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 Subject: Knowledge Management and technology/ Analysis
 
Author: Christian
Date:   1/29/2008 11:15 pm 
The goal of this analysis is to provide an overview of technologies that can be applied to knowledge management and to assess their actual or potential contribution to the basic processes of knowledge creation and sharing within organizations. The aim is to identify trends and new developments that seem to be significant and to relate them to technology research in the field, rather than to provide a comprehensive review of available products.

Knowledge management (see, for example, Davenport and Prusak[1]) is the name given to the set of systematic and disciplined actions that an organization can take to obtain the greatest value from the knowledge available to it.
"Knowledge" in this context includes both the experience and understanding of the people in the organization and the information artifacts, such as documents and reports, available within the organization and in the world outside.
Effective knowledge management typically requires an appropriate combination of organizational, social, and managerial initiatives along with, in many cases,
deployment of appropriate technology. It is the technology and its applicability that is the focus of this paper.

To structure the discussion of technologies, it is helpful to classify the technologies by reference to the notions of tacit and explicit knowledge introduced by Polanyi in the 1950s[2,3] and used by Nonaka[4,5] to formulate a
theory of organizational learning that focuses on the conversion of knowledge between tacit and explicit forms. Tacit knowledge is what the knower knows,
which is derived from experience and embodies beliefs and values. Tacit knowledge is actionable knowledge, and therefore the most valuable. Furthermore, tacit knowledge is the most important basis for the generation of
new knowledge, that is, according to Nonaka: "the key to knowledge creation lies in the mobilization and conversion of tacit knowledge."[5] Explicit knowledge is represented by some artifact, such as a document or a video, which
has typically been created with the goal of communicating with another person.
Both forms of knowledge are important for organizational effectiveness.[6]

These ideas lead us to focus on the processes by which knowledge is transformed between its tacit and explicit forms, as shown in Figure 1.[5] Organizational
learning takes place as individuals participate in these processes, since by doing so their knowledge is shared, articulated, and made available to others.
Creation of new knowledge takes place through the processes of combination and internalization. As shown in Figure 1, the processes by which knowledge is
transformed within and between forms usable by people are

o Socialization (tacit to tacit): Socialization includes the shared formation
and communication of tacit knowledge between people, e.g., in meetings.
Knowledge sharing is often done without ever producing explicit knowledge and,to be most effective, should take place between people who have a common
culture and can work together effectively (see Davenport and Prusak,[1] p. 96).
Thus tacit knowledge sharing is connected to ideas of communities and collaboration. A typical activity in which tacit knowledge sharing can take place is a team meeting during which experiences are described and discussed.

o Externalization (tacit to explicit): By its nature, tacit knowledge is difficult to convert into explicit knowledge. Through conceptualization, elicitation, and ultimately articulation, typically in collaboration with
others, some proportion of a person's tacit knowledge may be captured in explicit form. Typical activities in which the conversion takes place are in dialog among team members, in responding to questions, or through the
elicitation of stories.

o Combination: (explicit to explicit): Explicit knowledge can be shared in meetings, via documents, e-mails, etc., or through education and training. The use of technology to manage and search collections of explicit knowledge is
well established. However, there is a further opportunity to foster knowledge creation, namely to enrich the collected information in some way, such as by
reconfiguring it, so that it is more usable. An example is to use text classification to assign documents automatically to a subject schema. A typical activity here might be to put a document into a shared database.

o Internalization (explicit to tacit): In order to act on information, individuals have to understand and internalize it, which involves creating their own tacit knowledge. By reading documents, they can to some extent
re-experience what others previously learned. By reading documents from many sources, they have the opportunity to create new knowledge by combining their existing tacit knowledge with the knowledge of others. However, this process is becoming more challenging because individuals have to deal with ever-larger
amounts of information. A typical activity would be to read and study documents from a number of different databases.

These processes do not occur in isolation, but work together in different combinations in typical business situations. For example, knowledge creation
results from interaction of persons and tacit and explicit knowledge. Through interaction with others, tacit knowledge is externalized and shared.[7]
Although individuals, such as employees, for example, experience each of these processes from a knowledge management and therefore an organizational
perspective, the greatest value occurs from their combination since, as already noted, new knowledge is thereby created, disseminated, and internalized by
other employees who can therefore act on it and thus form new experiences and tacit knowledge that can in turn be shared with others and so on.[7] Since all
the processes of Figure 1 are important, it seems likely that knowledge management solutions should support all of them, although we must recognize that the balance between them in a particular organization will depend on the
knowledge management strategy used.[8]

Table 1 shows some examples of technologies that may be applied to facilitate the knowledge conversion processes of Figure 1. These technologies and others
are discussed in this paper. The individual technologies are not in themselves knowledge management solutions. Instead, when brought to market they are
typically embedded in a smaller number of solutions packages, each of which is designed to be adaptable to solve a range of business problems. Examples are
portals, collaboration software, and distance learning software. Each of these
can and does include several different technologies.

----------------------------------------------------------------------------
Table 1 Examples of technologies that can support or enhance the
transformation of knowledge

Tacit to Tacit Tacit to Explicit
E-meetings Answering questions
Synchronous collaboration (chat) Annotation

Explicit to Tacit Explicit to Explicit
Visualization Text search
Browsable video/audio of presentations Document categorization
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The approach to the technology of knowledge management in this paper emphasizes human knowledge. Sometimes in computer science "knowledge management" is interpreted to mean the acquisition and use of knowledge by computers, but that is not the meaning used here. In any case, automatic extraction of deep
knowledge (i.e., in a form that captures the majority of the meaning) from documents is an elusive goal. Today the level of automatic extraction is deemed
to be rather shallow because only a subset of the meaning, sometimes a very limited one, can be captured, ranging from recognition of entities such as
proper names or noun phrases to automatic extraction of ontological relations of various kinds (e.g., References 9 and [10), and there is no system that can
reason (in the sense of deducing something new from what it already knows) over the extracted knowledge in a way that even approaches the capabilities of a
human. As an example of the current state of the art in applications for extracting knowledge automatically, Figure 2 shows a system[11] for analyzing
reports of appellate court decisions to find the precedents they may affect.
Court opinions are analyzed to find language that refers to other cases that the opinion may modify or invalidate. The candidate cases are retrieved from a
database of law reports and are presented to an analyst for final judgment. The results are used to enrich the database with appropriate cross-references. Here
the approach is that a template defines the fragment of knowledge to be sought, and the system tries to fill it by extracting information from the text.
However, the candidate pieces of extracted knowledge must still be presented to a human for review and final decision, so that the value of the system is in
increasing the productivity of the human analysts. For the foreseeable future, knowledge management in business will be about human knowledge in its various forms.

The use of technology in knowledge management is not new, and considerable experience has been built up by the early pioneers. Even before the availability of solutions such as Lotus Notes**[12] on which many contemporary knowledge management solutions are based, companies were deploying intranets, such as EPRINET,[13] based on early generations of networking and computer technology that improved access to knowledge "on line." Collaboration and knowledge sharing solutions also arose from the development of on-line conferencing and forums[14] using mainframe computer technology. Today, of course, intranets and the Internet are ubiquitous, and we are rapidly approaching the situation where all the written information needed by a person to do his or her job is available on line. However, that is not to say that it can be used effectively with the tools currently available.

It is important to note that knowledge management problems can typically not be solved by the deployment of a technology solution alone. The greatest
difficulty in knowledge management identified by the respondents in a survey[15] was "changing people's behavior," and the current biggest impediment
to knowledge transfer was "culture." Overcoming technological limitations was much less important. The role of technology is often to overcome barriers of
time or space that otherwise would be the limitingfactors. For example, a research organization divided among several laboratories in different countries
needs a system that scientists with common interests can use to exchange information with each other without traveling, whereas a document management
system can ensure that valuable explicit knowledge is preserved so that it can be consulted in the future. Two caveats must be stated at this point. First is
the point made by Ackerman[16] that in many respects the state of the art is such that many of the social aspects of work important in knowledge management
cannot currently be addressed by technology. Ackerman refers to this situation as a "social technical gap." Second, the coupling between behavior and
technology is two-way: the introduction of technology may influence the way individuals work. People can and do adapt their way of working to take
advantage of new tools as they become available, and this adaptation can produce new and more effective communication within teams (e.g., the effect of
introducing solutions based on Lotus Notes on process teams in a paper mill described by Robinson et al.[17] or the adaptations made by people in a
customer support organization studied by Orlikowski[18] after Notes was introduced).

Other surveys of technology for knowledge management can be found in the book, Working Knowledge by Davenport and Prusak,[1] and in a paper by Jackson.[19]
Prospects for using artificial intelligence (AI) techniques in knowledge management have been discussed recently by Smith and Farquhar.[20]

In the following sections of this paper the technologies that support the processes of Figure 1 are described in more detail and illustrated with examples drawn largely from current research projects.

Tacit to tacit

The most typical way in which tacit knowledge is built and shared is in face-to-face meetings and shared experiences, often informal, in which information technology (IT) plays a minimal role. However, an increasing proportion of meetings and other interpersonal interactions use on-line tools known as groupware. These tools are used either to supplement conventional meetings, or in some cases to replace them. To what extent can these tools facilitate formulation and transfer of tacit knowledge?

Groupware. Groupware is a fairly broad category of application software that helps individuals to work together in groups or teams. Groupware can to some
extent support all four of the facets of knowledge transformation. To examine the role of groupware in socialization we focus on two important aspects:
shared experiences and trust.

Shared experiences are an important basis for the formation and sharing of tacit knowledge. Groupware provides a synthetic environment, often called a
virtual space, within which participants can share certain kinds of experience; for example, they can conduct meetings, listen to presentations, have discussions, and share documents relevant to some task. Indeed, if a
geographically dispersed team never meets face to face, the importance of shared experiences in virtual spaces is proportionally enhanced. An example of
current groupware is Lotus Notes,[12] which facilitates the sharing of documents and discussions and allows various applications for sharing information and conducting asynchronous discussions to be built. Groupware might be thought to mainly facilitate the combination process, i.e., sharing of explicit knowledge. However, the selection and discussion of the explicit knowledge to some degree constitutes a shared experience.

A richer kind of shared experience can be provided by applications that support real-time on-line meetings--a more recent category of groupware. On-line
meetings can include video and text-based conferencing, as well as synchronous communication and chat. Text-based chat is believed to be capable of supporting
a group of people in knowledge sharing in a conversational mode.[21] Commercial
products of this type include Lotus Sametime** and Microsoft NetMeeting**.
These products integrate both instant messaging and on-line meeting capabilities. Instant messaging is found to have properties between those of the personal meeting and the telephone: it is less intrusive than interrupting
a person with a question but more effective than the telephone in broadcasting a query to a group and leaving it to be answered later.

Finally, it should be emphasized again that this paper has dealt with human knowledge, not with the formation or use of expert systems or similar knowledge-based systems that aim to replace human reasoning with machine intelligence. The current capability of machine intelligence is such that, for the great majority of business applications, human knowledge will continue to be a valuable resource for the foreseeable future, and technology to help to
leverage it will be increasingly valuable and capable.




Cited references

1. T. H. Davenport and L. Prusak, Working Knowledge: How Organizations Manage
What They Know, Harvard Business School Press, Boston, MA (1998).

2. M. Polanyi, The Tacit Dimension, Routledge & Kegan Paul, London (1996).

3. M. Polanyi, "The Tacit Dimension," Knowledge in Organizations, L. Prusak,
Editor, Butterworth-Heinemann, Woburn, MA (1997).

4. I. Nonaka, "The Knowledge Creating Company," Harvard Business Review 69,
96-104 (November-December 1991).

5. I. Nonaka and H. Takeuchi, The Knowledge Creating Company, Oxford University
Press, Oxford, UK (1995).

6. I. Nonaka and H. Takeuchi, "A Dynamic Theory of Organizational Knowledge
Creation," Organizational Science 5, No. 1, 14-37 (1994).

7. I. Nonaka and N. Konno, "The Concept of 'Ba': Building a Foundation for
Knowledge Creation," California Management Review 40, No. 3, 40-54 (1998).

8. M. T. Hansen, N. Nohria, and T. Tierney, "What's Your Strategy for Managing
Knowledge?" Harvard Business Review 77, 106-116 (March-April 1999).

9. B. Boguraev and C. Kennedy, "Applications of Term Identification Technology:
Domain Description and Content Characterization," Natural Language Engineering
1, 1-28 (1998).

10. A. Maedche and S. Staab, "Mining Ontologies from Text," Knowledge
Acquisition, Modeling and Management (EKAW), Springer, Juan-les-Pins (2000).

11. P. Jackson, K. Al-Kofahi, C. Kreilick, and B. Grom, "Information Extraction
from Case Law and Retrieval of Prior Cases by Partial Parsing and Query
Generation," Proceedings of the 1998 ACM CIKM: 7th International Conference on
Information and Knowledge Management, Bethesda, MD (November 3-7, 1998), pp.
60-67.

12. L. Kalwell, Jr., S. Beckhardt, T. Halvorsen, R. Ozzie, and I. Greif,
"Replicated Document Management in a Group Communication System," Proceedings
of the Conference on Computer Supported Cooperative Work, Portland, OR (1988).

13. M. M. Mann, R. L. Rudman, T. A. Jenckes, and B. C. McNurlin, "EPRINET:
Leveraging Knowledge in the Electric Utility Industry," Knowledge in
Organizations, L. Prusak, Editor, Butterworth-Heinemann, Woburn, MA (1997), pp.
73-97.

14. D. A. Foulger, Medium as Process: The Structure, Use and Practice of
Computer Conferencing on IBM's IBMPC Computer Conferencing Facility, Ph.D.
thesis, Department of Communications, Temple University, Philadelphia, PA
(1991).

15. R. Ruggles, "The State of the Notion: Knowledge Management in Practice,"
California Management Review 40, No. 3, 80-89 (1998).

16. M. S. Ackerman, "The Intellectual Challenge of CSCW: The Gap Between Social
Requirements and Technical Feasibility," Human-Computer Interaction 15, 179-203
(2000).

17. M. Robinson, M. Kovalainen, and E. Auramaki, "Diary as Dialogue in
Papermill Process Control," Communications of the ACM 43, No. 1, 65-70 (January
2000).

18. W. Orlikowski, "Improvising Organizational Transformation over Time: A
Situated Change Perspective," Information Systems Research 7, No. 1, 63-92
(1996).

19. C. Jackson, Process to Product: Creating Tools for Knowledge Management,
http://www.brint.com/members/online/120205/jackson/secn1.htm (2001).

20. R. G. Smith and A. Farquhar, "The Road Ahead for Knowledge Management," AI
Magazine 21, No. 4, 17-40 (2000).

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