From Knowledge Sharing                    to Collaborative Decision MakingPierre-Emmanuel ArduinMichel Grundstein         ...
I. Background theory and assumptions     I.a Our vision of Collaborative Decision Making     I.b Our vision of Knowledge  ...
io n                               n t                         e   te                        R                dge         ...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba               Industrial context | Re...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba           Industrial context | Reorga...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba                   Industrial context ...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba                              Industri...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba         Industrial context | Reorgani...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba              Industrial context | Reo...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba     Industrial context | Reorganizing...
CDM          Background theory         Knowledge           and assumptions                                    The SECI mod...
Thank you for your kind attention                                     CDM          Background theory          Knowledge   ...
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Pierre emmanuel arduin slides - ewg-dss london-2011 workshop

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Pierre-Emmanuel Arduin slides - EWG-DSS London-2011 Workshop

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Pierre emmanuel arduin slides - ewg-dss london-2011 workshop

  1. 1. From Knowledge Sharing to Collaborative Decision MakingPierre-Emmanuel ArduinMichel Grundstein From Knowledge Sharing to EWG-DSS London Collaborative1 / 28 Rosenthal-Sabroux 24/06/2011Camille Pierre-Emmanuel Arduin Decision Making
  2. 2. I. Background theory and assumptions I.a Our vision of Collaborative Decision Making I.b Our vision of Knowledge I.c The SECI model I.d The concept of BaII. Case study II.a Industrial context II.b Reorganizing II.c Linking with SECI and Ba From Knowledge Sharing to Collaborative2 / 28 Pierre-Emmanuel Arduin Decision Making
  3. 3. io n n t e te R dge le n ow K Collaborative Decision Making From Knowledge Sharing to Collaborative3 / 28 Pierre-Emmanuel Arduin Decision Making
  4. 4. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and BaKNOWLEDGE Intelligence SHARED KNOWLEDGEKNOWLEDGE Design SHARED KNOWLEDGE ChoiceKNOWLEDGE SHARED KNOWLEDGE From Knowledge Sharing to Collaborative4 / 28 Pierre-Emmanuel Arduin Decision Making
  5. 5. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Sense–giving Sense–reading Externalization Internalization Structuring Interpreting Knowledge Knowledge Information Data Knowledge Knowledge Based on Shigehisa Tsuchiya’s works, 1993 From Knowledge Sharing to Collaborative5 / 28 Pierre-Emmanuel Arduin Decision Making
  6. 6. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Sense–reading Information Data Knowledge K Knowledge K Information Data Knowledge K KnowledgeK’ K Strong commensurability Low commensurabilitySharing to Collaborative From Knowledge6 / 28 Pierre-Emmanuel Arduin Decision Making
  7. 7. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba “ we can know more than we can tell ” Michael Polaniy, 1958 From Knowledge Sharing to Collaborative7 / 28 Pierre-Emmanuel Arduin Decision Making
  8. 8. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba IInternalization explicit to tacit C Combination tacit explicit to to tacit explicitSSocialization tacit to explicit Based on Ikujito Nonaka’s and Hirotaka Takeuchi’s works, 1995 E Externalization From Knowledge Sharing to Collaborative8 / 28 Pierre-Emmanuel Arduin Decision Making
  9. 9. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba IInternalization Ba explicit to tacit C Combination tacit explicit to to tacit explicit S Socialization tacit to explicit E Externalization Ikujito Nonaka and Ikujito Nonaka and Hirotaka Takeuchi, 1995 Noboru Konno, 1998 From Knowledge Sharing to Collaborative9 / 28 Pierre-Emmanuel Arduin Decision Making
  10. 10. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba 1985 32,000 From Knowledge Sharing to Collaborative10 / 28 Pierre-Emmanuel Arduin Decision Making
  11. 11. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba ? ?? Support Quality ? expert ?? expert Support center Quality center ? ?? Support Quality ?? ? supplier supplier From Knowledge Sharing to Collaborative11 / 28 Pierre-Emmanuel Arduin Decision Making
  12. 12. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba formalized rules Quality COBOL: Avoid large Programs expert - too many Lines of Code Quality center COBOL: Avoid Programs with High Cyclomatic Complexy Quality supplier From Knowledge Sharing to Collaborative12 / 28 Pierre-Emmanuel Arduin Decision Making
  13. 13. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Incidents’ file Support expert Statistics Pedagogic tool Support center Documentary base Support supplier From Knowledge Sharing to Collaborative13 / 28 Pierre-Emmanuel Arduin Decision Making
  14. 14. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Support expert Support center Support supplier From Knowledge Sharing to Collaborative14 / 28 Pierre-Emmanuel Arduin Decision Making
  15. 15. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Support expert Support center Support supplier From Knowledge Sharing to Collaborative15 / 28 Pierre-Emmanuel Arduin Decision Making
  16. 16. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba ? ? ?? ? ? From Knowledge Sharing to Collaborative16 / 28 Pierre-Emmanuel Arduin Decision Making
  17. 17. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Quality expertCompetence center Support expert Supplier Supplier From Knowledge Sharing to Collaborative17 / 28 Pierre-Emmanuel Arduin Decision Making
  18. 18. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba▪ Discuss: - The incidents - The decisions taken to solve them▪ Share Knowledge▪ Update the incidents’ file together From Knowledge Sharing to Collaborative18 / 28 Pierre-Emmanuel Arduin Decision Making
  19. 19. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba▪ Decide together: - The best way to solve the discussed incidents - What to insert into the incidents’ file From Knowledge Sharing to Collaborative19 / 28 Pierre-Emmanuel Arduin Decision Making
  20. 20. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and BaActive participation in incidents’ meetings, practice, repetition Internalization Socialization Combination To the new Externalization Incidents’ supplier meetings From Knowledge Based on Ikujito Nonaka’s and Hirotaka Takeuchi’s works, 1995 Sharing to Collaborative20 / 28 Pierre-Emmanuel Arduin Decision Making
  21. 21. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba▪ Weekly planned▪ Small meeting room▪ 1h30 → 2h Update Ba together From Knowledge Sharing to Collaborative21 / 28 Pierre-Emmanuel Arduin Decision Making
  22. 22. I. Background theory and assumptions II. Case studyCDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba Decisions: - Discussed in an incidents’ meetings - Obtained thanks to the incidents’ file - Alone elaborated but discussed later in an incidents’ meeting From Knowledge Sharing to Collaborative22 / 28 Pierre-Emmanuel Arduin Decision Making
  23. 23. CDM Background theory Knowledge and assumptions The SECI model The concept of Ba Industrial context Divided configuration Case study Incidents’ file Reorganizing Incidents’ meetings Linking with SECI and Ba From Knowledge Sharing to Collaborative23 / 28 Pierre-Emmanuel Arduin Decision Making
  24. 24. Thank you for your kind attention CDM Background theory Knowledge and assumptions The SECI model The concept of Ba Industrial context Divided configuration Incidents’ file Case study Reorganizing Incidents’ meetings Linking with SECI and Ba Related works ThinksLets, CSCW Perspective Measuring commensurability From Knowledge Sharing to Collaborative24 / 28 Pierre-Emmanuel Arduin Decision Making

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