Chapter 8 The Knowledge Management Platform Knowledge Processes

Chapter 8 The Knowledge Management Platform

Knowledge Processes and Technology Enablers n n n Objective Technology Enablers Find knowledge Create new knowledge Package and assembler knowledge Apply knowledge Employee skills yellow pages DSS Tools Customized discussion groups Reuse and revalidate knowledge Chapter 8 Search, retrieval, and storage tools to help classify both formal and informal knowledge Customer support knowledge bases, Co. P, past project record database �Knowledge Management 2

Seven Layers of KM Architecture Chapter 8 �Knowledge Management 3

KM Platform basic needs n Efficient Protocol : secure and fast sharing of content across locations, mobile clients n Portable operation : OS environment in different departments n n n Consistent and easy to use client interfaces Scalability Legacy integration from mainframe database Security Flexibility and customizability : in term of. . “What the user sees and needs to see” The lack of the end user’s ability to filter out the irrelevant content is the root cause of information overload. Chapter 8 �Knowledge Management 4

Web or Proprietary Platforms? Chapter 8 �Knowledge Management 5

Packaging Knowledge n n n Packaging : Filtering, editing, searching, and organizing pieces of knowledge. Knowledge must be packaging in such a way that it’s insightful, relevant, and useful. Allow the employee the time to Package Knowledge for future use to make content useful 1. 2. 3. 4. 5. Chapter 8 Identification : general domain Segmenting : target users Mass Customization : suit each audience Format : use indexes, groupings, and table of contents Tests : refine the steps to seek feedback �Knowledge Management 6

Knowledge Delivery n PULL Approach – User Choice : Users want the knowledge – “Go and Get” what users need to know n PUSH Approach – You want the users to have the knowledge – Noticeability – Ease of use : workgroup Chapter 8 �Knowledge Management 7

Knowledge Delivery n ALL – Suit for information management not KM – Data Slam : meaningless piece of data, difficult to navigate n Some – Useful, contextually applicable pieces n When to deliver the knowledge JIT “JUST IN TIME” : Better – JIC “JUST IN CASE” : Information not knowledge, – people ignore them, lack of action-ability that is not relevant to their immediate work Chapter 8 �Knowledge Management 8

Source and Feeds for Marketing KM Chapter 8 �Knowledge Management 9

Chapter 8 �Knowledge Management 10

Data Warehouse in the KM Infrastructure Chapter 8 �Knowledge Management 11

Data Warehouse in the KM Infrastructure Data representing, such as hypercube data model in multiple dimensions, help in supporting decision making with concrete data from the past. n A data warehouse is of little use unless the data is converted to meaningful information and applied when needed. n Chapter 8 �Knowledge Management 12

GA Based Tools in the KM Technology Framework Chapter 8 �Knowledge Management 13

GA Based Tools in the KM Technology Framework Genetic Algorithms are based on Charles Darwin’s theory of natural selection. n “I don’t know how to build a good solution, but I will know it when I see it” n Chapter 8 �Knowledge Management 14

Neural Network in the KMS Architecture Chapter 8 �Knowledge Management 15

Neural Network in the KMS Architecture A neural network is a networked computing architecture in which a number of processors are interconnected like the neurons in a human brain that can learn through trial and error. n n. NN has their root of biology. n. Preprocess Chapter 8 data, cleaning up data, training data �Knowledge Management 16

Neural Network Chapter 8 �Knowledge Management 17

Rule-Based Systems in the KM Infrastructure Chapter 8 �Knowledge Management 18

Rule-Based Systems in the KM Infrastructure n n If. . . . then. . . . else. . Work well when 1. The rules do not overlap 2. You know the variables in your problem 3. You can express them quantitatively Chapter 8 �Knowledge Management 19

Case-Based Reasoning in KM Chapter 8 �Knowledge Management 20

Case-Based Reasoning in KM Each attribute is assigned some weight, based on previous experience or existing knowledge. Cases that are closest matches to the case at hand are then retrieved. n Chapter 8 �Knowledge Management 21

Case-based reasoning Chapter 8 �Knowledge Management 22

Applications of Various Intelligence Tools in a KM Platform Chapter 8 �Knowledge Management 23

Chapter 8 �Knowledge Management 24

A Comparison of Intelligence Tools Chapter 8 �Knowledge Management 25

Level of Increasing Granularity in a KM System Representing the System’s Depth of Detail Chapter 8 �Knowledge Management 26

Customer Support and Knowledge levels Chapter 8 �Knowledge Management 27

Tagging Attributed for Knowledge Content in a KM system Chapter 8 �Knowledge Management 28

Form Attributed n paper n electronic n formal (file, word document, spreadsheet) n informal (multimedia, sound, video tape) n tacit or mental knowledge pointer (to person who has solved a problem of that nature before) n Chapter 8 �Knowledge Management 29

Type Attributed n procedure n memo n guideline n failure report n protocol n success report n manual n press report n reference n competitive n worst practice report n best practice report n note Chapter 8 intelligence report �Knowledge Management 30

Product and Service Attributed n Strategic consulting n Implementation consulting n e-commerce consulting Chapter 8 �Knowledge Management 31

Systems Commonly Confused with Customer KM Platform Chapter 8 �Knowledge Management 32

Application Layer in the KM Platform Chapter 8 �Knowledge Management 33

The Application Layer n Pointer to expertise – Electronic yellow pages n Document Management is not the focus of KM initiative. – Convert only those pieces of information that are needed. n Multimedia , Video Clip – A picture is worth a thousand words. n Microsoft Net. Meeting Conference Software – 28000 desktop users at 250 sites around the world – No inconsistent documents n Virtual Meeting Chapter 8 �Knowledge Management 34

Peer-to-peer networking peer-to-peer networking support KM because it is closely mirrors face-to-face communication n peer-to-peer networking is defined as sharing resources by direct exchange between individual systems in a digital network n 1. it must rapidly get the right people involved n 2. it enable them collectively to apply their expertise n Chapter 8 �Knowledge Management 35

Peer-to-peer networking Network of friends and their friends n Automatically pass on question, Stop when 1. run out of time 2. one of the peer confirms having matching expertise Chapter 8 �Knowledge Management 36

SECI Model and IT support Chapter 8 �Knowledge Management 37

Discussion Group Chapter 8 n 1. What is Knowledge in your company? n 2. Tagging attributed for your knowledge Content. (Activity, Domain, Form, Type, Product/Service, Time, Location) p. 28 -31. n 3. Define what are pull technology and push technology in your KM system. p. 7 Chapter 8 �Knowledge Management 38

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