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Knowledge management simple secret of sucessful
Seta A. Wicaksana is a psychologist who works at Humanika Consulting. She has several roles including being a senior advisor at BPJS Ketenagakerjaan and deputy dean at the Faculty of Psychology at Pancasila University. She founded Humanika Consulting and writes books. She develops psychological assessment tools and trains, counsels, and assesses clients. She also teaches at Pancasila University and is pursuing her doctorate there in human resource management.
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Knowledge management simple secret of sucessful
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- 2. Seta A. Wicaksana,M.Psi., Psikolog 0811 19 53 43 wicaksana@humanikaconsulting.com • Ahli Senior di Komite Kebijakan Pengelolaan Kinerja Organisasi dan SDM (KPKOS) Dewan Pengawas BPJS Ketenagakerjaan • Wakil Dekan II Fakultas Psikologi Universitas Pancasila • Pembina Yayasan Humanika Edukasi Indonesia • Pendiri dan Direktur Humanika Consulting • Penulis Buku “SOBAT” Elexmedia Gramedia 2016 • Trainer, Psikolog, Konselor Karir dan Assessor di Humanika Consulting • Pengembang Alat Tes minat bakat BRIGHT dan Sistem Tes Psikologi berbasis aplikasi HITS dan HABIT • Narasumber di Radio DFM 103,4FM • Dosen Tetap Fakultas Psikologi Universitas Pancasila • Sedang mengikuti tugas belajar Doktoral (S3) di Fakultas Ilmu Ekonomi dan Bisnis Universitas Pancasila Bidang MSDM • Lulusan Fakultas Psikologi S1 dan S2 Universitas Indonesia • Lulusan sekolah ikatan dinas Akademi Sandi Negara
- 3. "I wish weknew what we know…“
- 5. Background The move froman industrially-based economy to a knowledge or information-based one in the 21st Century demands a top-notch knowledge management system to secure a competitive edge and a capacity for learning.
- 6. Background • The newsource of wealth is knowledge, and not labor, land, or financial capital. It is the intangible, intellectual assets that must be managed. • The key challenge of the knowledge-based economy is to foster innovation.
- 8. Background Knowledge Influences Success: •Peter Drucker (the one factor) • Toffler (Survival in Knowledge Age is not who can read or write but who can learn and unlearn quicker) • Nonaka (the cutting edge) • Tom Peters (sum total of value-added) • Handy, Drucker (primary factor of productivity)
- 10. From Data toWisdom
- 11. Data Information, andKnowledge • Data = collection of facts, measurements, statistics • Information = organized data • Knowledge = contextual, relevant, actionable information – Strong experiential and reflective elements – Dynamic – Branches and fragments with growth – Difficult to estimate impact of investment – Evolves over time with experience Informationthat changes somethingor somebody— becoming grounds for action by making an individual, or institutioncapable of different, moreeffectiveaction Drucker,The New Realities
- 12. What is Knowledge •A justified true belief (Nonaka and Takeuchi) • It is different from data & information • Knowledge is at the highest level in a hierarchy with information at the middle level, and data to be at the lowest level • It is the richest, deepest & most valuable of the three • Information with direction, i.e., leads to appropriate actions
- 13. Value of Data,Information, & Knowledge H T H T T H H H T H … T T T H T pH = 0.40 pT = 0.60 RH = +$10 RT = -$8 nH = 40 nT = 60 InformationData Zero Low Medium High Very High Value Knowledge (approximation only) EV = -$0.80 Counting pH = nH/(nH+nT) pT = nT/(nH+nT) EV=pH RH+ pT RT
- 18. Beyond Knowledge • Knowledge– the know how – actionable information – e.g., Increasing the production capacity before “lebaran” each year to handle the extra sales volume; • Wisdom – the know why – e.g., why there is increasing sales volume just before “Lebaran”? – inclination to adjust
- 20. Relating Data, Information,Knowledge to Events Knowledge InformationData Information System Decision Events Use of information Knowledge actions Decision Support System
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- 22. Procedural vs DeclarativeKnowledge • Declarative knowledge (substantive knowledge) focuses on beliefs about relationships among variables – e.g., moon is round, Peter get married with Susan – round(moon), married(Peter, Susan) • Procedural knowledge focuses on beliefs relating sequences of steps or actions to desired (or undesired) outcomes – Run a lecture: take attendance, open PPT, … – Flowcharts – Procedure manuals
- 24. Explicit Vs Tacit Explicit knowledge Objective, rational, technical Policies,goals, strategies, papers, reports Codified Leaky knowledge Tacit knowledge Subjective, cognitive, experiential learning Highly personalized Difficult to formalize Sticky knowledge e.g.,E=mc2 e.g.,don’tdiveon thatislandwhensomethingwrong(tsunami’s coming) We can convert explicit knowledge to tacit knowledge or vice versa
- 25. General vs SpecificKnowledge • General knowledge is possessed by a large number of individuals and can be transferred easily across individuals – E.g. operating MS Windows • Specific knowledge, or “idiosyncratic knowledge,” is possessed by a very limited number of individuals, and is expensive to transfer – E.g. writing programs for MS Windows Question: How about “Installing MS Windows”?
- 26. Technically vs Contextually SpecificKnowledge • Technically specific knowledge is deep knowledge in a specific application domain – e.g, information technology, financial investment, etc. • Contextually specific knowledge refers to the knowledge of particular circumstances of time and place in which work is to be performed – E.g., work knowledge in a particular organization
- 27. Different Types ofKnowledge How does this related to RM / ECM?
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- 29. Knowledge Discovery • Developmentof new tacit or explicit knowledge –from data and information –or from the synthesis of prior knowledge • 2 main ways –Combination –Socialization
- 30. Knowledge Discovery: Combination •The process of synthesizing explicit knowledge - create new, more complex sets of explicit knowledge • multiple bodies of explicit knowledge • also involve data and information • incremental – e.g., “new” proposal • radical – e.g., data mining
- 31. Knowledge Discovery: Socialization •The process of synthesis of tacit knowledge across individuals • usually through joint activities instead of written or verbal instructions • E.g. chatting about how to find a good job • Facilitation by technologies – Groupware – Web 2.0 – forums, chat-room, face-book…
- 32. Knowledge Capture • Theprocess of retrieving either explicit or tacit knowledge that resides within people, artifacts, or organizational entities. • Knowledge captured might reside outside the organizational boundaries, including consultants, competitors, customers, suppliers, and prior employers of the organization’s new employees. • Externalization vs Internalization
- 33. Externalization vs Internalization •Externalization – converting tacit knowledge into explicit forms such as words, concepts, visuals, or figurative language. • Internalization – conversion of explicit knowledge into tacit knowledge. – traditional notion of “learning”. – E.g., after reading a book, you learn in your mind Discussion: How does IT help? Can you relate this to our main case study?
- 34. Knowledge Sharing • theprocess through which explicit or tacit knowledge is communicated to other individuals. • effective transfer - so that the recipient of knowledge can understand it well enough for actions. • may take place across individuals, groups, departments or organizations. • Knowledge is shared (internalized) and not recommendations (no internalization occurs) based on knowledge. • Socialization vs Exchange.
- 35. Knowledge Sharing: Socialization •focuses on the sharing of tacit knowledge among individuals, groups, and organizations • e.g., talking to a senior year student about how to finish your degree course with minimal amount of effort in the orientation camp. • e.g., apprenticeships Note: one may also use socialization to synthesize tacit knowledge for knowledge discovery.
- 36. Knowledge Sharing: Exchange •focuses on the sharing of explicit knowledge. • communicate or transfer explicit knowledge between individuals, groups, and organizations. • e.g., passing a computer manual from one to another. Discussion: How does IT help? Can you relate this to our main case study?
- 38. Knowledge Application • Theprocess of applying explicit or tacit knowledge to carry out some tasks. • The knowledge may have been internalized (exist in one’s mind) or not (e.g., work according to a manual). • Direction vs Routines.
- 39. Direction • Individuals possessingthe knowledge direct the action of another individual without transferring to that person the knowledge underlying the direction. • E.g., calling the help desk to solve your PC problems. • Experts’ knowledge embedded in knowledge-base, expert systems and decision support systems. • Troubleshooting systems based on the use of technologies like case-based reasoning.
- 40. Routines • involve theutilization of knowledge embedded in procedures, rules, and norms that guide future behavior. • economize on communication more than directions because they are embedded in procedures or technologies. • e.g., inventory management system for automatic re-ordering. • general information systems and automation helps: – Enterprise resource planning systems – Management information systems … Discussion: How does IT help? Can you relate this to our main case study?
- 41. KM Solutions (Summary) KMProcesses KM Mechanisms KM Infrastructure KM Technologies Organization Culture Analogies and metaphors Brainstorming retreats On-the-job training Face-to-face meetings Apprenticeships Employee rotation Learning by observation …. IT Infrastructure Common Knowledge ExternalizationCombination RoutinesSocialization Exchange DirectionInternalization Knowledge Capture Knowledge Sharing Knowledge Application Decision support systems Web-based discussion groups Repositories of best practices Artificial intelligence systems Case-based reasoning Groupware Web pages … Physical Environment Organization Structure Knowledge Discovery KM Systems Knowledge Capture Systems Knowledge Sharing Systems Knowledge Application Systems Knowledge Discovery Systems
- 42. Learning and Givingfor Better Indonesia