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From Information to Knowledge Management: The role of IT. Dr. Ricky Yeung Laboratory Manager Dept. Manufacturing Engg. & Engg. Management City University of Hong Kong President, Institute of Industrial Engineers (HK) Email: merickyy@cityu.edu.hk. From Data to Knowledge.

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slide1

From Information to Knowledge Management:

The role of IT

Dr. Ricky Yeung

Laboratory Manager

Dept. Manufacturing Engg. & Engg. Management

City University of Hong Kong

President, Institute of Industrial Engineers (HK)

Email: merickyy@cityu.edu.hk

from data to knowledge
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

slide3

Information

5C’s to convert Data to Information

Contextualization

Condensation

Categorization

Calculation

Correction

Data

slide4

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.

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

Definition of Knowledge

Actionable information is knowledge

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

Knowledge Management
what km is not
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-to-reward 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.
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.
Two categories of Knowledge

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.

slide9

Socialization

Externalization

Tacit -> Tacit

Tacit -> Explicit

E

S

I

C

Internalization

Combination

Tacit <- Explicit

Explicit <- Explicit

KM strategy - the Nonaka’s SECI model

slide10

I

I

I

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

slide11

G

I

I

I

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

slide12

G

C

G

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

slide13

C

G

I

Internalization : E to T

  • Collective Knowledge Networks
  • Notes Database / Org Memory
  • Pattern Recognition
  • Neural Networks

C: Company knowledge

G: Group or Team knowledge

I: Individual knowledge

slide14

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

ü ü

ü ü

ü

ü ü

ü

ü

ü ü

E - Explicit/Codificable T- Tacit/Needs Explication

slide15

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

ü ü

ü ü

ü

ü

ü ü

ü ü

ü ü

ü ü

E - Explicit/Codificable T- Tacit/Needs Explication

slide16

4 stages of knowledge leverage

Care-Why

Know-Why

Knowledge management

system supported

Know-How

Know-What

Current State of Most Companies

Desirable

Knowledge Stage

- by James Brian Quinn

Initial

Level of

Knowledge

Leveragibility

Desirable

slide17

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.

slide18

Role of IT: a leveraged infrastructure

Enterprise KM

Network

Information Sources

Information Mapping

Information and Knowledge Exchange

Repository

Distributed Search

Distributed Retrieval

Models

Viewing Tools

Knowledge Flows

Multimedia Content

Distribution Channels

Collaborative Annotation

Web Sites, Pointers

Versioning Controls

Enterprise Data

Context Addition

Databases

Metadata

Bulletin Boards

Messaging Integration

Messaging

PM Tools

Informal Conversation

Legacy Integration

File Systems

Check In/Out

Operational Data

Threading

Legacy Systems

External Networks

Transaction Reports

Platform Independence

Workflow

Collaborative Tools

Discussions

Intelligent Agent and Network Mining

Push Agents

Web Farming Technologies

Pull Agents

Information Indexing and Classification

Data and Text Mining

Information Clustering and Lumping

slide19

Web

Conferencing

Expertise

Pointers

Transparent

Capture Tools

e.g.Crosspads

Workflow

Document

Management

Telephones

Routing

Electronic

Conversion

Informal

Capture

Dialog

Conversation

Routing

Control

Distribution

Informal

Conversation

Making

Knowledge Management

Technologies

Project

Management

Watercoolers

Activities

Conversation

Distribution

Connectivity

Publishing

Problem Solving

Operational Data

Knowledge discover

Validation

Cleansing

Brainstorming

Tacit Knowledge

Capture

Decision

Support Systems

Case-based Reasoning

Collaboration

Intranets

Digital

Whiteboards

GroupWare

Notes

Data

Warehouse

Data Mining

Internal Capture

Independent Thought

Mind Maps

Visual Thinking Tools

Document Exchange

Data Cleansing

Collaboration

Validating

slide20

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 know-how, 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.
slide21

A closer look of Information Management

Socialization

Anarchy

Democracy

Can be a good first step to empower your employees to know-how and know-why. It can be achieved by establishment of Information Democracy.

Control

Access

slide22

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.
slide23

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.

slide24

Information value chain

Value

Within the Enterprise

Outside of the Enterprise

Usage

First Return on Information

Data Liability

Information

Merchandising

Business

Extension

Crossing

Boundaries

slide25

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
slide26

OLTP

Such as ERP/

legacy system

ETL

Extraction/

Transformation/

Loading

Data Marts

Data mining

OLAP

Business Intelligence/

ad hoc query/analysis

Trend/pattern prediction

A simplified model for information empowerment

slide27

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
slide28

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
slide29

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
slide30

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
slide31

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.
slide32

Planning and

R & D

Order

Fulfillment

Service and

Support

Procurement

Manufacturing

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.

Enterprise Value-Chain

slide33

ERP

E-Buy

E-Sell

Various implementation strategies

slide34

ERP

ERP

ERP

E-Buy

E-Buy

E-Buy

E-Sell

E-Sell

E-Sell

Various implementation strategies

Third Party

slide35

ERP

ERP

ERP

ERP

E-Buy

E-Buy

E-Buy

E-Buy

E-Sell

E-Sell

E-Sell

E-Sell

Various implementation strategies

slide36

ERP

ERP

ERP

Various implementation strategies

slide37

ERP

E-Buy

E-Sell

Various implementation strategies :BI approach

suppliers

customers

Data marts

Extranet

Extranet

OLAP

slide38

Sellers

Hub

Buyers

Digital or e-marketplace

slide39

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.
slide40

References

  • Knowledge Creating Company : how Japanese companies create the dynamics of innovation
  • byIkujiro 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.