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DATA Facts about situation Neutral Right data should be collected Data should be updated regularly Raw material extracted from environment Cash register Aero plane traveling Cooking a cake Contextualized Structured Categorized Condensed When we add something to data Information Assign value to data Transformation Decision making Problem solving A Find and send easily C Format and organize T Current for up-dated decisions Complete understanding Of Information Absorb information Filter Experience Beliefs Brought up Capabilities Useful actions Problem solving Decision making Information + Personal know-how Knowledge Dynamic Ever changing Why not static ? Based on non-static things 20th Century Information + Know-how 21st Century Information + Know-how Know-how ? Creation of value form information Types of knowledge Expressed knowledge What we know we know Car owner’s manual Travelers guide Formulas, methodologies, documents Expressible knowledge What we know we know but not noted Family business secrets Know - what ( How things work ) Know - what ( How things work ) + Know - what ( How things work ) + Know - who ( Experts ) Inexpressible knowledge What we know that can’t be noted Where it is present ? Minds of people Changing information Changing information + Expertise Changing information + Expertise = Best solution Hat Ribbon Knowledge assets Knowledge assets Data Knowledge assets Data Information Knowledge assets Data Information Expressed knowledge Knowledge assets Data Information Expressed knowledge Expressible knowledge Knowledge assets Data Information Expressed knowledge Expressible knowledge Inexpressible knowledge Management ? Knowledge assets Convert information into knowledge ? Apply knowledge For Value addition and competitive advantage ? Knowledge Management Historical overview Historical overview Master to apprentice in ancient times. Historical overview Master to apprentice in ancient times. Aristotle. Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Data storages Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Data storages. Artificial intelligence. ( speech, language ) Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Data storages. Artificial intelligence. ( speech, language ) Expert systems. (cloning of human reasoning ) Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Data storages. Artificial intelligence. ( speech, language ) Expert systems. (cloning of human reasoning ) Neural networks ( input-output pathways ) Historical overview Master to apprentice in ancient times. Aristotle. Nonaka. Data storages. Artificial intelligence. ( speech, language ) Expert systems. (cloning of human reasoning ) Neural networks ( input-output pathways ) Information explosion. SCM Production Apply knowledge to what we already do Innovation Apply knowledge to what is new Information handlers Information handlers Knowledge workers (solve problems + Add value ) Work harder Work harder Work smarter KM ( Hibbard 1997 ) Gathering firm’s collective expertise KM ( Hibbard 1997 ) Gathering firm’s collective expertise Data bases KM ( Hibbard 1997 ) Gathering firm’s collective expertise Data bases Books KM ( Hibbard 1997 ) Gathering firm’s collective expertise Data bases Books Processes KM ( Hibbard 1997 ) Gathering firm’s collective expertise Data bases Books Processes People’s minds KM ( Hibbard 1997 ) Gathering firm’s collective expertise Data bases Books Processes People’s minds Distribute to places for biggest payoff. KM ( Sveiby2000 ) Art of creating value KM ( Sveiby2000 ) Art of creating value From company’s intangible assets KM ( Brooking 1996 ) Accumulating knowledge assets KM ( Brooking 1996 ) Accumulating knowledge assets Use effectively for competitive advantage. Why KM now ? Time span of competitive advantage Type writers High speed of information Two faces of i explosion 300 million pages on Internet ( 1999 ) 300 million pages on Internet ( 1999 ) 1 billion pages on Internet (2002) Knowledge is key value added in products and services Knowledge values more than physical assets Tobin’s Q formula GM’s = $30 billion ( 2000 ) GM’s = $30 billion ( 2000 ) GM’s = $405 billion ( 1999 ) MS = $361 billion ( 2000 ) MS = $361 billion ( 2000 ) MS = $37 billion ( 2000 ) Total value Total value – Tangible assets Total value – Tangible assets = Knowledge asset Globalization Today’s business world not dealing with Consumers Prosumer Prosumer Aware of their needs Prosumer Aware of their needs Active Prosumer Aware of their needs Active Give feed back No more knowledge hoarding Early retirements Early retirements Rapid job changes Early retirements Rapid job changes Tense working environment Early retirements Rapid job changes Tense working environment Downsizing Roots of KM Roots of KM Business Roots of KM Business Economics Roots of KM Business Economics Psychology Roots of KM Business Economics Psychology Information KM involves KM involves People KM involves People Processes KM involves People Processes Technology KM processes Creation of knowledge KM processes Creation of knowledge Distribution of knowledge KM processes Creation of knowledge Distribution of knowledge Application of knowledge Existence before use Creation of knowledge Existing resources Fostering environment Packages Acquire Buy Mergers Social networks Distributing knowledge Good distribution system Good distribution system Early finding Good distribution system Early finding Proper packaging Good distribution system Early finding Proper packaging Timely delivery Early finding Locate the source Documents Processes People Proper packaging Right form Right context Regional Cultural Functional Enable employee to find what he needs Timely delivery Push technology Push technology Avoid over loading Pull technology Pull technology Avoid extra information Application of knowledge Medicine The Holy Quran Application Is Creation of value Puzzle Proper shape Easy to understand Compatible with work environment Motivated employee Suits employees job requirement Requirements Aligned with Company’s objectives Educate employees Tacit knowledge 50% to 95% Fuel for Innovation & Creativity engine Only competitive advantage in Unpredictable business environment Fish Vision without action Action without vision Vision with action can change the world Arthur Barker System analyst System analyst Knowledge developer Tacit knowledge Explicit knowledge Nonaka’s model of KC Nonaka’s model of KC Tacit to tacit communication ( socialization ) Discussions Nonaka’s model of KC Tacit to explicit communication ( externalization ) Brainstorming Nonaka’s model of KC Explicit to explicit communication ( communication ) Technology Nonaka’s model of KC Explicit to tacit communication ( internalization ) Deduce idea from report Evaluating expert Levels of expertise Levels of expertise Highly expert Levels of expertise Highly expert Moderate expert Levels of expertise Highly expert Moderate expert New expert Single experts More experts Understanding expert style Holding of sessions Understanding experience Language problem Type of interviews Arrangement of questions Reliability of information Response bias Inconsistency Ending the interview Other techniques On-site observation Brain storming Electronic brain storming Consensus decision making The Delphi method Concept mapping Black boarding Knowledge transfer Knowing-doing gap Atmosphere of trust Push reasoning before process Do than talk Tolerate mistakes for learning Cooperation & Collaboration Not Competition Asses job satisfaction Collective sequential transfer Explicit inter team transfer Internets Intranets Extranet B2B Chat rooms Video communication CRM Organizational learning Organizational learning Company’s collective ability To Organizational learning Company’s collective ability To Absorb information And Organizational learning Company’s collective ability To Absorb information And Learn from information RICE model RICE model Responsiveness RICE model Responsiveness Innovation RICE model Responsiveness Innovation Competency RICE model Responsiveness Innovation Competency Efficiency Creativity Emerges when existing solutions No longer serve the purpose Innovation Are responses to challenging problems