1. Understanding Knowledge
Lecture One

2. Introducing Knowledge Management
Lecture One

3. Objectives What is Knowledge Management (KM)?
What are the driving forces?
Role of KM in today’s organization
What is Knowledge Management System (KMS)?
Classification of Knowledge Management Systems
Effective Knowledge Management
First, I will overview the objectives for Part 1 of today’s lecture.
First, definition.
Second, need.
Third, function.
Fourth, put in practice.
Fifth, different manifestations.
Sixth, factors important to effective KMS.
First, what is knowledge management? Some of you might have previewed the lecture notes or the prescribed textbook, or just off the top of your head, what do you think Knowledge management is and what it involves?
[Ask one to two students]
Here, we want to understand what KM is and what are the driving forces behind KM projects/initiatives in today’s organization (big or small). In other words, the needs that KM is trying to address.
We hear about data management, or information management, and now Knowledge management? In terms of levels, knowledge is at the highest that is essential for decision making. It is more than simply data or information.
Second, we want to discuss the main issues that organizations will face when they consider the adoption of KM.
Third, we want to understand what constitute a KMS and its role and the functions it will provide to an organization.
Fourth, we will discuss the relevance of KM in today’s dynamic business environments that are fueled by the advancement of technologies.
Finally, we will consider both benefits and concerns when developing KM projects from an IT perspective.
KMS is not simply looking at the technical issues like we do in information processing systems. It involves people, including the experts, the knowledge developers, the users and of course importantly the management. Has anyone heard about a term CKO (Chief Knowledge Officer)? He is the one who is in a managerial position overseeing the management of organizational knowledge for the benefit and growth of the organization.

4. Knowledge Management - Motivation
“The 20th anniversary of the landing of an American on the surface of the Moon occasioned many bittersweet reflections. Sweet was the celebration of the historic event itself... Bitter, for those same enthusiasts, was the knowledge that during the twenty intervening years much of the national consensus that launched this country on its first lunar adventure had evaporated...” [Fries,S. 1992].
Copyright  NASA, Apollo 11 mission
First, just want to use a real world example to demonstrate importance of KM.
Here is an excerpt, taking out from an article written in 1992 by Fries, who is a historian with NASA (National Aeronautics and Space Agency) in USA, entitled NASA Engineers and the Age of Apollo.
What do you think is the sentiment of Fries just from reading this brief excerpt of the article? Do you think there would be people who shared his views?
[One to two students]
Here, Fries expressed a deep regret on the fact that if KM had been introduced in the management of the Space’s project at NASA, the wealth of knowledge that were accumulated in those who were involved in the expedition (or project) would not have been lost.
This has a bit of irony here. We might have thought that NASA, being the headquarter of US’s space project and the origin of many breakthroughs in science and technologies would have the capability to retain the vast amount of knowledge that was generated behind their successful space mission. But, as Fries’ study found out, the reality is most of these knowledge that should have been captured and retained were somehow lost when those who were involved retired, moved on to other opportunities, etc.
Having said that, one might have thought that some of those knowledge must have been documented one way or another in notebooks, records that have been used by those who were involved. Even if that would be true, trying to uncover, dig out and pull together these disparate sources of information now will incur magnitudes of efforts that could have been done when a suitable mechanism for systematic KM were in place from the start.
Seeing from the NASA example and its ramifications, it would not be reasonable to consider “knowledge” as not
just something abstract, intangible, but the presence/absence of relevant knowledge can facilitate …
[Ask the students from the attendance sheet] Referring to the NASA example, what areas might you think the knowledge would be helpful in?

5. Knowledge as Key Resource
“Knowledge has become the key resource, for a nation’s military strength as well as for its economic strength… is fundamentally different from the traditional key resources of the economist – land, labor, and even capital…we need systematic work on the quality of knowledge and the productivity of knowledge … the performance capacity, if not the survival, of any organization in the knowledge society will come increasingly to depend on those two factors” [Drucker,1994]
What is Drucker saying here? What are the main points he wanted to make in this excerpt?
[One to two students]
What are the differences between the traditional view of key resources that economist has and the view that is being presented here by Drucker?
Distinguish from traditional key resources of the economist – land, labor, and even capital.
Another excerpt, taken from a 1994 article written by an expert in KM, emphasized the importance of knowledge as a key resource to both the performance and survival of the modern organization.

6. What is Knowledge Management?
Knowledge management (KM) may be defined simply as doing what is needed to get the most out of knowledge resources.
KM focuses on organizing and making available important knowledge, wherever and whenever it is needed.
KM is also related to the concept of intellectual capital.
So, What is knowledge management?
Can someone give it a try, to say what is KM in your opinion?
[One to two students]
After second statement, turn to [1] clip [Read] Discuss.
After third statement, turn to [2] & [3] clip [Read] Discuss.
(Microsoft example; intellectual capital includes both human and structural capital.

7. Forces Driving Knowledge Management
Increasing Domain Complexity: Intricacy of internal and external processes, the rapid advancement of technology.
Accelerating Market Volatility: The pace of change, or volatility, within each market domain has increased rapidly in the past decade.
Intensified Speed of Responsiveness: The time required to take action based upon subtle changes within and across domains is decreasing.
Diminishing Individual Experience: High employee turnover rates have resulted in individuals with decision-making authority having less tenure within their organizations than ever before.
If you were in a decision-making process as to whether KM should be introduced into your organization,
what would the relative weights you might place on these driving forces? Why?
[One to two students]
Clip [4]
As a manager who is to decide on whether to introduce KM in your organization, what are the relative weights you might place on these driving forces? Why?
Take a few minutes to think about this? And share.

8. Role of KM in Today’s Organization
KM is important for organizations that continually face downsizing or a high turnover percentage due to the nature of the industry.
It’s clear here that increased domain complexity, accelerating market volatility, intensified speed of responsiveness are mainly market forces due to fierce competition, here in this illustration here, the “diminishing individual experiences” faced by most managers (I shouldn’t say younger) is an important “human resource” driving force for lack of a better word behind KM in organizations.
Facilitate today’s younger manager to make the tough decisions daily needed

9. What is Knowledge Management “Systems” ?
Social/Structural mechanisms (e.g., mentoring and retreats, etc.) for promoting knowledge sharing.
Leading-edge information technologies (e.g., Web-based conferencing) to support KM mechanisms.
Knowledge management systems (KMS): the synergy between social/structural mechanisms and latest technologies.

10. Classification of Knowledge Management Systems
Knowledge Discovery Systems
Knowledge Capture Systems
Knowledge Sharing Systems
Knowledge Application Systems
Artificial Intelligence and Machine Learning technologies play an important part (or role) in the processes of knowledge discovery, knowledge capture, knowledge sharing and knowledge application, enabling the development of KM systems.
Although we will not dwell into each of these systems in depth, the concepts and techniques discussed in this unit constitute some of the elements in building these KMS.

11. Effective Knowledge Management (1)
80% - Organizational processes and human factors
20% - Technology
PEOPLE
TECHNOLOGY
ORGANIZATIONAL
PROCESSES
OVERLAPPING FACTORS
So, there are several important points about Effective KM or KMS, is 80% organization processes and human factors and only 20% technology.

12. Effective Knowledge Management (2)
Knowledge is first created in the people’s minds.
KM practices must first identify ways to encourage and stimulate the ability of employees to develop new knowledge.

13. Effective Knowledge Management (3)
KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge.

14. Effective Knowledge Management (4)
KM should not distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization.

15. Review of Last Lecture What is Knowledge Management (KM)?
What are the driving forces?
Role of KM in today’s organization
What is Knowledge Management System (KMS)?
Classification of Knowledge Management Systems
Effective Knowledge Management
First, I will overview the objectives for Part 1 of today’s lecture.
First, definition.
Second, need.
Third, function.
Fourth, put in practice.
Fifth, different manifestations.
Sixth, factors important to effective KMS.
First, what is knowledge management? Some of you might have previewed the lecture notes or the prescribed textbook, or just off the top of your head, what do you think Knowledge management is and what it involves?
[Ask one to two students]
Here, we want to understand what KM is and what are the driving forces behind KM projects/initiatives in today’s organization (big or small). In other words, the needs that KM is trying to address.
We hear about data management, or information management, and now Knowledge management? In terms of levels, knowledge is at the highest that is essential for decision making. It is more than simply data or information.
Second, we want to discuss the main issues that organizations will face when they consider the adoption of KM.
Third, we want to understand what constitute a KMS and its role and the functions it will provide to an organization.
Fourth, we will discuss the relevance of KM in today’s dynamic business environments that are fueled by the advancement of technologies.
Finally, we will consider both benefits and concerns when developing KM projects from an IT perspective.
KMS is not simply looking at the technical issues like we do in information processing systems. It involves people, including the experts, the knowledge developers, the users and of course importantly the management. Has anyone heard about a term CKO (Chief Knowledge Officer)? He is the one who is in a managerial position overseeing the management of organizational knowledge for the benefit and growth of the organization.

16. In this Lecture Basic Knowledge-related Definitions
Data, Information and Knowledge
From Data Processing to Knowledge-based Systems
Types of Knowledge
Knowledge – An Attribute of Expertise

17. Basic Knowledge-Related Definitions
Common Sense
Fact
Heuristic
Knowledge
Intelligence
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

18. Basic Knowledge-Related Definitions
Common Sense
Innate ability to sense, judge, or perceive situations; grows stronger over time
Fact
Heuristic
Knowledge
Intelligence
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

19. Basic Knowledge-Related Definitions
Common Sense
Innate 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
Knowledge
Intelligence
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

20. Basic Knowledge-Related Definitions
Common Sense
Innate 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
Intelligence
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

21. Basic Knowledge-Related Definitions
Common Sense
Innate 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
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

22. Basic Knowledge-Related Definitions
Common Sense
Innate 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
Can anyone give me an example of each?
[3 to 4 students]
Do you see the differences?

23. Data, Information, and Knowledge
Data: Unorganized and unprocessed facts; static; a set of discrete facts about events
Information: Aggregation of data that makes decision making easier
Knowledge is derived from information in the same way information is derived from data; it is a person’s range of information
Note the level becomes more abstract as we go from data, to information, and to knowledge.
It is the knowledge that we have that enables us to make decisions.

24. Relationship between data, information and Knowledge
Zero
Low
Medium
High
Very High
Value
Knowledge

25. An illustration Zero Low Medium High Very High Knowledge Counting Data
Value
Information
Data
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 = 60
EV = -$0.80
Knowledge
Counting
pH = nH/(nH+nT)
pT = nT/(nH+nT)
EV=pH RH+ pT RT

26. Relating Data, Information, and Knowledge to Events
System
Decision
Events
Use of
information

27. How do we make sense of this pyramid?
Can someone give it a try?
What do we mean by algorithmic and non-algorithmic?
How comes data are much easier to program than for information, knowledge and even wisdom?

28. 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
Shallow vs. deep (necessary to make decision/solve problem in complex situations)

29. Explicit and Tacit Knowledge
Explicit (knowing-that) knowledge: knowledge codified and digitized in books, documents, reports, memos, etc.
Tacit (knowing-how) knowledge: knowledge embedded in the human mind through experience and jobs

30. Illustrations of the Different Types of Knowledge

31. Knowledge As An Attribute of Expertise
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

32. Expert’s Reasoning Methods
Reasoning by analogy: relating one concept to another
Formal reasoning: using deductive or inductive methods
Case-based reasoning: reasoning from relevant past cases

33. Deductive and inductive reasoning
Deductive reasoning: exact reasoning. It deals with exact facts and exact conclusions
Inductive reasoning: reasoning from a set of facts or individual cases to a general conclusion

34. Human’s Learning Models
Learning by experience: a function of time and talent
Learning by example: more efficient than learning by experience
Learning by discovery: undirected approach in which humans explore a problem area with no advance knowledge of what their objective is.

35. End of Lecture One