TACIT KNOWLEDGE CAPTURE

ideas, will enable a company to compete more effectively in the future. Com- petitiveness is becoming increasingly dependent on an organization’s agility or ability to respond to changes in a very timely manner. The major component of agility lies in the skills and learning abilities of the knowledge workers within that organization.

Without doubt knowledge capture may be difficult, particularly in the case of tacit knowledge. Tacit knowledge management is the process of capturing the experience and expertise of the individual in an organization and making it available to anyone who needs it. The capture of explicit knowledge is the systematic approach of capturing, organizing, and refining information in a way that makes information easy to find, and facilitates learning and problem solving. Knowledge often remains tacit until someone asks a direct question.

At that point, tacit can become explicit, but unless that information is cap- tured for someone else to use again at a later date, learning, productivity, and innovation are stifled.

Once knowledge is explicit, it should be organized in a structured document that will enable multipurpose use. The best KM tools create knowledge and then leverage it across multiple channels, including phone, e-mail, discussion forums, Internet telephony, and any new channels that come online. A wide variety of techniques may be used to capture and codify knowledge, and many of these techniques have their origins in fields other than knowledge manage- ment (e.g., artificial intelligence, sociology, and instructional design), which are described here.

ing at the stage of intuiting and the process of experimenting at the stage of interpreting.

In KM, this knowledge creation or capture may be done by individuals who work for the organization or a group within that organization, by all members of a community of practice (CoP), or by a dedicated CoP individual. It is really done on a personal level as well, for almost everyone performs some knowl- edge creation, capture, and codification activities in carrying out their job.

Cope (2000) refers to this as PKM (personalized KM). Within the firm, indi- viduals share perceptions and jointly interpret information, events, and expe- riences (Cohen and Levinthal, 1990), and at some point, knowledge acquisition extends beyond the individuals and is coded into corporate memory (Inkpen, 1995; Spender, 1996; Nonaka and Takeuchi, 1995). Unless knowledge is embedded into corporate memory, the firm cannot leverage the knowledge held by individual members of the organization. Organizational knowledge acqui- sition is the “amplification and articulation of individual knowledge at the firm level so that it is internalized into the firm’s knowledge base” (Malhotra, 2000, p. 334). The value of tacit knowledge sharing was discovered in a surprising way at Xerox (Roberts-Witt, 2002), as illustrated later in this chapter.

Many of the tacit knowledge capture techniques described in this chapter derive from techniques that were originally used in artificial intelligence—more specifically, in the development of expert systems. An expert system incorpo- rates know-how gathered from experts and is designed to perform as experts do. The term knowledge acquisition was coined by the developers of such systems to refer to various techniques such as structured interviewing, proto- col or talk aloud analysis, questionnaires, surveys, observation, and simula- tion. Some authors (e.g., Keritsis, 2001) even use the term digital cloning.

F

IGURE

4-3

T

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4I

MODEL OF ORGANIZATIONAL LEARNING

Organization Group Individual

FEEDBACK

FEED FORWARD

Individual Group Organization

Interpret

Integrate

Institutionalize Knowledge Intuiting

Attending

Experimenting

Source: Crossan, Lane, and White, 1999.

Knowledge management in business settings is similarly concerned with knowl- edge capture, finding ways to make tacit knowledge explicit (e.g., document- ing best practices) or creating expert directories to foster knowledge sharing through human–human collaboration (Smith, 2000). In 1989, for example, Feigenbaum contrasted traditional libraries as “warehouses of passive objects where books and journals wait for us to use our intelligence to find them, to interpret them and cause them finally to divulge their stored knowledge”

(p. 122) with a library of the future where “books” would interact and col- laborate with users.

Tacit Knowledge Capture at Individual and Group Levels

Knowledge acquisition from individuals or groups can be characterized as the transfer and transformation of valuable expertise from a knowledge source (e.g., human expert, documents) to a knowledge repository (e.g., corporate memory, intranet). This process involves reducing a vast volume of content from diverse domains into a precise, easily usable set of facts and rules. “The idea of acquiring knowledge from an expert in a given field for the purpose of designing a specific presentation of the acquired information is not new.

Reporters, journalists, writers, announcers and instructional designers have been practicing knowledge acquisition for years . . . system analysts have func- tioned in a very similar role in the design and development of conventional software systems” (McGraw and Harrison-Briggs, 1989, pp. 8–9).

The approach used to capture, describe, and subsequently code knowledge depends on the type of knowledge: explicit knowledge is already well described, but we may need to abstract or summarize this content. Tacit knowl- edge, on the other hand, may require much more significant up-front analysis and organization before it can be suitably described and represented. The ways in which we can tackle tacit knowledge range from simple graphical repre- sentations to sophisticated mathematical formulations.

In the design and development of knowledge-based systems, or expert systems, knowledge engineers interviewed subject matter experts, produced a conceptual model of their critical knowledge, and then “translated” this model into a computer-executable model such that an “expert on a diskette” resulted (e.g., Hayes-Roth, Waterman and Lenat, 1983). The global aim of such systems was to extract and render explicit the primarily procedural knowledge that comprised specialized know-how—typically in a very narrow field. Procedural knowledgeis knowledge of how to do things, how to make decisions, how to diagnose, and how to prescribe. The other type of knowledge, declarative knowledge, denotes descriptive knowledge or knowing “what” as opposed to knowing “how.” It soon became apparent that certain types of content were easily extracted and modeled in this manner—anything that was similar to an interactive online manual or help function in such fields as engineering, manufacturing, decision support, and medicine.

A wonderful by-product of the work in artificial intelligence was the array of innovative knowledge acquisition techniques that were created. The inter- actions with subject matter experts that were needed to render tacit knowledge

explicit made up the knowledge engineer’s toolkit. Quite a few of these tech- niques are imminently relevant and applicable to the process of tacit knowl- edge capture in knowledge management applications. The major tasks carried out by knowledge engineers included:

■ Analyzing information and knowledge flow.

■ Working with experts to obtain information.

■ Designing and implementing an expert system.

Only the last point would differ, and it could be replaced by “designing and implementing a knowledge management system or knowledge repository.” On the other side were the subject matter experts, and they had to be able to:

■ Explain important knowledge and know-how.

■ Be introspective and patient.

■ Have effective communication skills.

Subject or domain experts were usually “sole sources of information whose expertise companies wish to preserve” (McGraw and Harrison-Briggs, 1989, p. 7). Today, many organizations face knowledge continuity concerns due to a wave of retiring baby boomers who represent knowledge “walking out the door.” The concerns are quite similar, and the techniques used show a great deal of overlap. For example, multiple experts were often participants in knowledge engineering sessions in order to cover the range of expertise they represented, to validate the content, to provide different perspective, and so on. A number of group knowledge acquisition techniques were developed and used successfully with such groups. These approaches would be a perfect fit for knowledge acquisition at the community of practice level.

Another artificial intelligence researcher, Parsaye (1988), outlined the fol- lowing three major approaches to knowledge acquisition from individuals and groups:

1. Interviewing experts.

2. Learning by being told.

3. Learning by observation.

All three approaches are applicable to tacit knowledge capture, but no one approach should be used to the total exclusion of the others. In many cases, a combination of these approaches will be required to capture tacit knowledge.

The following section presents a toolkit and guidelines on the strengths and drawbacks of each as a means of helping select the best combination of tech- niques for different knowledge capture situations.

Interviewing Experts

Two of the more popular techniques for optimizing the interviewing of experts are structured interviewing and stories.

Structured Interviewing

Structured interviewing of subject matter experts is the most often used tech- nique to render key tacit knowledge of an individual into more explicit forms.

In many organizations, structured interviewing is performed through exit inter- views that are held when knowledgeable staff near retirement age. Content management systems are well suited to publishing their lessons learned and best practices accumulated over their years of experience at the organization.

Structured interviewing techniques require strong communication and con- ceptualization skills. In addition, interviewers need to have a good grasp of the subject matter at hand. These sessions yield specific data that is often declara- tive in response to focused questions. Structured interviews may also be used to clarify or refine knowledge originally elicited during unstructured interac- tions. The interviewer should outline specific goals and questions for the knowledge acquisition session. The interviewee should be provided with session goals and sample lines of questioning but usually not the specific ques- tions to be asked.

Two major types of questions are used in interviewing: open and closed ques- tions. Open questions tend to be broad and place few constraints on the expert.

They are not followed by choices because they are designed to encourage free response (Oppenheim, 1966). These types of questions allow interviewers to observe the expert’s use of key vocabulary, concepts, and frames of reference.

The expert can also offer information that was not specifically asked for. Some examples would be:

■ “How does that work?”

■ “What do you need to know before you decide?”

■ “Why did you choose this one rather than that one?”

■ “What do you know about . . .”

■ “How could . . . be improved?”

■ “What is your general reaction to . . . ?”

Closed questions set limits on the type, level, and amount of information an expert will provide. A choice of alternatives is always given. A moderately closed question would be something like: “which symptom led you to conclude that . . . ?” A very strong closed question is one that can only be answered by yes or no.

The structured interviewing process is primarily a people-focused one, and as such, techniques that serve to facilitate the interactions can greatly con- tribute to the successful outcome of such sessions. Reflective listening helps in cases where words may have multiple meanings. The interview participants may hold very different mental models, and personal characteristics such as background, attitude, training, and level of comfort with current position in the organization, may influence how an expert communicates his or her knowl- edge. The four major techniques used in reflective listening include para- phrasing, clarifying, summarizing, and reflecting feelings.

Paraphrasing is the restating of the perceived meaning of the speaker’s message but using your own words. The goal is to check the accuracy with which the message was conveyed and understood. Examples include:

■ “What I believe you said was . . .”

■ “If I am wrong, please correct me but I understood you to say . . .”

■ “In other words, . . .”

■ “As I think I understand it . . .”

Clarifying lets the expert know that the message was not immediately under- standable. These responses encourage the expert to elaborate or clarify the original message so that the interviewer gets a better idea of the intended message. One should always focus on the message and not on the expert’s ability to communicate, and the expert should be encouraged to elaborate or explain by using open questions wherever possible. Examples include:

■ “I don’t understand . . .”

■ “Could you please explain . . .”

■ “Please repeat that last part again . . .”

■ “Could you give me an example of that . . .”

Summarizing helps the interviewer compile discrete pieces of information and form a knowledge acquisition session into a meaningful whole. It also helps confirm that the expert’s message was heard and understood correctly.

The summary should be expressed in the words of the interviewer. Examples would be:

■ “To sum up what you have been saying . . .”

■ “What I have heard you say so far . . .”

■ “I believe that we are in agreement that . . .”

Finally, reflecting feelings mirrors back to the speaker the feelings that seem to have been communicated. The main focus is on emotions, attitudes, and reactions, and not on the content itself. The purpose is to clear the air of some emotional reaction or negative impact of the message. Some examples are:

■ “You seem frustrated about . . .”

■ “You seem to feel that you were put on the spot . . .”

■ “I sense that you are uncomfortable with . . .”

Transcripts of interviews are then analyzed in order to identify key concepts, common themes, and major methods or techniques that were mentioned. If multiple experts were interviewed for the same procedure or subject, then con- flict resolution might be needed. Usually, each individual will be interviewed more than once so that interviewers can validate their understanding of the knowledge that has been elicited, fill in any missing gaps, and better concep- tualize the content in an organized manner. Each interview will raise additional questions, whether these are aimed at clarifying, correcting, or expanding upon critical elements. After a number of interviews and follow-up sessions, the interviewer will be able to start identifying key themes and have a preliminary

framework for organizing these themes. Unlike the initial interview sessions, where new content is generated and captured, subsequent interviews are more focused and target a more detailed level.

The best test of whether enough content has been captured is to switch roles:

the interviewer can assume the role of novice practitioner and verbally or phys- ically go through the key tasks discussed to date. The interviewee can then validate until both are satisfied that the knowledge has been understood and captured in as complete and valid a manner as possible.

Stories

Stories are another excellent vehicle for both capturing and coding tacit knowledge. An organizational story is a detailed narrative of management actions, employee interactions, and other intraorganizational events that are communicated informally within the organization. A story can be defined as the telling of a happening or a connected series of happenings, whether true or fictitious (Denning, 2001). Snowden (2001) defines a narrative as: “not just about telling, constructing or even eliciting stories, it is about allowing the pat- terns of culture, behaviour, and understanding that are revealed by stories to emerge” (p. 1). An organizational story can be defined as a detailed narrative of past management actions, employee interactions, or other key events that have occurred and that have been communicated informally (Swap et al., 2001). Conveying information in a story provides a rich context, causing the story to remain in the conscious memory longer and creating more memory traces than is possible with information not in context. Stories can greatly increase organizational learning, communicate common values and rule sets, and serve as an excellent vehicle for capturing, coding, and transmitting valu- able tacit knowledge.

A number of conditions must be in place, however, in order to ensure that storytelling in its various enacted forms creates value in a particular organiza- tion. Sole and Wilson (2002) argue that although all stories are narratives, not all narratives are good knowledge-sharing stories. As an example, they cite movies, which tell stories designed primarily to entertain and therefore need not necessarily be authentic—or even believable. In contrast, in organizational storytelling, stories are often used to promote knowledge sharing, inform, and/or prompt a change in behavior, as well as communicate the organizational culture and create a sense of belonging. In order to achieve these organiza- tional objectives, knowledge-sharing stories need to be authentic, believable, and compelling. Stories need to evoke some type of response, and, above all, they need to be concise (Denning, 2001), so that the moral of the story or the organizational lesson to be learned can be easily understood, remembered, and acted upon. In other words, organizational stories should have an impact: they should prevent similar mistakes from being repeated, or they should promote organizational learning and adoption of best practices stemming from the collective organizational memory.

Denning (2001) describes the power of a springboard story, knowledge that has been captured in the form of a brief story that has the ability to create a strong impact on its audience. He outlines a number of key elements required to use stories to encapsulate valuable knowledge, such as:

■ The explicit story should be relatively brief and detailed just enough that the audience can understand it.

■ The story must be intelligible to the specific audience so that they are

“hooked.”

■ The story should be inherently interesting.

■ The story should spring the listener to a new level of understanding.

■ The story should have a happy ending.

■ The story should embody the change message.

■ The change message should be implicit.

■ The listeners should be encouraged to identify with the protagonist.

■ The story should deal with a specific individual or organization.

■ The protagonist should be prototypical of the organization’s main business.

■ Other things being equal, true is better than invented.

■ One should test, test, and test again.

The use of fables such as those found in Aesop (1968) is often quite helpful in capturing tacit knowledge. A simple approach is to invite participants to a workshop where they are given several classic fables to read; they are asked to recollect some of what they have heard and to identify the lesson to be learned in each. Fables are particularly useful with multicultural groups since fables are ubiquitous in all cultures, but they definitely differ one from the other.

Participants are given a fable minus the “punch line,” and they are asked to fill in the moral of the story. Asking for a punch line is a highly effective way of acquainting participants with the objectives of stories or the purpose of organizational storytelling—that is, what the reader should learn from it.

Participants also become sensitized to the fact that stories, like fables, need to be concise. A fable can consolidate multiple viewpoints and recollections of different individuals because it is not dependent on a single story to deliver its message (Snowden, 2001). Finally, the best way to end a fable—the punch line—is to have an ironic end in which the reader realizes how a happy ending could have come about without the narrative actually stating this in any form.

The following vignettes on IBM and Xerox illustrate the value of storytelling in the capture of tacit knowledge.

IBM

Knowledge disclosure is a key way of identifying the organizational culture. Knowledge disclosure techniques such as storytelling allow us to uncover knowledge in the context of its use. IBM views stories as a power- ful means of knowledge discovery and knowledge transfer. They are very good for conveying complex messages simply. Storytelling is a unifying and defining component of all communities. Stories exist in all organizations;

managed and purposeful storytelling provides a powerful mechanism for the disclosure of intellectual or knowledge assets in companies. It can also

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