The role of the Statistician in the Knowledge Based Economy IAOS Conference August 2002 Geoff Carss

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The role of the Statistician in the Knowledge
Based Economy  IAOS Conference August
2002Geoff CarssPrincipal, Knowledge
ManagementPublic Sector PracticeIBM Global
Servicese-mail geoff.carss_at_uk.ibm.comTel 44
(0)1252 558216
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Need for a new perspective

• New perspective to inform new thinking
• Particle Physics
• People thought that electrons were particles and
  so they looked for them and saw them
• then some people looked for waves and found
  waves
• Electrons are paradoxically waves and particles,
  you see what you look for

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The basis for current perspectives on the problem

• Descarte 17th Century
• Rational analysis
• .if we reduce complex and obscure propositions
  step by step to simpler ones.
• a(bc)
• Taylor 20th Century
• Reductionism/Scientific Management
• a b c
• Measurement of the Industrial Economy is based on
  reductionist quantitative analysis

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The knowledge based economy

• Move from labour and capital to knowledge and
  technology as key factors of production
• Global market for knowledge and innovation
• Global networks and relationships becoming a key
  factor in the economy
• Ability to create and sustain networks is a key
  driver in successful organisations

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Two key differences between the industrial and
knowledge based economy

• Managing cause and effect
• Increasingly difficult to relate cause and effect
• Planning and decision making
• Move from formal planning to informal consensus
  based direction
• Advocacy and story telling are key skills

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The Cynefin (Cun-ev-in) model
Knowable Analytical/Reductionist Sense Analyse
Respond Examples Communities, Scenario
Planning
Complex Pattern management Probe Sense
Respond Examples Economies
Known Legitimate best practice Sense - Categorise
Respond Examples Leading Practice, Standard
Operating Procedures
Chaos Turbulent and unconnected Act Sense
Respond Examples Crisis
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Complex space

• Emergent patterns
• Increasing information flow and connectiveness
• Realm of networks or communities
• Outcome is based on relationships of members
  trust and stories
• Use of statistics is to substantiate stories

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Conclusion

• Developing a new perspective can help inform
  understanding
• Where cause and effect can be meaningfully
  aligned then statistics can provide deep insights
  
• In knowledge based, network and global contexts,
  where cause and effect cannot be directly linked,
  statistics are used to build compelling stories
• so the role of the Statistician in the Knowledge
  based Economy to to help people tell great
  stories.

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Further reading

• www.ibm.com/services/cynefin