1. Session 3c, 27 Wed October 2010 eChallenges e-2010 Copyright 2010 Net-Centric Tacit Knowledge Management 1
Net-Centric Approach to
Tacit Knowledge Management
Michael Brown
SkillsNET Corporation
Brussels – Germany - UK
Visibility into Embedded Knowledge Assets

2. Session 3c, 27 Wed October 2010 eChallenges e-2010 Copyright 2010 Net-Centric Tacit Knowledge Management 2
Michael Brown. . .

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Framing the Discussion
• Today’s organization are experiencing a convergence:
• Emerging technologies affecting work practices
– Virtualization of work
• A maturing workforce
– Retiring and/or moving on to second careers
– Walking out the door with years of experience
• Hiring of Tech-savvy employees
– High comfort and skill; technology is natural
• New Internet capabilities
– Web 2.0 (social web) / Web 3.0 (semantic web)
• The Leadership mandate:
Maximize the enterprise’s intellectual capital via tacit
knowledge management to optimize capability and
competitiveness

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Motivation, Problem Area
• Specialized population of second line engineers needed to improve
processes to capture and share expertise
• Methodology could not duplicate existing knowledge capture and sharing
applications
• Solution had to improve workflow and worker productivity
• Process had to be self-directed / self-correcting / self-auditing
• To demonstrate the value of using semantic and social web tools to capture
and share hidden dimensions of knowledge or skills forming key elements
of „expertise‟
• Experienced workers draw upon these elements in everyday activities and continuously
expand them in tackling new or unexpected situations
Motivation:
Problem Area:

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Major Research Objectives
1. Is it possible to capture operational and tacit
knowledge via net-centric event and content analysis?
2. Could such a process become ubiquitously imbedded
in every day workflow routines?
3. Would such a system increase visibility into Tacit
Knowledge and expertise data?
4. Could such a system be integrated into enterprise
architecture?

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Sensor
Appliance
Associations/
Affiliation
Engine
Semantic/
NLP
Small Worlds
Context
Analytics
MIKE
Dashboard
Net-Centric
Event Management
/Content
Other Content
Sources
Taxonomic
Adjustment
Data Collection
1 32
Dashboard
Semantic Analysis Data Alignment Data Presentation
Email
Blog, Wiki
IM, etc.
Reports
Diagrams
Records
“We didn’t hire smart people so we could tell them what to do; we
hired them to tell us what to do.”
An interdisciplinary research approach
Research Approach, Methodology
Most Important
Knowledge and
Expertise
MIKE

7. Session 3c, 27 Wed October 2010 eChallenges e-2010 Copyright 2010 Net-Centric Tacit Knowledge Management 7
Second line engineers
collaborate electronically
with other engineers who
use TK & EK to assist
Second line
engineers
receive a
request for
assistance
Second line
engineers
use TK to
formulate a
solution
Electronic artifacts
are “processed” and
added to MIKE
MIKE Data are shared to solve
new problems; solutions are then
added to MIKE as new TK
M I K E
Application
EK with embedded TK
2.
3.
4.
5.
1.
Vendors Field Technicians /
Engineers
Second line engineers
research Net-centric
and other content, e.g.,
Records of Assistance,
Tech Reports,
Handbooks, etc.
Contextual Environment

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Major Outcomes / Results
MIKE is self-populating - self-correcting

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Major Outcomes / Results
• Extraction of data from social business, expertise and trust networks.
• Event-based filtering and navigation of e-mail, blog, wiki discussions.
• Uncovering hidden tacit knowledge in explicit knowledge artifacts.
• Filtering and navigation of VoIP telephony transactions.
Demonstrated easy exploratory yet comprehensive access to net-
centric data and allowed for:

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Conclusion and Outlook
• Given the forces of change, more effective capturing and sharing
of TK across the enterprise is essential for maximizing
organizational performance and competitiveness; MIKE
technology can facilitate this.
• The work culture is migrating toward a Virtual Organization (VO)
operational environment; MIKE technology can help organizations
manage that imminent change.
• Tacit knowledge and sharing patterns can be captured, presented
and optimized without disruption to employees’ daily routine.

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Early Adopters
Going beyond the proto-type experience…….
Major water utility in Maryland, USA
NASA aerospace contractors
University of Houston future smart grid workforce

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