Multidisciplinary Teams and Knowledge Models

1. Multidisciplinary Teams and Knowledge Models Professor M Neil James Faculty of Technology University of Plymouth

2. Multidisciplinary Teams • MDT's harness powerful knowledge benefits from members • Advances in technology in different areas • New ideas • Cross-fertilisation of concepts from other disciplines • What knowledge do other people possess that the MDT is unaware of ? • Information retrieval/mining

3. Knowledge Pools • Standard business model – Bonsai tree • Fruit – saleable products • Trunk – core skills • Roots generic knowledge • Small and perfect • Not easily capable of growth • Expansion into new areas difficult

4. Knowledge Pools • Need to 'dip' into other knowledge pools • Innovative synergies • Ready-made problem solutions • New openings for growth and product range • Leads to the 'sequoia' model of business growth

5. Knowledge Pools • Sequoia can be 80-100 m high • Root system contained in top 1.5 m of soil • Spreads out over 4 square acres • Clone by suckers • Young trees use ancient root system of adults

6. Knowledge Pools • Young trees use ancient root system of adults • Share water resources • 'Dip' into each others pools • Share root linkage • Fast growth once water supply stabilised • New roots for mutual support

7. Knowledge Pools • Business analogy • Dipping into different knowledge bases • Mutative growth possible • Fundamental process 'keys' in nature

8. Knowledge Pools • Business analogy • Dipping into different knowledge bases • Mutative growth possible • Fundamental process 'keys' in nature • Mutation

9. Knowledge Pools • Business analogy • Dipping into different knowledge bases • Mutative growth possible • Fundamental process 'keys' in nature • Mutation • Replication (cloning)

10. Knowledge Pools • Equivalent 'keys' in business • Design innovation General Atomics Predator B unmanned aircraft

11. Knowledge Pools • Equivalent 'keys' in business • Design innovation • Smart fabrication

12. Role of Team Leaders • Manage problem constraints

13. Role of Team Leaders • Manage problem constraints • Coach and counsel team members

14. Role of Team Leaders • Manage problem constraints • Coach and counsel team members • Resolve conflicts

15. Role of Team Leaders • Manage problem constraints • Coach and counsel team members • Resolve conflicts • Attributes: • Forceful

16. Role of Team Leaders • Manage problem constraints • Coach and counsel team members • Resolve conflicts • Attributes: • Forceful • Goal orientated

17. Role of Team Leaders SAVE the WHALE In short, a caring Genghis Khan…..

18. Application to Design • MDT's drawn from several potential disciplines • Different interests • Different skills

19. Application to Design • MDT's drawn from several potential disciplines • Different interests • Different skills • Gain experience in information retrieval from different 'pools'

20. Application to Design • MDT's drawn from several potential disciplines • Different interests • Different skills • Gain experience in information retrieval from different 'pools' • Harness the internet as a data mining source • Image from Journal of Data Mining and Knowledge Discovery, Kluwer Academic Publishers • http://www.digimine.com/usama/datamine/

21. Application to Design • MDT's drawn from several potential disciplines • Different interests • Different skills • Gain experience in information retrieval from different 'pools' • Harness the internet as a data mining source • Develop conceptual thought processes

22. Application to Design • MDT's drawn from several potential disciplines • Different interests • Different skills • Gain experience in information retrieval from different 'pools' • Harness the internet as a data mining source • Develop conceptual thought processes • Develop skills in identifying critical areas in problems

23. Application to Design • Visualise the web of linkages between: • Modules

24. Application to Design • Visualise the web of linkages between: • Modules • Skills

25. Application to Design • Visualise the web of linkages between: • Modules • Skills • Disciplines

26. Application to Design • Visualise the web of linkages between: • Modules • Skills • Disciplines • Individual disciplines are all part of the overall field of engineering • Interlinked • Interdependent

27. What Might MDT's Achieve in the Future ? • Reduced product development times • Classic example is Liberty ship design • Riveted construction ~ 242 days • Welded construction < 7 days

28. What Might MDT's Achieve in the Future ? • Reduced product development times • Classic example is Liberty ship design • Riveted construction ~ 242 days • Welded construction < 7 days • Increased risk avoidance • Greater reliability • More holistic understanding of linkages/problems

29. What Might MDT's Achieve in the Future ? • Impact of network technologies • Information access • Real communication

30. What Might MDT's Achieve in the Future ? • Impact of network technologies • Information access • Real communication • Effective knowledge capture • Higher recycling potential • Lean and efficient materials usage

31. What Might MDT's Achieve in the Future ? • Impact of network technologies • Information access • Real communication • Effective knowledge capture • Higher recycling potential • Lean and efficient materials usage • 'Virtual' design and manufacturing environments • Game technology • Process modelling

32. What Might MDT's Achieve in the Future ? • Potential limitations • Shortage of multi-skilled MDT team leaders • Loss of social dimension • Cyber-nerds There is hope however……. http://romance.live.com.au/articles/index.jsp http://romance.live.com.au/articles/snaggies.jsp