Transcript Knowledge Management - Personal Web Server

Dr. Ricky Yeung
Laboratory Manager
Dept. Manufacturing Engg. & Engg. Management
City University of Hong Kong
President, Institute of Industrial Engineers
(HK)
Email: [email protected]
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
From Data to Knowledge
Data is just a set of particular and objective facts about an event or the
structured record of a transaction.
Data has little use by itself unless converted into information.
Data should not be stored into a system for managing knowledge; it should be stored as
value-added information - by the addition of historical context.
Information is just data endowed with relevance and purpose.
- by Peter Drucker
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
5C’s to convert Data to Information
Condensation
Contextualization
Calculation
Correction
Data
Department of Manufacturing Engineering
and Engineering Management
Categorization
Information
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
5C’s to convert Data to Information
Condensed
Data is summarized in more concise form and unnecessary depth is
eliminated.
Contextualized
we know why the data was collected.
Calculated
Analyzed data, similar to condensation of data.
Categorized
The unit of analysis is known.
Corrected
Errors have been removed, missing “data holes: have been
accounted for.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Definition of Knowledge
Knowledge is a fluid mix of framed experience, values, contextual information, expert
insight and grounded intuition that provides an environment and framework for evaluating
and incorporating new experiences and information. It originates and is applied in the minds
of knowers. In organizations, it often becomes embedded not only in documents or
repositories but also in organizational routines, processes, practices, and norms.
- by Thomas Davenport and Laurence Prusak
Actionable information is knowledge
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Knowledge Management
Knowledge Management is thus the management of knowledge. It enables the creation,
communication, and application of knowledge of all kinds to achieve business goals.
- by Paul Quintas
Knowledge Management is the ability to create and retain greater value from core business
competencies.
- by Kirk Klasson
Knowledge Management addresses business problems particular to your business - whether
it is creating and delivering innovative products or services; managing and enhancing
relationships with existing and new customers, partner, and suppliers; or administering and
improving work practices and processes
- by Amrit Tiwana
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
What KM is not ?
• KM is not knowledge engineering. KM is more a business and cultural problems. It
needs to take care of people, information systems and management.
• KM is about process, not just digital networks. IT is just one of the biggest enabler for
effective KM. KM needs a knowledge culture driven by a performance-linked-toreward system to encourage knowledge sharing.
• KM is not about building a “smarter” intranet. Intranet is just a good front-end that
provides a stable messaging and collaboration platform.
• KM is not about one-time investment. It involves a continuous process of measure,
audit, review, and so on.
• KM is not about “capture”. Most of the knowledge cannot be captured, only
information can be captured.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Two categories of Knowledge
Tacit knowledge is personal, context-specific knowledge that is difficult to formalize,
record, or articulates. It is stored in the heads of people. The tacit component is mainly
developed through a process of trial and error encountered in practice.
• Belief, norms, experience, values, etc.
Explicit knowledge is that component of knowledge that can be codified and transmitted
in a systematic and formal language : documents, databases, webs, e-mail, etc.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
KM strategy - the Nonaka’s SECI model
Socialization
Externalization
Tacit -> Tacit
Tacit -> Explicit
S
E
I
C
Internalization
Combination
Tacit <- Explicit
Explicit <- Explicit
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Socialization : T to T
Face-to-face Communications
 Video Conferencing Tools
 Web Cams
 Virtual Reality Tools

C: Company knowledge
G: Group or Team knowledge
I: Individual knowledge
Department of Manufacturing Engineering
and Engineering Management
I
I
I
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Externalization : T to E
Process Capture Tools
 Traceability
 Reflective Peer-to-Peer networks
 Expert System
 Discussion Platform

C: Company knowledge
G: Group or Team knowledge
I: Individual knowledge
Department of Manufacturing Engineering
and Engineering Management
G
I
I
I
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Combination : E to E
Systemic Knowledge Tools
 Collaborative Computing Tools
 Intranets, GroupWare
 Discussion Lists
 Web Forums
 Best Practice Database

C: Company knowledge
G: Group or Team knowledge
I: Individual knowledge
Department of Manufacturing Engineering
and Engineering Management
G
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
C
G
City University
of Hong Kong
Internalization : E to T
Collective Knowledge Networks
 Notes Database / Org Memory
 Pattern Recognition
 Neural Networks

C
C: Company knowledge
G: Group or Team knowledge
I: Individual knowledge
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
G
I
City University
of Hong Kong
Typical source of Knowledge
Source
E
T
Employee knowledge, skills, and Competencies


Experiential knowledge (both at an individual and


group level)
Team-based collaborative skills

Informal shared knowledge

Values

Norms

Beliefs
E - Explicit/Codificable
Department of Manufacturing Engineering
and Engineering Management



T- Tacit/Needs Explication
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Typical source of Knowledge
Source
E
T
Task-based knowledge


Knowledge embedded in physical systems


Human capital

Knowledge embedded in internal structures

Knowledge embedded in external structures
Customer capital
Experiences of the employee
Customer relationship
E - Explicit/Codificable
Department of Manufacturing Engineering
and Engineering Management








T- Tacit/Needs Explication
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
4 stages of knowledge leverage
Desirable
Care-Why
Knowledge Stage
Know-Why
Knowledge management
system supported
- by James Brian Quinn
Know-How
Know-What
Current State of Most Companies
Initial
Level of
Knowledge
Department of Manufacturing Engineering
and Engineering Management
Leveragibility
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
Desirable
City University
of Hong Kong
4 stages of knowledge leverage
Know-what : This is the fundamental stage where the organization makes use
of IT of some kinds to collect, gather and store the cognitive type of
knowledge. In simple words, they just know what they know, but don’t mean
that they know when and how to apply such knowledge solve their problem.
Know-how : It represents the ability to translate bookish knowledge into real
world results. In this stage, they know when to use which knowledge to solve
real-world, complex problems.
Know-why : It goes beyond the know-how stage where they can use known
rules and apply them well. In addition, they have in-depth knowledge of the
complex slush of cause-and-effect relationships that underlie. This knowledge
enables individuals to move a step above know-how and create extraordinary
leverage by using knowledge, bringing in the ability to deal with unknown
interactions and unseen situations.
Care-why : It represents self-motivated creativity that exists in a company. This
happens to be the only level that cannot be supported by knowledge
management system.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Role of IT: a leveraged infrastructure
Enterprise KM
Network
Knowledge Flows
Information Mapping
Information Sources
Web Sites, Pointers
Repository
Distributed Search
Information and
Knowledge Exchange
Databases
Models
Distributed Retrieval
Viewing Tools
Messaging
Distribution Channels
Multimedia Content
Collaborative Annotation
File Systems
Enterprise Data
Versioning Controls
Context Addition
Legacy Systems
Metadata
Bulletin Boards
Messaging Integration
Workflow
Informal Conversation
PM Tools
Legacy Integration
Collaborative Tools
Check In/Out
Operational Data
Threading
Discussions
External Networks
Transaction Reports
Platform Independence
Intelligent Agent and Network Mining
Push Agents
Pull Agents
Department of Manufacturing Engineering
and Engineering Management
Data and Text Mining
Web Farming Technologies
Information Indexing and Classification
City University
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
of Hong Kong
Information Clustering and Lumping
Workflow
Document
Management
Routing
Control
Distribution
Project
Management
Routing
Electronic
Conversion
Informal
Capture
Dialog
Conversation
Knowledge Management
Technologies
Activities
Distribution
Connectivity
Publishing
Web
Conferencing
Expertise
Pointers
Transparent
Capture Tools
e.g.Crosspads
Collaboration
Intranets
Operational Data
Knowledge discover
Validation
Cleansing
GroupWare
Data
Warehouse
Internal Capture
Data Mining
Document Exchange
Data Cleansing
Collaboration
Validating
Department of Manufacturing Engineering
and Engineering Management
Telephones
Informal
Conversation
Making
Conversation
Watercoolers
Problem Solving
Brainstorming
Tacit Knowledge
Capture
Notes
Digital
Whiteboards
Decision
Support Systems
Case-based
Reasoning
Independent Thought
Mind Maps
Visual Thinking Tools
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Wrap up : points to remember
• Collaborative synergy and support : KM needs to support collaboration,
knowledge sharing, learning and continuous improvement.
• Real knowledge, not artificial intelligence : no more about capturing smartest
employee’s knowledge in a knowledge base or expert system.
• Conversation as a medium for thought : free, unrestricted, and easy conversation
must be supported.
• Sources and originators, not just information : make it easy to find sources of knowhow, locate people and expertise.
• The golden rule : KM is built around people.
• Decision support : be enhanced by historical perspective that KM support.
• Pragmatism, not perfection : begin with what you have, and then incrementally
improve it.
• The user is king : ability of end users to define and control interaction with
numerous sources of information.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
A closer look of Information
Management
Can be a good first step to empower your employees to know-how and knowwhy. It can be achieved by establishment of Information Democracy.
Socialization
Democracy
Control
Anarchy
Department of Manufacturing Engineering
and Engineering Management
Access
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
A survey in 1998 in US/UK
• 88% of managers use gut feeling over 75% of time for making business
decision
• 93% of them are under pressure to make effective decisions with short timespans.
• 62% of them do not receive right information to make decision, yet 99% have
access to desktop computer.
• 100% of sales and marketing managers have to reply on other people for
information. Only 25% of them believe that the information is up-to-date.
• Company directors are intolerant of decisions made by managers based on gut
feeling, insisting that decisions should be made only on hard facts.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Democratization and business value
Influenced by three key factors :• level of democratization within the organisation : the ratio of business intelligence
enabled used out of the total number of desktops.
• level of empowerment : the number of users entitled to perform ad hoc requests for
data versus the number of total users.
• level of cultural propensity : the number of different departments that are involved
in the deployment of the solution times the capacity to get access to other
departments’ information.
The greater these levels, the bigger the value of an
organisation‘s business intelligence.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Information value
chain
Outside of the Enterprise
Value
Within the Enterprise
Information
Merchandising
Business
Extension
Crossing
Boundaries
Usage
First Return on Information
Data Liability
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Information value
chain
• Data liability zone: the number of users is limited to the IT staff, for maintenance
purposes only.
• First return of Information zone: business users can now access data about their own
departmental activity. However, they still do not have access to the information
about information which is part of another system in another division of the
company.
• The enterprise Intelligence zone: company opens a department‘s business
intelligence to other departments or divisions. This requires a culture of information
sharing. Ultimately, it will reach a state of Information Democracy where a
collective intelligence is being built through open communication and willingness to
share data.
• The Extended Enterprise zone: the first extension of data access beyound the
organisation‘s four wall to an external constitutent (such as suppliers, customers,
or partners). Towards Information Embassy.
• Information Merchandising zone: Selling data to new types of customers via
Intelligent Extranets
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
A simplified model for information
empowerment
OLTP
Such as ERP/
legacy system
ETL
Extraction/
Transformation/
Loading
Data Marts
Data mining
OLAP
Business Intelligence/
ad hoc query/analysis
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
Trend/pattern prediction
City University
of Hong Kong
From Information Democratization to
Information Embassy
• Empowerment of your suppliers and customers like your employees
• use of Extranet deployment to create 3 new applications areas
• Supply chain extranet
• CRM extranet
• Information brokerage extranet
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Information Embassy by e-business
Intelligence ExtraNets
• Empower your customers, suppliers and partners, hust as empower your employees
• Motivation
• from e-commerce to e-business
• lots of information to share
• a needs for transparency : enables customers to access and analyze the data
through browsers
• a requirement for performance : your suppliers need to have instant access to
information that only their customer own
• a key enabler for competitiveness
• traditional paper reports
• arrive an important delay
• costly to print
• static
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Benefit of Information Embassy
• Create competitive advantage thtrough differentiation from competitors
• Help your customer save money
• Improve customer satisfaction
• Build customer loyalty and “lock-in”
• improving your own lot : force good, consistent information
• Reduce costs for generation paper and electronic reports and supplying them to
customers
• Generate a new revenue stream
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Challenges of Information Embassy
• Worry that customers can use newly available information to their advantages (short
term effect)
• how much functionality to offer
• basic reporting is mandatory
• ad hoc query/multi-dimensional analysis
• does not suffering from degraded response times
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Ingredients for success
• Make it a partnership
• an opportunity for the customer to contribute to the quality of information
relevant to both parties. Extranet welcome the opportunity to promptly correct
errors and omissions.
• make it functional, make it secure
• ensure that customers see only their own personal data. Balance the desirability
for a speedy deployment with the need to assess and select appropriate
software tools and infrastructure built to last.
• think creatively , be inclusive
• Building an information embassy involves many of the same fundamental
processes as an internal e-business intelligence system. Think about what
information may be of value to which customers.
• Build it to scale.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
One typical form of Information
embassy :
Supply chain ExtraNets
SCE : connects an organization with its supply chain partners. The goal is to provide
access to information that allow materials to flow smoothly and efficiently along an
organization business ecosystem.
Planning and
R&D
Procurement
Manufacturing
Order
Fulfillment
Service and
Support
Enterprise Value-Chain
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Various implementation strategies
E-Buy
Department of Manufacturing Engineering
and Engineering Management
ERP
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
E-Sell
City University
of Hong Kong
Various implementation strategies
E-Buy
E-Buy
ERP
E-Sell
E-Sell
E-Buy
Department of Manufacturing Engineering
and Engineering Management
ERP
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
ERP
E-Sell
City University
of Hong Kong
Various implementation strategies
E-Buy
ERP
E-Sell
ERP
E-Buy
E-Sell
E-Buy
ERP
E-Sell
E-Sell
Department of Manufacturing Engineering
and Engineering Management
ERP
E-Buy
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Various implementation strategies
ERP
Department of Manufacturing Engineering
and Engineering Management
ERP
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
ERP
City University
of Hong Kong
Various implementation strategies :
BI approach
E-Buy
ERP E-Sell
suppliers
customers
Extranet
Data marts
Extranet
OLAP
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Digital or e-marketplace
Sellers
Hub
Buyers
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
Digital or e-marketplace
• It takes the notion of an extranet one step further, by seeking to tie together the
supply chain of a large number of companies within an industry.
• Propose to improve the tradition supply chain with economic of scale and array of
choices that a single company cannot match.
• The e-marketplace generate huge qualities of data that is valuable to all
stakeholders.
• Therefore supply chain extranet can be built on top of e-marketplace.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong
References
• Knowledge Creating Company : how Japanese companies create the dynamics of
innovation
by Ikujiro Nonaka and Hirotaka Takeuchi, Oxford University Press, 1995.
• Knowledge Management Toolkit: Practical techniques for building a Knowledge
Management System
by Amrit Tiwana, Prentice Hall, 2000.
• Turning Information into Knowledge into Profit : e-Business Intelligence
by Bernard Liautaud, et al. McGraw Hill Press, 2001.
• E-business and ERP: Transforming the Enterprise
by Grant Norris, James R. Hurley, et al. Wiley Press, 2000.
Department of Manufacturing Engineering
and Engineering Management
Dr. Ricky Yeung, Lab. Manager, Jan., 2001
City University
of Hong Kong