Introducing Knowledge Management

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Introducing Knowledge Management by Mind Map: Introducing Knowledge Management

1. 80% - Organizational processes and human factors 20% - Technology

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

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

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

4.1. Data Processing versus Knowledge-based Systems

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

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

7. Knowledge Discovery Systems

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

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

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

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

12. Knowledge as Key Resource

13. What is Knowledge Management (KM)?

14. driving forces

14.1. Diminishing Individual Experience

14.2. Increasing Domain Complexity

14.3. Accelerating Market Volatility

14.4. Intensified Speed of Responsiveness

15. Role of KM in today’s organization

16. Knowledge Management System (KMS)?

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

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

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

17. Classification of Knowledge Management Systems

17.1. Knowledge Capture Systems

17.2. Knowledge Application Systems

17.3. Knowledge Sharing Systems

18. Effective Knowledge Management

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

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

19. Understanding Knowledge

19.1. Basic Knowledge-related Definitions

19.1.1. Common Sense

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

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

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

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

19.1.2. Fact

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

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

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

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

19.1.3. Heuristic

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

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

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

19.1.3.4. 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.

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

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

19.1.3.7. Heuristic Virus.

19.1.4. Knowledge

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

19.1.5. Intelligence

19.1.5.1. The capacity to acquire and apply knowledge

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

19.3. Data, Information and Knowledge

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

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

19.4. Types of Knowledge

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

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

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

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

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

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

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

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

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

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

19.6. Expert’s Reasoning Methods

19.6.1. Reasoning by analogy: relating one concept to another

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

19.6.3. Formal reasoning: using deductive or inductive methods

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

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

20. Human’s Learning Models

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

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