1 / 40

Dr. Ricky Yeung Laboratory Manager Dept. Manufacturing Engg. & Engg. Management City University of Hong Kong Preside

From Information to Knowledge Management: The role of IT. Dr. Ricky Yeung Laboratory Manager Dept. Manufacturing Engg. & Engg. Management City University of Hong Kong President, Institute of Industrial Engineers (HK) Email: merickyy@cityu.edu.hk. From Data to Knowledge.

rowdy
Download Presentation

Dr. Ricky Yeung Laboratory Manager Dept. Manufacturing Engg. & Engg. Management City University of Hong Kong Preside

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. From Information to Knowledge Management: The role of IT Dr. Ricky Yeung Laboratory Manager Dept. Manufacturing Engg. & Engg. Management City University of Hong Kong President, Institute of Industrial Engineers (HK) Email: merickyy@cityu.edu.hk

  2. From Data to Knowledge Data is just a set of particular and objective facts about an event or the structured record of a transaction. Data has little use by itself unless converted into information. Data should not be stored into a system for managing knowledge; it should be stored as value-added information - by the addition of historical context. Information is just data endowed with relevance and purpose. - by Peter Drucker

  3. Information 5C’s to convert Data to Information Contextualization Condensation Categorization Calculation Correction Data

  4. 5C’s to convert Data to Information Condensed Data is summarized in more concise form and unnecessary depth is eliminated. Contextualized we know why the data was collected. Calculated Analyzed data, similar to condensation of data. Categorized The unit of analysis is known. Corrected Errors have been removed, missing “data holes: have been accounted for.

  5. Knowledge is a fluid mix of framed experience, values, contextual information, expert insight and grounded intuition that provides an environment and framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms. - by Thomas Davenport and Laurence Prusak Definition of Knowledge Actionable information is knowledge

  6. Knowledge Management is thus the management of knowledge. It enables the creation, communication, and application of knowledge of all kinds to achieve business goals. - by Paul Quintas Knowledge Management is the ability to create and retain greater value from core business competencies. - by Kirk Klasson Knowledge Management addresses business problems particular to your business - whether it is creating and delivering innovative products or services; managing and enhancing relationships with existing and new customers, partner, and suppliers; or administering and improving work practices and processes - by Amrit Tiwana Knowledge Management

  7. What KM is not ? • KM is not knowledge engineering. KM is more a business and cultural problems. It needs to take care of people, information systems and management. • KM is about process, not just digital networks. IT is just one of the biggest enabler for effective KM. KM needs a knowledge culture driven by a performance-linked-to-reward system to encourage knowledge sharing. • KM is not about building a “smarter” intranet. Intranet is just a good front-end that provides a stable messaging and collaboration platform. • KM is not about one-time investment. It involves a continuous process of measure, audit, review, and so on. • KM is not about “capture”. Most of the knowledge cannot be captured, only information can be captured.

  8. Tacit knowledge is personal, context-specific knowledge that is difficult to formalize, record, or articulates. It is stored in the heads of people. The tacit component is mainly developed through a process of trial and error encountered in practice. • Belief, norms, experience, values, etc. Two categories of Knowledge Explicit knowledge is that component of knowledge that can be codified and transmitted in a systematic and formal language : documents, databases, webs, e-mail, etc.

  9. Socialization Externalization Tacit -> Tacit Tacit -> Explicit E S I C Internalization Combination Tacit <- Explicit Explicit <- Explicit KM strategy - the Nonaka’s SECI model

  10. I I I Socialization : T to T • Face-to-face Communications • Video Conferencing Tools • Web Cams • Virtual Reality Tools C: Company knowledge G: Group or Team knowledge I: Individual knowledge

  11. G I I I Externalization : T to E • Process Capture Tools • Traceability • Reflective Peer-to-Peer networks • Expert System • Discussion Platform C: Company knowledge G: Group or Team knowledge I: Individual knowledge

  12. G C G Combination : E to E • Systemic Knowledge Tools • Collaborative Computing Tools • Intranets, GroupWare • Discussion Lists • Web Forums • Best Practice Database C: Company knowledge G: Group or Team knowledge I: Individual knowledge

  13. C G I Internalization : E to T • Collective Knowledge Networks • Notes Database / Org Memory • Pattern Recognition • Neural Networks C: Company knowledge G: Group or Team knowledge I: Individual knowledge

  14. Typical source of Knowledge Source E T Employee knowledge, skills, and Competencies Experiential knowledge (both at an individual and group level) Team-based collaborative skills Informal shared knowledge Values Norms Beliefs ü ü ü ü ü ü ü ü ü ü ü E - Explicit/Codificable T- Tacit/Needs Explication

  15. Typical source of Knowledge Source E T Task-based knowledge Knowledge embedded in physical systems Human capital Knowledge embedded in internal structures Knowledge embedded in external structures Customer capital Experiences of the employee Customer relationship ü ü ü ü ü ü ü ü ü ü ü ü ü ü E - Explicit/Codificable T- Tacit/Needs Explication

  16. 4 stages of knowledge leverage Care-Why Know-Why Knowledge management system supported Know-How Know-What Current State of Most Companies Desirable Knowledge Stage - by James Brian Quinn Initial Level of Knowledge Leveragibility Desirable

  17. 4 stages of knowledge leverage Know-what :This is the fundamental stage where the organization makes use of IT of some kinds to collect, gather and store the cognitive type of knowledge. In simple words, they just know what they know, but don’t mean that they know when and how to apply such knowledge solve their problem. Know-how:It represents the ability to translate bookish knowledge into real world results. In this stage, they know when to use which knowledge to solve real-world, complex problems. Know-why :It goes beyond the know-how stage where they can use known rules and apply them well. In addition, they have in-depth knowledge of the complex slush of cause-and-effect relationships that underlie. This knowledge enables individuals to move a step above know-how and create extraordinary leverage by using knowledge, bringing in the ability to deal with unknown interactions and unseen situations. Care-why :It represents self-motivated creativity that exists in a company. This happens to be the only level that cannot be supported by knowledge management system.

  18. Role of IT: a leveraged infrastructure Enterprise KM Network Information Sources Information Mapping Information and Knowledge Exchange Repository Distributed Search Distributed Retrieval Models Viewing Tools Knowledge Flows Multimedia Content Distribution Channels Collaborative Annotation Web Sites, Pointers Versioning Controls Enterprise Data Context Addition Databases Metadata Bulletin Boards Messaging Integration Messaging PM Tools Informal Conversation Legacy Integration File Systems Check In/Out Operational Data Threading Legacy Systems External Networks Transaction Reports Platform Independence Workflow Collaborative Tools Discussions Intelligent Agent and Network Mining Push Agents Web Farming Technologies Pull Agents Information Indexing and Classification Data and Text Mining Information Clustering and Lumping

  19. Web Conferencing Expertise Pointers Transparent Capture Tools e.g.Crosspads Workflow Document Management Telephones Routing Electronic Conversion Informal Capture Dialog Conversation Routing Control Distribution Informal Conversation Making Knowledge Management Technologies Project Management Watercoolers Activities Conversation Distribution Connectivity Publishing Problem Solving Operational Data Knowledge discover Validation Cleansing Brainstorming Tacit Knowledge Capture Decision Support Systems Case-based Reasoning Collaboration Intranets Digital Whiteboards GroupWare Notes Data Warehouse Data Mining Internal Capture Independent Thought Mind Maps Visual Thinking Tools Document Exchange Data Cleansing Collaboration Validating

  20. Wrap up : points to remember • Collaborative synergy and support : KM needs to support collaboration, knowledge sharing, learning and continuous improvement. • Real knowledge, not artificial intelligence : no more about capturing smartest employee’s knowledge in a knowledge base or expert system. • Conversation as a medium for thought : free, unrestricted, and easy conversation must be supported. • Sources and originators, not just information : make it easy to find sources of know-how, locate people and expertise. • The golden rule : KM is built around people. • Decision support : be enhanced by historical perspective that KM support. • Pragmatism, not perfection : begin with what you have, and then incrementally improve it. • The user is king : ability of end users to define and control interaction with numerous sources of information.

  21. A closer look of Information Management Socialization Anarchy Democracy Can be a good first step to empower your employees to know-how and know-why. It can be achieved by establishment of Information Democracy. Control Access

  22. A survey in 1998 in US/UK • 88% of managers use gut feeling over 75% of time for making business decision • 93% of them are under pressure to make effective decisions with short timespans. • 62% of them do not receive right information to make decision, yet 99% have access to desktop computer. • 100% of sales and marketing managers have to reply on other people for information. Only 25% of them believe that the information is up-to-date. • Company directors are intolerant of decisions made by managers based on gut feeling, insisting that decisions should be made only on hard facts.

  23. Democratization and business value • Influenced by three key factors :- • level of democratization within the organisation : the ratio of business intelligence enabled used out of the total number of desktops. • level of empowerment : the number of users entitled to perform ad hoc requests for data versus the number of total users. • level of cultural propensity : the number of different departments that are involved in the deployment of the solution times the capacity to get access to other departments’ information. The greater these levels, the bigger the value of an organisation‘s business intelligence.

  24. Information value chain Value Within the Enterprise Outside of the Enterprise Usage First Return on Information Data Liability Information Merchandising Business Extension Crossing Boundaries

  25. Information value chain • Data liability zone: the number of users is limited to the IT staff, for maintenance purposes only. • First return of Information zone: business users can now access data about their own departmental activity. However, they still do not have access to the information about information which is part of another system in another division of the company. • The enterprise Intelligence zone: company opens a department‘s business intelligence to other departments or divisions. This requires a culture of information sharing. Ultimately, it will reach a state of Information Democracy where a collective intelligence is being built through open communication and willingness to share data. • The Extended Enterprise zone: the first extension of data access beyound the organisation‘s four wall to an external constitutent (such as suppliers, customers, or partners). Towards Information Embassy. • Information Merchandising zone: Selling data to new types of customers via Intelligent Extranets

  26. OLTP Such as ERP/ legacy system ETL Extraction/ Transformation/ Loading Data Marts Data mining OLAP Business Intelligence/ ad hoc query/analysis Trend/pattern prediction A simplified model for information empowerment

  27. From Information Democratization to Information Embassy • Empowerment of your suppliers and customers like your employees • use of Extranet deployment to create 3 new applications areas • Supply chain extranet • CRM extranet • Information brokerage extranet

  28. Information Embassy by e-business Intelligence ExtraNets • Empower your customers, suppliers and partners, hust as empower your employees • Motivation • from e-commerce to e-business • lots of information to share • a needs for transparency : enables customers to access and analyze the data through browsers • a requirement for performance : your suppliers need to have instant access to information that only their customer own • a key enabler for competitiveness • traditional paper reports • arrive an important delay • costly to print • static

  29. Benefit of Information Embassy • Create competitive advantage thtrough differentiation from competitors • Help your customer save money • Improve customer satisfaction • Build customer loyalty and “lock-in” • improving your own lot : force good, consistent information • Reduce costs for generation paper and electronic reports and supplying them to customers • Generate a new revenue stream

  30. Challenges of Information Embassy • Worry that customers can use newly available information to their advantages (short term effect) • how much functionality to offer • basic reporting is mandatory • ad hoc query/multi-dimensional analysis • does not suffering from degraded response times

  31. Ingredients for success • Make it a partnership • an opportunity for the customer to contribute to the quality of information relevant to both parties. Extranet welcome the opportunity to promptly correct errors and omissions. • make it functional, make it secure • ensure that customers see only their own personal data. Balance the desirability for a speedy deployment with the need to assess and select appropriate software tools and infrastructure built to last. • think creatively , be inclusive • Building an information embassy involves many of the same fundamental processes as an internal e-business intelligence system. Think about what information may be of value to which customers. • Build it to scale.

  32. Planning and R & D Order Fulfillment Service and Support Procurement Manufacturing One typical form of Information embassy : Supply chain ExtraNets SCE : connects an organization with its supply chain partners. The goal is to provide access to information that allow materials to flow smoothly and efficiently along an organization business ecosystem. Enterprise Value-Chain

  33. ERP E-Buy E-Sell Various implementation strategies

  34. ERP ERP ERP E-Buy E-Buy E-Buy E-Sell E-Sell E-Sell Various implementation strategies Third Party

  35. ERP ERP ERP ERP E-Buy E-Buy E-Buy E-Buy E-Sell E-Sell E-Sell E-Sell Various implementation strategies

  36. ERP ERP ERP Various implementation strategies

  37. ERP E-Buy E-Sell Various implementation strategies :BI approach suppliers customers Data marts Extranet Extranet OLAP

  38. Sellers Hub Buyers Digital or e-marketplace

  39. Digital or e-marketplace • It takes the notion of an extranet one step further, by seeking to tie together the supply chain of a large number of companies within an industry. • Propose to improve the tradition supply chain with economic of scale and array of choices that a single company cannot match. • The e-marketplace generate huge qualities of data that is valuable to all stakeholders. • Therefore supply chain extranet can be built on top of e-marketplace.

  40. References • Knowledge Creating Company : how Japanese companies create the dynamics of innovation • byIkujiro Nonaka and Hirotaka Takeuchi, Oxford University Press, 1995. • Knowledge Management Toolkit: Practical techniques for building a Knowledge Management System • by Amrit Tiwana, Prentice Hall, 2000. • Turning Information into Knowledge into Profit : e-Business Intelligence • by Bernard Liautaud, et al. McGraw Hill Press, 2001. • E-business and ERP: Transforming the Enterprise • by Grant Norris, James R. Hurley, et al. Wiley Press, 2000.

More Related