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KNOWLEDGE MANAGEMENT #5 (Political Issues in Compound UK (Notes was used…
KNOWLEDGE MANAGEMENT #5
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Findings
Positive
- Local "mastery" achieved through databases + regular face-to-face meetings
Negative
- At a less local level the databases were the only communication method
- "Can't put this level of detail into a Notes database, + much of what I do input must be meaningless to others"
- Simplistic representation
- Reps didn't understand what ppl wanted, + why they sought clarification
- This feedback put them off recording - it didn't seem to be working
Separate Functions
- Sales, marketing + medical sectors all overlap [venn diagram style]
- Not much shared understanding
- Uncertainty about what other functions wanted from them
- Fear of appearing stupid/irrelevant
- Lack of time to contribute to databases
- Normally only accounted for their actions when things went wrong
- Accounts on the databases lacked the background [histories, activities + assumptions] in each discipline
- This form of codifying knowledge often failed. Social network development might have been more effective, to allow social processes to develop between staff
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Entreprise 2.0
- Entreprise Knowledge Management based on Web 2.0
- Attempts to use social networking style systems in work contexts
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- User comments + discussion
- Open creation + editing policies
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- Integration [linking] across systems + platforms
- Overall, advocates of E2.0 technologies claim that they more readily lend themselves to becoming a part of everyday work and, thus, they're more representative of what ppl are doing + who they're doing it with
- By tagging, users are more likely to categorise contributions that are related to what they're doing, + thus result in more meaningful search requests and retrievals
- Viewed more critically, and in relation to the case specific literature, such claims are technologically deterministic
- Further, while the use of Web 2.0 technologies may provide some of the benefits claimed, the use of such technologies in the form of E2.0 within a specific organisational setting will vary greatly
- KM can view technological determinism as negative, too optimistic about technology. Much KM work assumes the ability to transfer knowledge, later work is about getting the right ppl together to allow their social processes to allow creation of knowledge
Future Directions
Many of the issues are 'people issues'. It's possible artificially-intelligent agents could help by:
- Choosing relevant content
- Tagging and organising knowledge
- Knowledge representations of the world allow logic to highlight inconsistencies + logical conclusions from minimal facts [or assertions]
- Some robots can learn by doing [transfer tacit knowledge?]
- 3D printing to transfer some kinds of tacit knowledge
Social Networking could also help as it works by connecting ppl, so knowledge transfer issues may be reduced