfind unusual strategies from some other domain.

For example, in traditional “Western” medicine,germs have been considered the “enemy” and strat-egies of care for someone who has an infection typ-ically have involved attacking and killing these en-emies. However, other strategies might includeboosting and supporting the body’s own immune sys-tem, altering the characteristics of the germs so thatthey become harmless, “leading them out” of thebody by providing a more hospitable environmentelsewhere, altering the germs so they attack eachother, coating the germs so they can no longer affectthe body, etc. Our conjecture is that providing al-ternative strategies from other domains might en-able doctors to engage in breakthrough thinking. Infact, various drug companies are considering the useof alternative strategies to facilitate innovative think-ing.

Stories and storytelling. Stories and storytelling pro-vide another possible way to foster creativity in in-dividuals and groups, and they also provide avaluable way of presenting and communicatingknowledge. In some cases, particular stories can il-lustrate a specific point. One fairly common yet dif-

ficult point to make in teaching the concepts of sys-tems thinking is the kind of mutual impact thatpeople have on each other. For example, a market-ing department may feel that the engineering depart-ment is unresponsive and takes too long to makechanges. To counter this, the marketing departmentmay develop a whole suite of requirements and askfor them earlier than is actually necessary, hopingto “speed up” development so that enough featureswill be provided for a timely, competitive product.Of course, such behavior makes the engineering de-partment feel less like being responsive to market-ing. Breaking out of such “vicious circles” is diffi-cult. Direct communication can often backfire underthese circumstances, because it can trigger defensive-ness and defensive countermoves. An alternative sug-gested here is to provide a story to both groups aboutanother situation in which the same principles ap-ply. Snowden42,43 reports several business cases inwhich the use of various types of stories has helpedto produce breakthroughs.

Finding appropriate stories for the situation at hand,however, is nontrivial. In our laboratory, we are de-veloping tools to help. In one such tool, Gordon44

describes a “script-based browser” that allows a userto find stories based on the type of activity they con-tain. This approach has been applied to a very largestory collection called the “American Heritage Proj-ect”—stories commissioned in the 1930s by theWorks Progress Administration, many of which areavailable on line. As work progresses on the abstractplanning strategy language described previously, thebrowser can be used to find stories about analogousactivities as well.

In some cases there are other characteristics of astory that may be important in selection. Our lab-oratory has begun developing a Story Markup Lan-guage for describing the various aspects of a story.We plan to develop software for either adding meta-data to stories automatically or helping a user do itin a straightforward fashion. Such meta-data mightbe used to search for specific kinds of stories or couldbe used as the basis for visualizations of the set ofstories that users can quickly scan to find likely can-didates.

The Story Markup Language not only deals with theinternal content of the story but also with the socialcontext. Storytelling is fundamentally social: in ev-eryday events, people tell stories to specific otherpeople (who are usually physically present) in par-ticular social contexts (at dinner, in a meeting, etc.).


Social factors influence who tells what stories towhom and when. In designing effective ways to col-lect and provide access to stories, we think it is im-portant to attend to some of the basic social dynam-ics that affect everyday storytelling, such as reasons

for telling stories, the teller’s knowledge of the au-dience, and the role the audience takes in the tell-ing.

As one example of how the social context of story-telling can influence its teaching effectiveness, wemust recall that, in a business context, the audienceof a story does not simply “take in” the story. In thecase of fictional stories (e.g., stories told in an en-tertainment context), readers and listeners will “buy”the story as long as it is internally consistent. But inthe context of using stories to foster change in thereal world, the audience must not only see the storyas internally consistent, but also as consistent withexternal reality. An elaboration of such social fac-tors in storytelling and their implications can befound in Lawrence and Thomas.45

Expressive communication. Communication is cen-tral to any complex, modern organization. We findit useful to draw a distinction between what we mightcall instrumental versus expressive communication.Instrumental communication is that which is neces-sary for accomplishing tasks related to the immedi-ate organizational goals. It is typically supported byspecific forms and media, for example, job offers, req-uisitions, ratings, invoices, RFPs (requests for propos-als), contracts, formal award certificates, and so on.Such communications are typically created in well-defined formats (e.g., forms), delivered in specificcontexts, and need to include specific information.In contrast, expressive communication is communi-cation in which individuals or teams are primarilymotivated by personal or social aims such as sharingexperiences, indicating agreement, being humorous,etc. Expressive communication often occurs in in-formal settings including hallway conversations,

informal meetings, stories, notes scrawled on con-gratulatory cards or napkins, and e-mail about non-business issues.

Organizations clearly rely on instrumental commu-nications, but the role of expressive communicationsis less clearly understood, with perceived value vary-ing from irrelevant, to disruptive, to vital to theaccomplishment of work. Recently some have arguedthat such communications are important in support-ing innovative thinking46 and the building of socialcapital11 within organizations. In any case, it is clearthat the effective use of expressive communicationwithin organizations requires certain conditions, e.g.,appropriate social and cultural norms. Technologycan enhance the use of expressive communication.One idea is to simply modify existing forms to in-clude a field for comments and contact informationfor an ombudsman, a person responsible for solvingproblems associated with a mismatch between theassumptions of the built systems and the workdayrealities. Providing a place for such commentary andthe ensuing conversation could be vital for support-ing the instrumentality of the system.

An instructive real-world example is provided byHarris and Henderson.47 In a shipping firm, paperforms were being replaced with a more “efficient”computer system. In one case, a shipment was to bedelivered to a boat. In the paper version, in the fieldmarked “Ship to Address,” a worker wrote “Call Mr.X at number Y to see where the ship will be at timeof delivery.” Entering the same data in the computerversion yielded an error message. The worker wouldthen enter a bogus, but syntactically correct addressin the computer form. As a result of many such er-rors, the workers ended up using the computerizedsystem and the old paper system.

A two-fold approach can be taken for the preven-tion of such absurdities. First, as a general princi-ple, knowledge systems should provide for expres-sive communication. This will result in fewer errorsand more effective operations; it will also enhancesocial capital. Second, systems should be designedwith an understanding of how work is actually done,and not how IT developers think the work is done.Processes for developing such understanding can befound, for example, in Beyer and Holtzblatt.48

Expressive communication as a means of building trust.In Arie De Geus’s49 classic study on the longevityof large organizations, he found that mutual trustwas a strong characteristic of long-lived organiza-

Expressive communication iscommunication in which individuals

or teams are primarily motivated bypersonal or social aims such as

sharing experiences, indicatingagreement, or being humorous.


tions. In Robert Putnam’s50 study of various regionsand local governments in postwar Italy, he also foundthat mutual trust, facilitated by various informalgroups, clubs, and associations, was an excellent pre-dictor of future economic growth. Instrumental com-munication may inform about a person’s competenceand reassure us that the person follows the organi-zational rules. Character, however, is revealed bychoices under pressure.51,52 In a well-structured or-ganization, instrumental communication minimizeschoice; hence, it is difficult to learn about someonefrom purely instrumental communication. On theother hand, if a person tells a story about him or her-self, has a social conversation, or participates in cre-ative design sessions, he or she will inevitably revealsomething personal. Over time, we learn somethingabout another person and may come to trust them.In fact, there is some evidence that people preferpeople who use more expressive means of commu-nication, even in organizational settings.53 This maybe one reason why effective leaders turn to story.54,55

The importance of mutual trust in coworkers maynot be evident if people in an organization are allfollowing a procedure that works. However, in timesof change or breakdown, mutual trust will allow col-laborative effort to proceed toward organizational(as opposed to individualistic, locally optimized)goals. Looked at another way, what expressive com-munications allow people to do is build up a morecomplete and complex model of others so that therewill be a basis for behavioral prediction in novel sit-uations requiring conjoint but not prechoreographedaction.

Of course, while stories and other forms of expres-sive communication have the capability of buildingmutual trust, they also have the capability of reduc-ing mutual trust. As mentioned above, stories in anentertainment context create their own frame. Butstories told in the context of an organization will notsimply be “accepted”; they will be viewed against thebackdrop of the current context and if the story toldis too discrepant from actual behavior, one result willbe less trust, not more.37

Expressive communication is not a sufficient condi-tion to build mutual trust; however, it may be nec-essary. Hence, the design of knowledge managementsystems would do well to support expressive com-munications as well as instrumental ones if they areto help organizations thrive in times of change andadversity. Some recent designs seem to be movingin this direction.37,56

Conversation. We conclude our review of practicaltechniques for supporting a socially informed ap-proach to knowledge management by turning to atechnique that is so common as to go unremarked:conversation.

We view conversation as essential. We use it as amedium for decision-making. It is through conver-sation that we create, develop, validate, and shareknowledge. When systems—automated or bureau-cratic—freeze, or simply prove too rigid, we pick upthe phone to figure out appropriate “workarounds.”And with all our advances in information retrieval,the preferred method for obtaining information isstill to ask a colleague.

Why is this? We suggest that conversation has twocharacteristics that are central to its power and ubiq-uity. One vital characteristic of talk is that it is adeeply interactive intellectual process (see Clark28

for a detailed exposition). As we talk we refer to acommon ground of already established understand-ings, shared experiences, and past history. As the con-versation proceeds, we are continuously attemptingto interpret what is said, verify that we have beenunderstood, and offer new contributions. Sometimesmisunderstandings occur, and so we attempt to fixthem by rephrasing our words, or “debugging” theprevious conversation to reveal that what we thoughtwere shared understandings were not, in fact, shared.What all this amounts to is that conversation is a su-perb method for eliciting, unpacking, articulating,applying, and recontextualizing knowledge.

Conversation is more than simply an intellectual en-deavor: it is a fundamentally social process.57–59 Con-versation is social in two ways. First, people speakto an audience. Speakers notice how their audienceis reacting and steer their remarks appropriately:nods and eye contact convey one message; questionsand furrowed brows another; yawns and fidgeting stillanother. Second, conversation is social in that peo-ple portray themselves through conversation. Theyadvance their personal agendas, project their per-sonal style, take credit, share blame, and accomplishother social ends through their talk, often with a greatdeal of subtlety. The social nature of talk is not anundesirable side effect, but rather the heart of it: per-sonal motivations fuel conversation and provide theenergy for the considerable intellectual work it takes,whether the conversation in question is banter overmorning coffee or discussing the composition of ajournal paper.


In addition, conversation within the digital medium,has a property of great importance for our purpos-es: it can persist. Instantiated as text, whether typedin or spoken and recognized, persistence expandsconversation beyond those within earshot, render-ing it accessible to those in other places and at latertimes. Thus, digital conversation may be synchronousor asynchronous, and its audience intimate or vast.Its persistence opens the door to a variety of newuses and practices: persistent conversations may besearched, browsed, replayed, annotated, visualized,restructured, and recontextualized, with what arelikely to be profound impacts on personal, social, andinstitutional practices.

Summary. This concludes our review of an array ofresearch findings and practical techniques that haveto do with the cognitive and social factors that comeinto play in the creation and communication ofknowledge. We hasten to note that we do not claimthis review is, in any sense, comprehensive. We havefocused on pieces of the knowledge managementpuzzle that, while missing from many accounts, haveinformed our own explorations. We have no reasonto believe that we have somehow, through eithergood luck or cleverness, uncovered all the missingpieces. In our view, even as it condenses into a co-herent discipline, it is important to recognize thatour understanding of the critical factors in manag-ing knowledge is in its infancy.

New pictures: Socially informed knowledgemanagement systems

So what are we to make of all this? We have out-lined several new pieces to the knowledge manage-ment puzzle—but how do these new pieces fit withthe old ones and provide a new and seamless pic-ture of knowledge management? As we noted in theintroduction, we think such a goal is premature, andthat the field would be better served by a multiplic-ity of partial models and a commitment to exploremultiple perspectives. In line with this view, ratherthan trying to present a unified framework, we offertwo examples from our own work that suggest howall the pieces might start to come together in a so-cially informed approach to knowledge managementsystems.

The first example, a system called “Babble,” comesfrom an area known as social computing.56 Socialcomputing has to do with digital systems that drawupon social information and context to enhance theactivity and performance of people, organizations,

and systems. Instances of social computing systemsinclude recommender programs (e.g., for movies ormusic), “wearware” (i.e., showing signs of “wear” orhistory in a digital system, such as how heavily tra-versed a Web link is), social navigation,60 and socialawareness indicators (e.g., visualizations of peopleand their behavior, buddy lists). Babble is an on-linemultiuser environment that is intended to supportthe creation, explication, and sharing of knowledgethrough text-based conversation. The basic rationaleunderlying Babble is described first, and the systemand usage experience with Babble follow.

The second example, knowledge socialization, de-scribes a constellation of projects around the use ofstories and storytelling in business settings. The ra-tionale for knowledge socialization is described first,showing how stories can facilitate knowledge cre-ation, sharing, and reuse. Following this, we describean integrated suite of story-related tools that sup-ports these ends.

The rationale for Babble: Visibility yields awarenessyields accountability. Imagine a knowledge manage-ment system that was designed from a social perspec-tive, a system predicated on the assumption thatknowledge is rooted in a social context. Such a sys-tem would assume that knowledge is producedwithin, and dispersed among, a network of people;that only a small proportion of knowledge is capturedin concrete form; that knowledge sharing involvessocial factors like relationships, trust, obligation, andreputation. One way in which a system might instan-tiate such assumptions is not just by providing ac-cess to data and documents, but also by intercon-necting the social network of people who producedthe knowledge.

Imagine further that we include not just the peoplewho produce the knowledge, but those who use itas well. Suppose that—just as we look for crowdedrestaurants, eye fellow shoppers, or look for engag-ing conversations—we could see similar traces ofthose making use of information in a knowledgemanagement system. After all, some of the knowl-edge users might have to invest considerable effortin order to apply the knowledge to their own ends,developing an understanding of its shortcomings andparticularities, as well as building on it. If we couldcapture traces of this knowledge work, others withsimilar needs might find as much value in talking withusers of this knowledge as with the original authors.Such a system would not be just a database fromwhich workers retrieved knowledge, it would be a


focus for a knowledge community, a place withinwhich people could discover, use, and manipulateknowledge, and encounter and interact with otherswho are doing likewise.61

How might we do this? One way in which this mightbe achieved is in the context of an on-line computer-supported communication environment. Thus wemight imagine a computer-based system that not onlyallows records and documents to be stored, but al-lows people to converse with one another and to havesome visible presence. Such a system would not justmake people and knowledge visible, but it wouldmake interactions among them visible. That is, itshould be possible to see people interacting with ex-plicitly expressed knowledge (e.g., reading), and itshould be possible to see people conversing with oneanother (both as a means of explicating tacit knowl-edge and as a means of building and maintaining thesocial factors such as trust and relationships that areimportant in knowledge management).

For the last four years our research has been focusedon ways of making such interactions visible in on-line environments. We have developed the notionof socially translucent systems46 to guide us in de-signing such environments. By social translucencewe mean systems that provide perceptually based in-formation about the presence and activity of users,thus creating social resources that the group as wellas individuals can use to structure and enhance theiron-line interactions. When such information is madevisible to all participants, people become aware ofone another’s presence and activity, allowing socialconventions and other social dynamics to come intoplay. With mutual awareness comes accountabilityfor one’s actions (e.g., if “I know that you know thatI know” of your presence and activity, my activitywill be interpreted with respect to that knowledge;that is, I will be held accountable for my actions).By invoking social translucence as a framework, weare attempting to make people and their behaviormore prominent, enabling the creation, exercise, andmutual observation of social behavior. By so doing,we aim to create a basis for more coherent, produc-tive, and fluid interactions on line. Socially translu-cent systems make it easier for users to interact inpurposeful, coherent ways; to observe and imitateothers’ actions; to engage in peer pressure; to cre-ate, notice, and conform to social conventions. Wesee social translucence as a fundamental requirementfor supporting most types of communication and col-laboration in digital spaces.

Babble: An infrastructure for a knowledge commu-nity. Babble is an on-line, digital space in whichknowledge can be created, discovered, shared, andreused.56 One of the principal means for fulfillingthese core knowledge management processes in Bab-ble is its support for blended expressive and instru-mental communication through informal conversa-tion. Babble is therefore particularly concerned withsupporting long-running, contextual interactions (asopposed to short-term, task-focused activities). Itvery deliberately blends work and social talk, syn-chronous and asynchronous interactions, and privateand public discourse. The aim is to provide a digitalsubstrate upon which knowledge communities cangrow, and where “discourse bases,” rather than da-tabases, can provide a medium for people to develop,share, and reuse experiences and knowledge, andwatch others do the same.

The Babble system. Babble resembles a multichan-nel, text-based chat system to which many users canconnect, and either select from a list of conversa-tions to participate in, or create their own. Babblediffers, however, from conventional chat in two ways,both of which stem from our goal of creating a so-cially translucent system that supports knowledgemanagement. First, the textual conversation that oc-curs in Babble is persistent: that is, unlike conven-tional chat where newly arriving users see only whathas transpired since they have joined a channel, Bab-ble users can see everything entered in any existingconversation. These traces give the system the po-tential to function as a knowledge store, or what weprefer to call a “discourse base.” Second, Babblemakes the presence and activity of the participantsvisible through a variety of means, but principallythrough what we call a social proxy.

Figure 1 shows the Babble user interface. The up-per left pane contains a list of the names of userscurrently connected to Babble. The middle upperpane contains the social proxy, which we describeshortly. The upper right pane displays a hierarchi-cal list of the conversation topics, grouped in cat-egories and subcategories. The pane that occupiesthe lower half of the window contains the text of thecurrent conversation, whose topic name is high-lighted in the topics list; within the pane, each com-ment is prefaced with the name of the user, and thedate and time of its creation. Babble conversationsneed not be synchronous; indeed, some are asynchro-nous, with hours, days, or weeks separating com-ments. A variety of other functions may be invokedvia the menu bar, or through context-sensitive menus


accessed via right clicks, and keyboard shortcuts.These include functions for creating messages, cre-ating, changing, and deleting topics and categories,conducting private, ephemeral chats, and so forth.

The social proxy, also known as the cookie, in theupper middle pane, represents the current conver-sation as a large circle, and the participants as col-ored dots, also known as marbles. Marbles withinthe circle are involved in the conversation beingviewed; marbles outside the circle represent thosewho are logged on but are viewing other conversa-tions. What makes the social proxy interesting hasto do with the position of the marbles in the circle.When a user becomes active, either “speaking” (i.e.,typing) or “listening” (i.e., interacting with the con-versation window by clicking or scrolling), the us-er’s marble moves rapidly to the center ring of the

circle. If the user stops interacting, the marble grad-ually drifts to the inner periphery of the circle overthe course of about 20 minutes. Thus, when thereis a lot of activity in the conversation, there is a tightcluster of marbles around the center of the circle.The social proxy shown in Figure 1 depicts a situ-ation in which three people have been recently ac-tive (i.e., speaking or listening) in the current con-versation, and one other has been idle for a while(and a fifth person is off in the “Grapevine” topic).

When people leave the current conversation theirmarbles move to the outside of the circle’s periph-ery (as with the marble at “eleven o’clock”); whenthey enter the conversation, their marbles move in-side the circle. When a person logs onto the system,a virtual wedge is created for the person’s marble,

Figure 1 The Babble interface

CURRENT CONVERSATION


adjusting the position of all the marbles in the socialproxy; when the person departs, the wedge is de-stroyed, and the remaining marbles adjust to uni-formly occupy the space. All marble movements areshown with animation, thus making arrivals, move-ments, and departures visually salient. Although sim-ple in concept, this social proxy gives a sense of thesize of the audience and the degree to which the au-dience is actively listening or contributing, indicateswhether people are gathering or dispersing, and whois coming or going.

In addition to the social proxy, Babble uses additionalmechanisms to reveal the presence and activity ofusers. In the topic list, to the left of the topic names,are “minicookies,” thumbnails of the social proxy foreach topic with at least one participant in it. So, inFigure 1, we can see that there is a single person in

the third topic, “Grapevine.” Babble also highlightsinformation that the user has not yet seen: the namesof topics and categories with new material in themare shown in red (e.g., Grapevine and B_Ethnog-raphies), and within the conversation pane, com-ments that have been added since the user last“touched” Babble have their authors’ names in red.

The cookie shows only synchronous interactions—that is, it shows only the presence and activities ofpeople who are currently logged on to Babble. Thismay be a drawback because often the majority of theconversations carried on in Babble are asynchronous,with just a few comments per day (or per week, orper month). As a consequence, we designed a sec-ond, asynchronous social proxy, the timeline,62 illus-trated in Figure 2.

Figure 2 The timeline


The basic goal of the timeline is to provide a way fora “speaker” to see that people were “listening” (ornot), even when the listening was offset in time. Eachuser logged on to Babble is represented by a row.When the user “speaks,” a vertical mark or blip ap-pears on the line. If the line/blip is in color, it meansthe user was active in the conversation currently be-ing viewed by the user of the timeline; otherwise theline/blip is shown in gray (and the line is thinner).As the user moves the mouse over the timeline, thename of the topic, the user, and the time being ex-amined are shown in the upper left corner of the win-dow; the user can scroll back through as much asone week of activity. Other functions of the timelinemay be invoked by right-clicking on another user’srow (e.g., private chats).

The timeline in Figure 2 covers about half a day’sworth of activity. We can see that over the courseof the afternoon about 20 people have logged ontoBabble (shown by the number of rows), most of themhave spent some time in the current conversation(shown by the color/increased thickness of the lines),and many, but not all, have “spoken” (shown by theblips). Gaps in the line indicate intervals when theperson logged off. In the center of the timeline, aflurry of concentrated activity can be seen. This rep-resents an on-line brainstorming session that tookplace in midafternoon, involving a majority of thepeople who logged onto Babble that day. Since thisview of the timeline is from the Commons Area, wecan see that the brainstorming session started outwith people arriving and “hanging out” (i.e., not nec-essarily saying very much) in the Commons Area (asshown by the multiple colored lines), followed by alot of interaction in topics that the group created formore focused brainstorming by subgroups (as shownby the colored lines changing to gray as people switchto the focused topics). Note that this synchronoususe of Babble occurred in conjunction with a con-ference call (not shown in the timeline visualization),so the lack of activity in the Commons Area may havebeen due to the simultaneous conference call, fol-lowed by a flurry of brainstorming activity in spe-cific topics just after the phone call ended. After thesynchronous interaction, the timeline shows “listen-ers” entering the various topics and spending timethere. We can infer that these visitors are readingthrough conversations they may have missed.

The timeline thus can reveal that others in the knowl-edge community have been paying attention to con-versations (i.e., listening), even if they do not posta comment (i.e., speak). Although user interviews

we have conducted suggest that the timeline is notroutinely used by most Babble users, it has been usedby more sophisticated users, for example, the hostsof on-line group interaction, to get a sense of howwell the group is functioning and who is participat-ing over time.62 This portrayal of on-line participa-tion that includes both speakers and listeners ismeant to increase the amount of social feedbackavailable in the environment.

Usage experiences with Babble. Having described thebasic Babble functionality, we now turn to describ-ing some of our experiences in using Babble our-selves, and in watching others use Babble. While onemust be wary about drawing conclusions concern-ing the usability of software when its developers useit, our aim here is to simply provide a sense for howBabble is actually used by a group and to give someexamples of how Babble functions as a knowledgecommunity.

Our group has used Babble for the almost four yearsof its existence. The group consists of a software de-velopment group that designed and implemented thesystem and includes a mix of computer scientists andsocial scientists (including the authors). The size ofthe group has varied in number over the years fromfour to nineteen users. The variance is due in partto the ebb and flow of people characteristic of groupsin large organizations, and in part to current mem-bers inviting “associates”—colleagues with whomthey had strong social or professional ties—to join.

Over the last several years we have deployed Bab-ble to a number of other work groups: about 15groups within IBM and one group formed by a uni-versity class outside IBM. We have studied the de-ployments in a variety of ways, ranging from detailedethnographic studies—see Reference 63 for a studyof six IBM Babble groups—to studies based on sur-veys and analysis of log data and conversation ar-chives.64

We have had mixed experiences with the adoptionof Babble. If we consider a Babble deployment suc-cessful when it is used more or less daily, by severalpeople, for more than six weeks, then we can say thatabout half of our Babble deployments have met withsuccess. Currently we have eight Babble groups run-ning, not including our own. Five of these havepassed the six-week mark (some are far past it), withfour showing continued robust daily activity, and onein decline. In one of the recent deployments we haveseen Babble support a time-limited, specific group


exercise—a month-long, global brainstorming exer-cise (the source of the data in Figure 2).

It is evident that when Babble catches on in a group,it supports a variety of communication purposes andpractices, often similar to those we have observedin our own usage. Here we describe three social phe-nomena that are most relevant to the knowledgecommunity vision.

One social practice we have observed is “waylaying,”in which a user watches for a particular person tobecome active on Babble (signaled by the movementof their marble into the center of the social proxy),and then initiates a conversation by greeting the per-son in a public conversation, via private chat, tele-phone, or other means. Because the movement ofthe marble occurs when the user has just begun in-teracting with the system, it indicates an opportunemoment for contact (since the user’s attention hasjust shifted to communication with the group). Way-laying is used for purposes ranging from asking ques-tions to initiating casual social chat.

Babble also supports group awareness through thepersistence of its conversation. For example, whenmembers of a Babble group travel, many report read-ing through conversations that occurred in their ab-sence to “find out what happened.” For someonewho is a member of the group and understands thecontext, seemingly trivial comments can convey con-siderable information about what is going on at theindividual, group, and organizational levels. Thus,a sign off—“I have to go to the [project] meetingnow”—reveals that one participant is still involvedin a particular project, and a question—“Does any-one know how to do a screen capture”—indicatesthat another participant is beginning to write a pa-per.

In addition to the persistence of conversation, Bab-ble also supports group awareness through the time-line proxy. Babble participants have reported usessuch as: looking to see who has visited a topic in whichthey had posted questions; looking to see whethera colleague who had not posted recently had beenon line; and using the timeline to get a sense for theactivity of the community as a whole. One user wrote:“It’s a little like reading an electrocardiogram, theheartbeat of the community. I noticed that I missed[Susan] by an hour on Monday morning . . . . [Daph-ney] comes in every so often as a blip. [Frasier] jumpsfrom space to space . . . .”

Another phenomenon that can be observed in Bab-ble is the development of social norms. That is, oneparticipant may develop a particular way of doingsomething, and others will imitate it. Examples ofthis include what users include in their on-line nick-

name (e.g., in some Babble groups, users append“@mylocation” after their name), the types of on-line conversations created (e.g., some Babble groupshave categories for “personal places” or “offices”),and naming conventions (e.g., one Babble group usesthe term “chitchat” to signal that a topic is intendedfor casual conversation. Babble groups also evolvevarious interactive customs, the most common be-ing to say “hello” upon logging in (even when no oneelse is present).

Waylay, group awareness, and the development ofsocial norms are examples of the effect of social trans-lucence: they are made possible by the mutual vis-ibility and awareness of Babble participants and theiractivity. These social practices help to forge an iden-tity for the group and allow individuals to becomemore fully dimensional as communicative partners:that is, they emerge not just as disembodied wordson the screen, but as real people who might be likedor disliked, trusted or treated with caution, with rep-utations that can grow or be tarnished, and so forth.The fact that these effects emerge from long-run-ning, day-to-day, work-related interactions in Bab-ble is also important. As Cohen and Prusak65 state,“Social capital is mainly created and strengthened(and sometimes damaged) in the context of realwork. The conditions and durable connections thatwe experience day after day have vastly more influ-ence on it than special events and team-building ex-ercises.”

In our experience, Babble provides an environmentwhere social capital can be built. The following com-ments were drawn from a Babble group whose mem-bership is composed of a worldwide cross-section ofpeople in IBM and Lotus interested in on-line com-munities. In this group, participant comments indi-cate that the social interaction that occurs within theenvironment is valuable. Several of the participants

Babble provides an environmentwhere social capital

can be built.


see the lightweight conversation that is possible inBabble as important in building social capital. Oneparticipant points to the role of ongoing, chat-likeconversations in establishing what Clark and Bren-nan66 have referred to as common ground:

[Lightweight conversations] can have more valuethan is immediately apparent. This (rather than withtechnical discussions) is often where personalities areexposed. That can make a big difference over timein feeling comfortable about asking for or offeringopinions and help. Rapid exchanges often make allthe difference in building mutual understanding.

Another participant feels that informal interactionhelps to build trust among remote collaborators:

In today’s world . . . you’d want threaded discussions. . . and also have a chat space that would providefor real-time dialog, not necessarily staying on a par-ticular topic, but a way to build trust, establish deeperrelationships, a way to complement what you’re try-ing to address over in the threaded dialog space. It’sneeded in the widely distributed, no-travel, matrixmanaged environment that we have today.

Finally, another participant describes a deepeningof relationships with colleagues through the daily in-teractions on Babble:

Babble has helped me establish a tighter social andprofessional relationship with all of them—we havemuch more regular contact with each other, muchas we would if we were collocated, via the Babbleconnection. This in turn has built social capitalamong us which may be of use in the future.

These remarks confirm that the informal interactionin Babble, and the blend of social and work talk, con-tribute to the formation and maintenance of a so-cial fabric that underlies collaboration with distantcolleagues. Through our work on Babble, we havebegun to create an infrastructure that can supportrich forms of social interaction. We have found thatsocial proxies are a promising development, and wecontinue to be impressed with the power of plain textas a means of supporting interactions that are bothcomplex and subtle. We believe that one of the mostimportant aspects of a knowledge community is thatit can be used as a place for unguarded discussionamong people who know one another, who shareprofessional interests, and who understand the con-texts within which their remarks are being made.

We now turn to our second example of a socially in-formed approach to knowledge management.

Knowledge socialization: Using stories to supportknowledge creation, sharing, and reuse. We chosethe term “knowledge socialization” to describe ourwork for several reasons. First, as discussed earlier,knowledge is heavily influenced by social and cul-tural factors: it is entwined, on the one hand, withhuman cognition, and, on the other, with the socialcontext of teams, organizations, and communities.Second, the term “knowledge socialization” is meantto stand in contrast to the many approaches to knowl-edge management that take a particular technologyor family of technologies as a starting point. Third,it connotes a holistic growth of knowledge througha complex, emergent system of richly interconnectedprocesses (somewhat akin, metaphorically, to thegrowth of a snow crystal). In contrast, we believe theproduction line metaphor67 of knowledge being cre-ated, then captured, then disseminated and then in-ternalized can be quite misleading as an overallscheme for knowledge management. While somemethods and technologies may legitimately focus onproviding support for one of these processes, ourwork has focused on stories and storytelling as anexemplary holistic knowledge socialization process.We claim that storytelling is useful in creating, cap-turing, disseminating, and internalizing knowledgeand that it accomplishes all of these simultaneously,not sequentially. Storytelling is also a representativeknowledge socialization process in that it typicallyincludes both instrumental and expressive aspects.In this section, we expand on the role of storytellingas a process that can be used throughout an orga-nization and report on some preliminary tools to sup-port storytelling. We end by claiming that an under-standing of story as a knowledge socialization processis necessary for a deeper understanding of the so-cial aspects of knowledge regardless of whetherknowledge is explicitly presented as story.

There are many uses of story and storytelling in bus-iness. Stories can be useful ways for a business tofind out about the needs of its customers in a deeperway. Stories can also help advertise a product or ser-vice; they help in showing the proper context for theuse of a product or service and allow us to see thebenefits. Stories can be used as educational mate-rials within a company. Stories can be used as a toolin the design process.68,69 Informally, colocated com-munities of practice may spontaneously share expe-riences in the form of oral stories.26 Wider, more dis-tributed communities of practice may share stories


in electronic forms; e.g., stories, as well as other kindsof knowledge, were shared successfully via theIBM VM (virtual machine) forums. Even more for-mally, stories may be collected and arranged into sce-nario-based learning systems.18 Stories can be usedto help establish or change corporate culture. Sce-narios, a variant of stories, can be used to help or-ganize the design process and keep it focused on realcustomer needs. Scenarios can be used for strategicplanning. Scenarios can also be a useful way for teammembers from different functions to see how theycan relate to solve a problem.

As instantiations of a type of knowledge that can beused in so many business processes, stories also havethe advantage that they can help knowledge flowthrough the organization. Not only are stories ca-pable of being used by many different business func-tions (marketing, design, management), they are alsocapable of being understood by various professions.Thus, stories can serve not only to support commu-nities of practice with a common vocabulary; theycan also serve an important coordinating role withina team whose members come from different com-munities of practice. A story might start with a cus-tomer expressing a need, be used as a scenario dur-ing design of a service to meet that need, and thenbe included as part of a marketing campaign to showhow that need can be met. A different story mightencapsulate the experiences of a consultant to thepetrochemical industry. This story might seem to of-fer a lesson learned that is at odds with the expe-riences of another consultant. By comparing the sto-ries and examining the apparent contradiction, thetwo consultants themselves (or even a third party)could find the differentiating factors between the twosituations and, in effect, use the story combinationto create new knowledge.

Although stories have the capability of serving as akind of cognitive glue across the many functions andlevels of a large organization, there is no guaranteethat they will do so. Either the formal organizationor the corporate culture may introduce roadblocksof various kinds to the use of stories. Perhaps theorganization does not reward people for sharing theirexperiences. Or, even if the formal organization putsin explicit rewards for sharing experiences, the in-formal corporate culture may discourage people invarious ways; stories may be seen as a kind of second-class knowledge compared to an algorithm or a for-mula; or stories from the marketing department maybe seen as suspect by people in the engineering de-partment. In the latter case, the potential flow of rich

information about users and their context that couldserve as a competitive differentiator for the companyis blocked; instead people in the engineering depart-ment design products based on their own traditionsor biases.

Even where the organizational and cultural factorsare favorable to the use of stories, however, theremay well be technological barriers. Stories are quitea natural way for small groups of trusted colleaguesto exchange information. Scaling such a process toa large, global organization requires an integratedset of story tools such as we are developing at IBMResearch. Dave Snowden, an IBM colleague work-ing with stories, uses an apt analogy to explain whyit may now be necessary to take storytelling to thenext level. When the modern Olympics began in1896, a natural athlete who trained hard had a goodchance at winning a gold medal. At the end of thiscentury, that is no longer true. Only a good athletewho trains hard and trains scientifically, with expertadvice in nutrition, biomechanics, sports medicine,and other fields has a chance at a gold medal.

In the past, great leaders in business have instinc-tively told stories to help motivate people and to cre-ate an organizational reality. Workers have alsoshared knowledge by telling stories in small, face-to-face groups. But today, we live in a world at oncefaster paced, more competitive, and more global. Sci-ence and technology might now be used to make sto-ries and storytelling more effective, more appropri-ate, more scalable to large organizations.

An integrated suite of story-related tools. In orderto provide a common underpinning for the variousstory-related tools that we have developed, we haveproposed a first pass at a “StoryML,” that is, amarkup language specifically geared toward stories.The initial representation is based on a distillationof many different approaches to story.52,70–80 Our ini-tial formulation has three different but related“views” of story: Story Form (what is in the story);Story Function (what are the purposes of the story);and Story Trace (what is the history of the story).In turn, the Story Form can be broken down intodimensions of environment, character, plot, and nar-rative. The idea of the StoryML is that it is expand-able according to purpose. For some purposes, theuser (e.g., a student studying mystery plots) may besatisfied with minimal detail concerning function andtrace but may need to expand certain aspects of theStory Form in great detail. In another context, a dif-ferent user (e.g., a historian comparing certain


themes across time and cultures) might have a veryhigh-level view of Story Form and Story Functionbut want to see a detailed description of Story Trace.At this point, the meta-data in StoryML must be sup-plied by a knowledgeable human being. However,increasingly, it could become feasible to partially au-tomate this process.

The following scenario illustrates how a StoryMLmight support reasoning about a business process.

Jane is under the gun to cut costs in the fulfill-ment process without increasing delivery time ordecreasing customer satisfaction. In fact, her boss,Betty, has strongly suggested that rethinking thefulfillment process should allow her to decrease de-livery time and increase customer satisfaction.Jane’s knowledge portal is already personalizedto her general profile mostly via a dynamic back-ground process that takes note of what Web sitesshe visits, what the topics of her e-mail are, andwith whom she communicates. She can turn a soft-ware “dial” on any given knowledge scan that de-termines how much the scan will be influenced byher general profile and how much by the specificsearch terms she uses. In this case, Jane wants tosee an overall story frequency map. Since storiesgenerally arise when things do not go as planned,the story “hot spots” show her likely places wherecurrent fulfillment processes are probably ineffi-cient or subject to breakdown. At this point, sheis not very concerned with the structure of the storyor even the function. She is mainly concerned withthe Story Trace. Jane focuses on the two mostlikely trouble areas and sets up two separate story-exchange meetings of people expert in these twoareas.

The story exchange meetings only last an houreach and the stories exchanged are all digitally re-corded with an associated (imperfect) transcript.Although the transcripts are imperfect, they serveadequately to allow her to zoom in accurately onaudio versions of some very telling stories. Theseare referenced throughout the subsequent processre-engineering. Jane quickly assembles anotherteam to explore possible ways to improve the ful-fillment process. In this creative synectics35 ses-sion, along with other techniques, she again ac-cesses a corporate-wide story base, but this time,she is primarily concerned with Story Function.She is looking for stories that help people thinkabout things in new ways and break old thoughthabits. From a host of potentially useful ideas, she

and her team pick out a few high-leverage, quicklyimplementable, and practical ideas to pursue.

In order to concretize these ideas for dissemina-tion and also to double-check on their practical-ity, Jane develops some scenarios for how fulfill-ment will be done under the new process. Beforecommitting further resources, she uses these sce-narios to get feedback from a small but varied setof customers. These customers provide some ad-ditional insights and requirements.

In parallel with the development of an improvedprocess, training materials are produced to explainthe new process as well as the design rationale be-hind it. In this case, a story creation tool (whichincorporates examples and guidelines) focuses onStory Form. The materials make it quite clear howto use the new process and also explain why. Inaddition, related stories are created for market-ing materials stressing to the customers how it iseven more desirable now to do business with Jane’scorporation.

In the scenario above, we showed how stories canbe used in many ways. In each case, however, we weredescribing what might be termed “endogenous sto-ries.” That is, the “complete story” in some sensewas captured and contained in some explicit record.But the potential use of stories extends considerablybeyond “endogenous stories.”

Suppose that Albert Einstein writes an equation suchas “Energy � mass times speed-of-light squared.”This is clearly not a story, per se. It is, after all, anequation. And, yet, in the larger sense, stories em-anate in every direction from this equation. How didEinstein come up with this? How did it lead to theatom bomb? These might be termed “exogenous sto-ries”—stories created around knowledge.

In order to take natural language processing to thenext level, it will be necessary to understand such“exogenous stories.” We will need to understandagents, goals, obstacles, communicative strategies,and intentions. Otherwise, it will not, in general, bepossible to understand the import of even such a sim-ple statement as “Alice left the party early.” Whois making this statement, and to whom? What do theyintend to communicate? Is it truthful or a lie? Onlyby understanding the larger “exogenous story” canwe possibly know the function of this statement. Suchfunctional variations in context can easily project intothe semantic and even the syntactic domain as the


well-known example “Time flies like an arrow” il-lustrates. We cannot parse this sentence nor assignlexical items to all the surface tokens without un-derstanding the exogenous story of which this sen-tence is a part.

Indeed, understanding the “exogenous story” ofwhich individual statements partake, extends beyondwhat is typically termed “natural language process-ing.” Current attempts to incorporate “intelligentagents” into various systems often lead to problems,even in something as simple as automatic spellingand capitalization correction. The reason is essen-tially that the system has no knowledge of the user’scurrent context and intention. Therefore, a partic-ular “correction” offered by an agent may or maynot make any sense in the current context. As an ex-ample, in the immediately preceding sentence, Mi-crosoft Word** caused a menu to pop up over bothinstances of the token “may,” inviting me to substi-tute “May 6, 2001,” which happens to be the currentdate. In order for computer systems to be more thanpassive conduits for human knowledge, we will needto develop knowledge representations that can ac-count for and represent the essential elements of sto-ries in terms of their form, their function, and theirhistory. This is not to say that all knowledge is in theform of story; we claim only that once we understandand can represent story (StoryML is an initial pro-posal in this direction), we will have the concepts nec-essary to produce true knowledge-based systems. Un-til we build such representations, “intelligent agents”will as often constitute an amusing (or frustrating)distraction as a collaborative knowledge partner.Without such representations, so-called knowledge-based systems will not be capable “social actors,” al-though it is possible that they will be temporarily per-ceived as such. Since the social aspects of knowledgemanagement constitute an absolutely critical aspectof the general problem of knowledge management,until we can understand and represent story, we willnot have the tools to build the underlying architec-ture for a knowledge-based system in which humansand computers can effectively collaborate.

Summary and conclusion

The simple picture of knowledge management as get-ting the right information to the right people at theright time is wrong. Knowledge management is notjust a matter of managing information. It is, we haveargued, deeply social in nature, and must be ap-proached by taking human and social factors intoaccount. We have provided some extra pieces for the

knowledge management puzzle and demonstratedhow we have used them in our own work to assem-ble some knowledge management systems that arestrongly shaped by human and social factors. As thefield of knowledge management develops, and morewidespread and varied experience with different ap-proaches to KM is gained, we believe not only thatadditional critical pieces of the KM puzzle will be re-vealed, but that it will become clearer how all thepieces fit together to create a rich picture of socialand intellectual capital within organizations. Cer-tainly, looking toward the future of work, as it be-comes more centered in virtual relationships andspaces both within and across organizations, creat-ing and maintaining knowledge and its social con-text will only become more vital.

We believe that one of the most important aspectsof a knowledge management system is that it be-comes what we have termed a knowledge commu-nity: a place within which people discover, use, andmanipulate knowledge, and can encounter and in-teract with others who are doing likewise.46,61 Wehave talked about two approaches for supportingknowledge communities, namely social computingand knowledge socialization. A fundamental char-acteristic of a knowledge community is that it in-cludes conversation and other forms of narrative, forexample stories, and/or unguarded discussion amongpeople who know one another, who share profes-sional interests, and who understand the contextswithin which their remarks are being made. We haveoutlined a variety of specific techniques that can con-tribute to a realistic and effective approach to knowl-edge management, including supporting new formsof group interaction (e.g., Bohm Dialogue, stories),methods for enhancing creativity (e.g., the use ofmetaphor), and support for expressive communica-tion. When such techniques are incorporated intoknowledge communities, they result in organizationalopportunities to build social capital, including trustand cooperation among colleagues. This notion ofa knowledge management environment as a “trust-ed place” is an interesting and challenging one forsystem designers and for organizations. How—tech-nically, socially, and organizationally—can we bal-ance the need for a safe and trusting place, withinwhich so much knowledge creation and social cap-ital building takes place, with the organizational im-perative to share information more broadly? We be-lieve that a greater understanding of how to designsocially translucent systems that permit social mech-anisms to come into play will help developers of tech-nological systems to negotiate such issues. Similarly,


we believe that understanding better how to social-ize knowledge through techniques such as storytell-ing and scenarios will offer organizations greatermastery and scope in creating, sharing, and reusingthe knowledge that is critical to survival in the twenty-first century.

Acknowledgments

This work is highly collaborative, and we owe a greatdebt to our colleagues, past and present. Thanks inparticular to Andrew Gordon, Christine Halverson,Cynthia Kurtz, Mark Laff, Peter Malkin, TraceeWolf, Mark Ackerman, John Richards, Rachel Bel-lamy, Cal Swart, David N. Smith, Erin Bradner, Ja-son Ellis, Beth Veinott, Jason Elliot, James Reed,James Hudson, Karrie Karahalios, Barbara Kelly,and Brent Hailpern. We also thank three anonymousreviewers for their comments on an earlier versionof this paper.

*Trademark or registered trademark of International BusinessMachines Corporation.

**Trademark or registered trademark of Lotus Development Cor-poration or Microsoft Corporation.

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Accepted for publication August 6, 2001.

John C. Thomas IBM Research Division, Thomas J. Watson Re-search Center, P.O. Box 704, Yorktown Heights, New York 10598(electronic mail: [email protected]). Dr. Thomas (www.truthtable.com) is manager of knowledge socialization at theThomas J. Watson Research Center. He received his Ph.D. degreein experimental psychology in 1971 from the University of Mich-igan. He has worked in a number of areas of human-computerinteraction including speech systems, query systems, natural lan-guage systems, and design problem solving. In 1986, he foundedthe Artificial Intelligence Laboratory at NYNEX where work wascarried out in expert systems, human computer interaction, ma-chine vision, robotics, and computer-aided instruction. Dr. Tho-mas rejoined IBM Research in 1998 to work in the area of knowl-edge management (www.research.ibm.com/knowsoc/).

Wendy A. Kellogg IBM Research Division, Thomas J. Watson Re-search Center, P.O. Box 704, Yorktown Heights, New York 10598(electronic mail: [email protected]). Dr. Kellogg is managerof social computing at the Thomas J. Watson Research Center.Her current work involves designing and studying socially trans-lucent systems for computer-mediated collaboration in groupsand organizations. Dr. Kellogg’s work in human-computer inter-action over the last 15 years has spanned research areas includ-ing HCI theory, evaluation methods, design, and development.She is an author of numerous papers and was coeditor in 2000of a millennial special issue of Human-Computer Interaction en-titled “New Agendas for Human-Computer Interaction.” Dr.Kellogg holds a Ph.D. degree in cognitive psychology from theUniversity of Oregon.

Thomas Erickson IBM Research Division, Thomas J. Watson Re-search Center, P.O. Box 704, Yorktown Heights, New York 10598(electronic mail: [email protected]). Mr. Erickson (http://www.pliant.org/personal/Tom_Erickson) is an interaction designer andresearcher whose approach to systems design is shaped by workin sociology, rhetoric, architecture, and urban design. He has con-tributed to the design of a number of products and authored about40 publications on topics ranging from personal electronic note-books to pattern languages and virtual community. Originallytrained as a cognitive psychologist at the University of Califor-nia, San Diego, he spent five years at a startup company, nineyears at Apple Research, and finally joined IBM in 1997 as a re-search staff member. His primary agenda is studying and design-ing systems that support network mediated group interaction.
