Unit-IV; Professional Sales Representative (PSR).pptx
Pierre emmanuel arduin slides - ewg-dss london-2011 workshop
1. From Knowledge Sharing
to Collaborative Decision Making
Pierre-Emmanuel Arduin
Michel Grundstein From Knowledge Sharing to EWG-DSS London
Collaborative
1 / 28 Rosenthal-Sabroux 24/06/2011
Camille Pierre-Emmanuel Arduin Decision Making
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 Ba
II. Case study
II.a Industrial context
II.b Reorganizing
II.c Linking with SECI and Ba
From Knowledge Sharing to Collaborative
2 / 28 Pierre-Emmanuel Arduin Decision Making
3. io n
n t
e te
R
dge
le
n ow
K
Collaborative Decision Making
From Knowledge Sharing to Collaborative
3 / 28 Pierre-Emmanuel Arduin Decision Making
4. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
KNOWLEDGE Intelligence SHARED
KNOWLEDGE
KNOWLEDGE Design SHARED
KNOWLEDGE
Choice
KNOWLEDGE SHARED
KNOWLEDGE
From Knowledge Sharing to Collaborative
4 / 28 Pierre-Emmanuel Arduin Decision Making
5. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
5 / 28 Pierre-Emmanuel Arduin Decision Making
6. I. Background theory and assumptions II. Case study
CDM | 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 Knowledge
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7. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
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8. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
IInternalization
explicit
to
tacit C
Combination
tacit explicit
to to
tacit explicit
S
Socialization tacit
to
explicit
Based on Ikujito Nonaka’s and Hirotaka Takeuchi’s works, 1995
E
Externalization
From Knowledge Sharing to Collaborative
8 / 28 Pierre-Emmanuel Arduin Decision Making
9. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
9 / 28 Pierre-Emmanuel Arduin Decision Making
10. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
1985
32,000
From Knowledge Sharing to Collaborative
10 / 28 Pierre-Emmanuel Arduin Decision Making
11. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
11 / 28 Pierre-Emmanuel Arduin Decision Making
12. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
12 / 28 Pierre-Emmanuel Arduin Decision Making
13. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
13 / 28 Pierre-Emmanuel Arduin Decision Making
14. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
Support
expert
Support center
Support
supplier
From Knowledge Sharing to Collaborative
14 / 28 Pierre-Emmanuel Arduin Decision Making
15. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
Support
expert
Support center
Support
supplier
From Knowledge Sharing to Collaborative
15 / 28 Pierre-Emmanuel Arduin Decision Making
16. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
? ? ??
? ?
From Knowledge Sharing to Collaborative
16 / 28 Pierre-Emmanuel Arduin Decision Making
17. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
Quality
expert
Competence center
Support
expert
Supplier Supplier
From Knowledge Sharing to Collaborative
17 / 28 Pierre-Emmanuel Arduin Decision Making
18. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
18 / 28 Pierre-Emmanuel Arduin Decision Making
19. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
19 / 28 Pierre-Emmanuel Arduin Decision Making
20. I. Background theory and assumptions II. Case study
CDM | Knowledge | SECI model | Ba Industrial context | Reorganizing | Linking with SECI and Ba
Active 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 Collaborative
20 / 28 Pierre-Emmanuel Arduin Decision Making
21. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
21 / 28 Pierre-Emmanuel Arduin Decision Making
22. I. Background theory and assumptions II. Case study
CDM | 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 Collaborative
22 / 28 Pierre-Emmanuel Arduin Decision Making
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 Collaborative
23 / 28 Pierre-Emmanuel Arduin Decision Making
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 Collaborative
24 / 28 Pierre-Emmanuel Arduin Decision Making