Introducing Knowledge Management

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Introducing Knowledge Management by Mind Map: Introducing Knowledge Management

1. For example, someone with common sense would know not to touch a red stove eye.

2. “Knowledge has become the key resource, …we need systematic work on the quality of knowledge and the productivity of knowledge

3. KM is important for organizations that continually face downsizing or a high turnover percentage due to the nature of the industry

4. Knowledge Sharing Systems

5. Knowledge Discovery Systems

6. Related to the concept of intellectual capital (both human and structural).

7. KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge

8. Knowledge management (KM) may be defined simply as doing what is needed to get the most out of knowledge resources.

9. Social/Structural mechanisms (e.g., mentoring and retreats, etc.) for promoting knowledge sharing.

10. Leading-edge information technologies (e.g., Web-based conferencing) to support KM mechanisms.

11. Knowledge management systems (KMS): the synergy between social/structural mechanisms and latest technologies

12. KM should not distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization

12.1. Learning by discovery: undirected approach in which humans explore a problem area with no advance knowledge of what their objective is

13. Procedural (repetitive, stepwise) versus Episodical (grouped by episodes or cases)

13.1. Data Processing versus Knowledge-based Systems

14. Knowledge as Key Resource

15. What is Knowledge Management (KM)?

15.1. KM focuses on organizing and making available important knowledge, wherever and whenever it is needed.

16. driving forces

16.1. Diminishing Individual Experience

16.2. Increasing Domain Complexity

16.3. Accelerating Market Volatility

17. Role of KM in today’s organization

18. Knowledge Management System (KMS)?

19. Classification of Knowledge Management Systems

19.1. Knowledge Capture Systems

19.1.1. Knowledge Application Systems

20. Effective Knowledge Management

20.1. Intensified Speed of Responsiveness

20.2. Knowledge is first created in the people’s minds.

20.3. 80% - Organizational processes and human factors 20% - Technology

20.4. KM practices must first identify ways to encourage and stimulate the ability of employees to develop new knowledge

21. Understanding Knowledge

21.1. Basic Knowledge-related Definitions

21.1.1. Common Sense

21.1.1.1. The knowledge and experience which most people already have, or which the person using the term believes that they do or should have

21.1.1.2. Some related concepts include intuitions, pre-theoretic belief, ordinary language, foundational beliefs, axioms, wisdom, folk wisdom, folklore, and public opinion.

21.1.1.3. "the basic level of practical knowledge and judgment that we all need to help us live in a reasonable and safe way“.

21.1.1.4. Common-sense ideas tend to relate to events within human experience and appear commensurate with human scale.

21.1.2. Fact

21.1.2.1. A fact (derived from the Latin factum) is something that has really occurred or is actually the case.

21.1.2.2. The usual test for a statement of fact is verifiability, which is whether it can be proven to correspond to experience.

21.1.2.3. Standard reference works are often used to check facts.

21.1.2.4. The most fundamental heuristic is trial and error, which can be used in everything from matching nuts and bolts to finding the values of variables in algebra problems.

21.1.2.5. Scientific facts are verified by repeatable experiments.:Sunrise and sunset.

21.1.2.6. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, or common sense.

21.1.3. Heuristic

21.1.3.1. Where the exhaustive search is impractical, heuristic methods are used to speed up the process of finding a satisfactory solution.

21.1.3.2. Heuristic ("find" or "discover") refers to experience-based techniques for problem solving, learning, and discovery.

21.1.3.3. If you are having difficulty understanding a problem, try drawing a picture.

21.1.3.4. Heuristic Virus.

21.1.4. Knowledge

21.1.4.1. Understanding gained through experience; familiarity with the way to perform a task; an accumulation of facts, procedural rules, or heuristics

21.1.5. Intelligence

21.1.5.1. If you can't find a solution, try assuming that you have a solution and seeing what you can derive from that ("working backward").

21.2. Data, Information and Knowledge

21.2.1. Data: Unorganized and unprocessed facts; static; a set of discrete facts about events

21.2.1.1. Information: Aggregation of data that makes decision making easier

21.3. Types of Knowledge

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

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

21.3.2.1. Explicit (knowing-that) knowledge: knowledge codified and digitized in books, documents, reports, memos, etc.

21.3.2.1.1. The capacity to acquire and apply knowledge

21.3.2.2. Tacit (knowing-how) knowledge: knowledge embedded in the human mind through experience and jobs

21.4. What makes someone an expert (knowledge worker)?

21.4.1. An expert in a specialized area masters the requisite knowledge

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

21.4.2.1. Knowledge is derived from information in the same way information is derived from data; it is a person’s range of information

21.4.3. Knowledgeable experts are more selective in the information they acquire

21.5. Expert’s Reasoning Methods

21.5.1. Experts are beneficiaries of the knowledge that comes from experience

21.5.2. Reasoning by analogy: relating one concept to another

21.5.3. Case-based reasoning: reasoning from relevant past cases

21.5.4. Formal reasoning: using deductive or inductive methods

21.5.4.1. Inductive reasoning: reasoning from a set of facts or individual cases to a general conclusion

21.5.4.2. Deductive reasoning: exact reasoning. It deals with exact facts and exact conclusions

22. Human’s Learning Models

22.1. Learning by experience: a function of time and talent

22.2. Learning by example: more efficient than learning by experience