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Knowledge Management and Distributed Collaborative Work
This lecture will describe Distributed Collaborative Work (DCW) and its relationship to Knowledge Management (KM). It will identify two categories of DCW: Hot and Cold. The nature of these forms of DCW will be explored in further detail using the concepts of Hard and Soft knowledge from the field of KM. This will lead to a more detailed exploration of the relationship between KM and DCW based on three separate application areas.
Distributed Collaborative Work
Work may be distributed either physically (e.g. it may be carried out in different places) or temporally (e.g. it may be carried out at different times). The forms of Distributed Working that are considered in this course may involve one or both of these. Collaborative Work is taken to mean work that is undertaken as part of a group activity. There is an implicit assumption in most of the literature on Collaborative Working that the group activity is directed towards some shared goal or has some common purpose. As with almost any form of group activity there is some element of social interaction to the work as well as the simple fulfillment of a task (e.g. teamwork usually requires some degree of trust between the members of the team if it is to be effective).
Two distinct forms of Distributed Collaborative Work can be identified based on the work that is being done.
- Hot Distributed Collaborative Work (also known as 'closely coupled', 'tightly coupled' or 'on-line' distributed collaborative work) is collaborative in the sense that we would normally think of it, i.e. it is interactive work, done in association with others which requires the active participation of the other members of the group. However, as this is also distributed work, the groups will not be co-located.
- Cold Distributed Collaborative Work (also known as 'loosely coupled' or 'off-line' distributed collaborative work) is also collaborative work in the sense that it is part of some collective activity directed towards a shared goal or common purpose, but it is work that is performed individually, i.e. it is not work that requires the active participation of the other members of the group.
Knowledge is increasingly seen as central to the success of organizations and an asset that needs to be managed. Since the 1980s, many organizations have taken steps to outsource, downsize and de-skill in an effort to remain competitive. Outsourcing, downsizing and programmes of planned redundancy all mean that, as people leave, they take with them a valuable stock of knowledge. In addition, many organizations now employ trans-national teams. Such teams may lose many opportunities for informal collaboration and knowledge sharing. Working in an internationalized setting also means that teams have to face not only geographical distance, but also time, culture and possibly linguistic differences. Knowledge Management (KM) is an approach that claims to tackle these issues through focusing on techniques to manage the common base of organizational knowledge and encouraging its sharing and re-use.
Although there are many views about the nature of the knowledge to be managed (see The Duality of Knowledge) we will discuss two broad types.
- Hard Knowledge is unambiguous and unequivocal; it can be clearly and fully expressed, leaving nothing implied and no room for interpretation. Hard knowledge is formalized and structured knowledge, and thus can more easily be 'captured' and stored in a database or document. It is knowledge that is both abstract and static: it is about, but not in, the world such as a mathematical formula, operating procedure or instruction for action. It may be 'owned' without being used.
- Soft Knowledge is knowledge that is implicit and not easily articulated. Soft knowledge is knowledge that can be understood without being openly expressed. Soft knowledge can be socially constructed knowledge but is more often knowledge that has been acquired through the praxis of work. It might be internalized domain knowledge or expertise that has become second nature or is embedded in day-to-day working practices. It is about something we do, it is not something that can be possessed.
Based on this simple classification we might expect the relationship between KM and DCW to look something like this:
However, as we will see when we look at some examples of "real world" DCW, this relationship is not as straight forward as it seems.
- Nonaka, I. and von Krogh, G. (2009). Perspective - Tacit Knowledge and Knowledge Conversion: Controversy and Advancement in Organizational Knowledge Creation Theory. Organization Science, 20(3), pp. 635-652.
- Hildreth, P. and Kimble, C. (2002) The Duality of Knowledge Information Research, 8(1), paper no. 142
- Hildreth P. Wright P. and Kimble C. (1999) Knowledge Management: Are We Missing Something?. In Brooks L. and Kimble C. Information Systems - The Next Generation. Proceedings of the 4th UKAIS Conference, York, UK pp. 347-356
- Cook S.D. and Brown J.S. (1999) Bridging Epistemologies: The Generative Dance Between Organizational Knowledge and Organizational Knowing, Organization Science Vol. 10, No. 4, July-August, pp. 381-400.
- Preece J, Sharp H and Rogers Y. Interaction Design: beyond Human-Computer Interaction. John Wiley, 2002
- Okubo T, Matsutsuka, T, Nomura Y, Hara H, and Uehara S. (2000) Practical Experiences of Designing a Distributed Collaborative System, Fourth International Enterprise Distributed Object Computing Conference (EDOC'00), pp. 21 - 27
- Winograd, T. and Flores, F. (1987) Understanding Computers and Cognition. Addison-Wesley, Reading, Mass.
Distributed Collaborative Work (DCW)
- The Parting of the Ways: Divergence, Data Management and Collaborative Work. (.pdf)
Systems coordinating distributed collaborative work must manage user data distributed over a network. The strong consistency algorithms which designers have typically borrowed from the distributed systems community are often unsuited to the particular needs of CSCW. Here, Paul Dourish outlines an alternative approach based on divergence and synchronization between parallel streams of activity.
- Collaboration and Collaborative Information Technology: What is the nature of their relationship? (.pdf)
Collaborative information technologies have been claimed to enhance collaboration in organizations, under certain conditions. This claim was found to be problematic in several respects. A number of issues emerged in the review that could help in understanding the relationship of collaborative information technologies and changes in work and organization. The issues included the role of the specific capabilities of the technology; the difference between technology as a product and technology-in-use; the kind of care needed in bringing about desired changes; the emergent, drifting nature of the change process; the role of the technology as a constructive tool in improvising and enacting the changes and the gradual translations of influences from work practices to organizational practices.
- What is Knowledge Management? (Sveiby Knowledge Management)
"Concepts are best defined from how people use them". Sveiby attempts to define Knowledge Management by looking at what "the people in this field" are doing - i.e. vendors (consultants and researchers) and users ". Describes KM from a people and an IT viewpoint and also traces the history of the KM concept from 1992 onwards.
- Knowledge Management: Concepts and Controversies
In most dimensions of knowledge management social and personal issues are highly relevant. The effectiveness of physical space for knowledge work is dependent on what is physically delivered through architecture, construction and facilities management. It is at least as dependent on personal and conceptual space - territoriality, privacy, and intimate communications.
- A theoretical framework for knowledge management implementation
This paper outlines ongoing research in the area of knowledge management implementation strategies. An investigation of the literature reveals that when organizations initiate a knowledge management effort, most of them tend to over-emphasize the role of information technology at the expense of the human factor. This paper proposes a framework that consists of three main interlinked components: Knowledge Management of the Organization, People, and Infrastructure and Processes.
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