KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE · · 2016-03-02Manage Change and Rewards Structure Form...

KNOWLEDGE

MANAGEMENT SYSTEMS

LIFE CYCLE

Lecture Two

(Chapter 2, Notes;

Chapter 3, Textbook)

Chapter 3: Knowledge Management Systems Life Cycle

2-2

Motivation

For any task, from as simple as planning a trip, working on a maths problem,

The process involves a number of steps until you come up with a solution.

In developing a large software system used in industry, the process also follows a number of defined steps which are accepted as best practices by practitioners.


2-3

Motivation Cont

How many of you have taken a

programming unit either here or

elsewhere before?

What would be the steps you would take in completing a programming

assignment?


2-4

Motivation Cont

read the problem statement

mentally think about how to solve it

select a programming language (if decided, select what kind of data structures)

translate into program code

compile, run and test

modify if program doesn't function as expected

Satisfied!!


2-5

This week’s Topics

Challenges in building KM Systems

Compare CSLC and KMSLC

User’s vs. Expert’s Characteristics

Stages of KMSLC


2-6

CHALLENGES IN BUILDING KM

SYSTEMS

Culture— getting people to share knowledge

Knowledge evaluation— assessing the worth of knowledge

across the organization

Knowledge processing— documenting how decisions are

reached

Knowledge implementation— organizing knowledge and

integrating it with the processing strategy for final deployment


2-7

Conventional

System Life Cycle

Recognition of Need and

Feasibility Study

Logical Design (master

design plan)

Physical Design (coding)

Testing

Implementation (file

conversion, user training)

Operations and Maintenance

Functional Requirements

Specifications

Iterative

KM System

Life Cycle

Evaluate Existing

Infrastructure

Knowledge Capture

Design KMS Blueprint

Verify and validate the KM

System

Implement the KM System

Manage Change and

Rewards Structure

Form the KM Team

Post-system evaluation

versus

Iterative


2-8

Key Differences

Systems analysts deal with information from the user; knowledge developers deal with knowledge from domain experts

Users know the problem but not the solution; domain experts know both the problem and the solution

Conventional SLC is primarily sequential; KM SLC is incremental and interactive.

System testing normally at end of conventional system life cycle; KM system testing evolves from beginning of the cycle


2-9

Key Differences (cont’d)

Conventional system life cycle is process-drivenor “specify then build”

KM system life cycle is result-oriented or “start slow and grow”


2-10

Key Similarities

Both begin with a problem and

end with a solution

Both begin with information

gathering or knowledge capture

Testing is essentially the same

to make sure “the system is

right” and “it is the right system”

Both developers must choose

the appropriate tool(s) for

designing their respective

systems


2-11

Stages of KMSLCEvaluate Existing

Infrastructure

Knowledge Capture

Design KM Blueprint

Verify and validate the KM

System

Implement the KM System

Manage Change and

Rewards Structure

Form the KM Team

Post-system evaluation

Iterative Rapid

Prototyping


2-12

(1) Evaluate Existing

InfrastructureSystem justifications:

What knowledge will be lost

through retirement, transfer, or

departure to other firms?

Is the proposed KM system

needed in several locations?

Are experts available and

willing to help in building a KM

system?

Does the problem in question

require years of experience

and tacit reasoning to solve?


2-13

The Scope Factor

Consider breadth and

depth of the project within

financial, human resource,

and operational constraints

Project must be completed

quickly enough for users to

foresee its benefits

Check to see how current

technology will match

technical requirements of

the proposed KM system


2-14

Role of Strategic Planning

Risky to plunge into a KMS without strategy

Knowledge developer should

consider:

Vision

Resources

Culture


2-15

(2) Form the KM Team

Identify the key stakeholdersof the prospective KM system.

Team success depends on:

Ability of team members

Team size

Complexity of the project

Leadership and team motivation

Not promising more than can be realistically delivered


2-16

(3) Knowledge Capture

Explicit knowledge captured in repositories from various media

Tacit knowledge captured from company experts using various tools and methodologies

Knowledge developers capture knowledge from experts in order to build the knowledge base


2-17

Selecting an Expert

How does one know the expert is in fact an expert?

How would one know that the expert will stay with the project?

What backup should be available in case the project loses the expert?

How could we know what is and what is not within the expert’s area of expertise?


2-18

(4) Design the KM BlueprintThe KM blueprint addresses

several issues:

Finalize scope of proposed KM system with realized net benefits

Decide on required system components

Develop the key layers of the KM software architecture to meet company requirements

System interoperability and scalability with existing company IT infrastructure


2-19

(5)Testing the KM System

Verification procedure:

ensures that the system

has the right functions

Validation procedure:

ensures that the system

has the right output

Validation of KM

systems is not

foolproof


2-20

(6) Implement the KM System

Converting a new KM system into actual operation

includes conversion of data or files

also includes user training

Quality assurance is important, which includes checking for:

Reasoning errors

Ambiguity

Incompleteness

False representation (false positive and false negative)


2-21

(7) Manage Change and

Rewards Structure

Goal is to minimize

resistance to change

Experts

Regular employees

(users)

Troublemakers

Resistances via

projection, avoidance,

or aggression


2-22

(8) Post-system Evaluation

Assess system impact in terms of effects

on:

People

Procedures

Performance of the business

Areas of concern:

Quality of decision making

Attitude of end users

Costs of Knowledge processing and update


2-23

Key Questions

Has accuracy and timeliness of decision

making improved?

Has KMS caused organizational changes?

What are users’ reactions towards KMS?

Has KMS changed the cost of operating

the business?

Have relationships among users affected?

Does KMS justify the cost of investment?


2-24

End of Lecture 2


2-25

Basic Knowledge-Related

Definitions

Common

Sense

Inborn ability to sense, judge, or perceive

situations; grows stronger over time

Fact A statement that relates a certain element

of truth about a subject matter or a domain

Heuristic A rule of thumb based on years of

experience

Knowledge Understanding gained through experience;

familiarity with the way to perform a task;

an accumulation of facts, procedural rules,

or heuristics

Intelligence The capacity to acquire and apply

knowledge


2-26

Types (Categorization) of

Knowledge

Shallow (readily recalled) and deep(acquired through years of experience)

Explicit (already codified) and tacit (embedded in the mind)

Procedural (repetitive, stepwise) versus

Episodical (grouped by episodes)

Knowledge exist in chunks


2-27

What makes someone an

expert? An expert in a specialized area

masters the requisite knowledge

The unique performance of a knowledgeable expert is clearly noticeable in decision-making quality

Knowledgeable experts are more selective in the information they acquire

Experts are beneficiaries of the knowledge that comes from experience


2-28

1. Purpose

2. Statement of Scope & Objectives2.1 System functions

2.2 Users and characteristics

2.3 Operating environment

2.4 User environment

2.5 Design/implementation constraints

2.6 Assumptions and dependencies

3. Functional Requirements3.1 User interfaces

3.2 Hardware interfaces

3.3 Software interfaces

3.4 Communication protocols and interfaces

4. Nonfunctional Requirements4.1 Performance requirements

4.2 Safety requirements

4.3 Security requirements

4.4 Software quality attributes

4.5 Project documentation

4.6 User documentation


2-29

Users Versus ExpertsAttribute User Expert

Dependence on system High Low to nil

Cooperation Usually cooperative Cooperation not

required

Tolerance for ambiguity Low High

Knowledge of problem High Average/low

Contribution to system Information Knowledge/expertise

System user Yes No

Availability for system

builder Readily available Not readily available


2-30

Rapid Prototyping Process?

Build

a Task

Structure

a Task

Structure

the Problem

Make

Modifications

Reformulate

the Problem

Repeated

Cycle(s)

Repeated

Cycle(s)


2-31

User Interface(Web browser software installed on each user’s PC)

Authorized access control(e.g., security, passwords, firewalls, authentication)

Collaborative intelligence and filtering(intelligent agents, network mining, customization, personalization)

Knowledge-enabling applications(customized applications, skills directories, videoconferencing, decision support systems,

group decision support systems tools)

Transport(e-mail, Internet/Web site, TCP/IP protocol to manage traffic flow)

Middleware(specialized software for network management, security, etc.)

The Physical Layer(repositories, cables)

. . . . .

Databases Data warehousing

(data cleansing,

data mining)

Groupware

(document exchange,

collaboration)

Legacy applications

(e.g., payroll)

1

2

3

4

5

6

7

Layers of KM Architecture


2-32

Knowledge Capture and

Transfer Through Teams

Team performs

a specialized task

Knowledge

transfer

method

selected

Evaluate relationship

between action and

outcome

Outcome

Achieved

Knowledge

Developer

Knowledge

stored in a

form usable by

others in the

organization

Feedback


2-33

An illustration

Zero Low Medium High Very High

Value

InformationData

H T H T T

H H H T H

…

T T T H T

pH = 0.40

pT = 0.60

RH = +$10

RT = -$8

nH = 40

nT = 60EV = -$0.80

Knowledge

CountingpH = nH/(nH+nT)

pT = nT/(nH+nT)EV=pH RH+ pT RT


2-34

CHALLENGES IN BUILDING KM

SYSTEMS

Culture— getting people to share knowledge

Knowledge evaluation— assessing the worth of knowledge

across the organization

Knowledge processing— documenting how decisions are

reached

Knowledge implementation— organizing knowledge and

integrating it with the processing strategy for final deployment


2-35

Vision

Foresee what the business

is trying to achieve, how it

will be done, and how the

new system will achieve

goals


2-36

Resources

Check on the affordability of the

business to invest in a new KM

system


2-37

Culture

Is the company’s

political and social

environment open and

responsive to adopting

a new KM system?

KNOWLEDGE MANAGEMENT SYSTEMS LIFE CYCLE · · 2016-03-02Manage Change and Rewards Structure Form...

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