Report on The Fortune Sellers

1
Report on The Fortune Sellers

• MIS 696a
• October 23, 2002

2
Order of Business

• Jack Introduction
• Jack The Second Oldest Profession
• Amit When Chaos Rains (The Weather)
• Mark The Dismal Scientists (Economics)
• Kelly The Market Gurus
• Surendra Checking the Unchecked Population
• Jason Science Fact Fiction
• Rong The Futurists
• Sherry Corporate Chaos
• Jack The Certainty of Living in an Uncertain
  World

3
Introduction

• Prognostication Inherent Human Need
• Can Also be Extremely Profitable
• Despite Scientific and Technological Advances,
  Experts Have Poor Track Record
  
• Future is Fundamentally Unpredictable - Chaos
  and Complexity Theories
  

4
Chapter 1 The Second Oldest Profession

• Economics
• Financial Services
• Technology
• Business Planning

• Weather
• Population
• Futurists
• Fortune Telling

5
Chapter 2 When Chaos Rains

• Weather Forecasting Chaos Theory
• The Interaction
• The Result
• Whats in for us as researchers?

6
Chaotic Weather in our lives

• 1588 storm destroyed Spanish ships English
  ruled
  
• Winter of 41-42 Germans could not win Soviet
  Union
  
• 70 A single cyclone drowned 200,000
  Bangladeshis
  
• Feb. 78 Disastrous blizzard struck New
  England
  
• Oct. 87 Worst storm to strike UK since 1703
• Aug. 91 US East Coast 1.5 billion loss
• 92 Hurricane Andrew 25 billion loss !!
• Mar. 93 winter storm accurate forecast by
  NWS
  
• Summer 93 worst flood in Mississippi River
  Valley

7
35 Billion Losses/year Due to Weather
8
Weather Forecasting

• Variables have we considered them all?
• Data is it precise?
• Top Forecasters
• UKs National Meteorological Office
• USs National Weather Service (NWS)

9
What is Chaos really?

• Order, Stability ?
• Disorder, Instability ?
• Zoom In smaller pieces of the system
• Total Disorder
• Zoom Out the system as a whole
• All possible behaviors

10
Mathematics of Chaos Theory

• Poincaré (1892) The Father of Mathematics of
  Chaos Theory
  
• Lorenz (1961) Revived the study of Chaos Theory
• Sensitive Dependence on Initial Conditions
• The Butterfly Effect
• Transitivity
• Order within Disorder
• Global Stability with Local Instability

11
Evaluating Weather Prediction

• If persistence or climatology forecasts are
  right most of the time, which they often are,
  then how smart does a forecaster have to be to be
  right most of the time Not very!
• So much fuss about measuring skill (improvement
  over some standard usually stupid forecasting
  method, such as random guessing, climatology or
  persistence), rather than accuracy!
• - Charles Doswell III, Meteorologist at NWS

12
Long Term Weather Forecasting

• Patterns are decieving
• Theres an almost infinite number of weather
  patterns that could result from any of the
  persistent environmental conditions or
  combinations of conditions.

13
Value of Weather Forecasting

• Forecasts have valuefrom the resources that are
  saved
  
• Savings in human lives alone justifies the 4
  billion spent on modernization
  
• 20 - 40 billion in saved property also
• But, no reason to spend on providing
  long-range forecasting
  Research should continue though

14
Learning for us as Researchers

• Need to understand Global Stability Breadth of
  the field
  
• Appreciate the Interdisciplinary Nature of
  Management Information Systems
  
• Small, but significant contribution
  can be a major revolution in the field

15
Learning for us as Researchers

• Beware of deceiving patterns its a chaotic
  world, things hardly ever repeat
  
• Long-term prediction is difficult
  Be best at short-term prediction,
  at the least
  appreciate our role as Fortune
  Sellers!!

16
Chapter 3 The Dismal Scientists

• Economic Forecasting
• Arguably, everything we care about is, in one way
  or another, economics....
  

17
Background

• Economists used to focus on the social sciences,
  the laws that govern government, commerce, and
  society.

18
The Leading Intellectuals of the 19th Century
were Economists

• Adam Smith
• John Stewart Mills
• Karl Marx

19
The Dismal Scientists, A Name that Stuck

• The Term Dismal Scientists comes from Thomas
  Malthuss treatise, An essay on the the
  ever-expanding human population and possible
  future ramifications
• Its been continued in use in part due to the
  terrible track record economists have in
  predicting the future

20
Everyone Wants to Predict the Economy, Most
Really Try
International
Corporations
Japan
European Governments
United States Government
21
The Problem with Forecasting the Economy

• Its not chaotic, just Complex!
• Its impossible to understand a starting Point
• Feed-back and Feed-forward loops
• Economic Forecasting has a dismal track record
• Cannot Predict Turning Points Economy
• Cannot beat the Naive forecast

22
And Economists Are Not Helping The Matter

• Economists forecast depending on their particular
  religion of economics.
  
• Many Economists treat forecasting as more of an
  arcane art then a scientific endeavor
  

23
The Ironic mix of Economics and Information
Science

• The funny thing about economics is that it
  requires so much information, even information
  science cant help it!
  
• Of course, it doesnt help that Economics doesnt
  have a full complement of natural laws, people
  act erratically, (although experimental economics
  is helping that).

24
Key Points on Forecasting the Economy

• The Economy is too complex to forecast
• Economists forecast anyway, with the expected
  dismal results
  
• What economists forecast often depends on their
  particular economic religion
  
• Part of the problem is a lack of accurate
  information, something information systems could
  theoretically assist with, but which in reality
  is beyond the scope of current technology.

25
Applying This to the Future of IS

• The utilization/impact of information systems is
  dependent upon the economic state of the
  companies seeking to implement them, which in
  turn depends on the general economy
• If the general economy cannot be forecast
  accurately, then the use and implementation of IS
  cannot be forecast accurately.

26
And Hence

• If the use of information systems cannot be
  forecast, then
  
• It is very difficult to determine future areas of
  beneficial research with any certainty.
  
• Work whose relevance is dependent upon forecasts
  should be eschewed for work which is
  forecast-independent whenever possible.

27
Chapter 4 The Market Gurus

• The Stock Market is a complex system
• Much like the economy, only faster
• A form of synthetic life with a brain composed
  of millions of minds
  
• Driven by the concept of self-interest

28
Predicting the Market

• Technicians

Vs.
Fundamentalists
29
Technicians

• Use historical price data to predict future
  trends
  
• Believe that the Market is driven by
  psychological momentum
  
• Use various techniques including charts, trend
  theories, and astrology

30
Fundamentalists

• Estimation of a stocks intrinsic value
• Determination of market over-value or under-value
  of the stock
  
• Assume a rise or fall in the price as proper
  value is attained
  

31
Problems with prediction

• Stock prices are random
• Corporate earnings growth is random
• Efficient Market Hypothesis
• Strong Market knows all
• Semi-strong Market knows almost all
• Weak Past stock prices cannot be used to
  predict future stock prices
  

32
15 Minutes of Fame
Roger Babson Crash of 1929
Elaine Garzarelli Black Monday
Joseph Granville Granville Market Letter
Robert Prechter Elliot Wave Theorist
33
The Value Line Enigma

• Predictions for 1800 stocks using timeliness
• Seems to defy the EMH
• Problems
• Requires transactions that are temporally
  infeasible
  
• Does not account for risk
• Not invincible, just enormously influential

34
Is the Market Rational?

• While rational forces drive the market toward
  its fair value, irrational forces of speculation
  and panic cause the market to diverge from
  rational value. These irrational forces give
  rise to explosive nonlinearities that make the
  market unpredictable.
• -p. 118

Speculation
Overvalued
Panic
Undervalued
35
Is Chaos the Key?

• Stock prices not precisely random. May exhibit
  some element of chaos
  
• Search for chaotic structure involves massive
  data mining (MIS!!!)
  
• Patterns, if existent, are so complex and deeply
  embedded that they are unlikely to be discovered

36
Implications for MIS

• MIS is a multidisciplinary field
• Shaped by expectations, rationalities, and
  irrationalities of practitioners and users across
  many disciplines
  
• Influenced by complex (and sometimes chaotic)
  interactions between people with divergent
  motives, intentions, aspirations, and visions of
  the future

37
Implications for Research

• Researchers must anticipate the bears and the
  bulls of the research market
  
• Researchers must be proactive, implicitly
  predicting the future by guiding the direction of
  the discipline
  
• Researchers must understand the needs,
  expectations, and motives of those who need and
  use their work
  

38
Research is Networking

• Research has a Substantive-Intellectual side and
  a Community side
  
• How well will your research fit certain social
  and political requirements of the research
  community
  
• Become valuable on the outside in order to become
  valuable on the inside
  
• Adopt a sound research strategy (i.e. the Porter
  Business Model)
  
• -Source Lee, Allen S. Researching is
  Networking Three Stories about How to Do
  Research

39
A way of conceptualizing IS Research as a System

• Research Culture
• values, norms, traditions
• editors, reviewers, colleagues
• tenure committees
• funding agencies

• Research Technology
• knowledgetheories, frameworks, concepts
• reasoning positivist, interpretive, critical,
  and other methods

the behavioral subsystem
the technological subsystem
the emergent interactions between the behavioral

subsystem and the technological subsystem
Source Lee, Allen S. Four Lessons for New
Information Systems Scholars,
Keynote address at the Doctoral Consortium of the
Pacific Asia Conference on Information Systems
(PACIS), Hong Kong SAR, China June 1, 2000.
40
MIS ResearcherAverage Lifespan 15 minutes

• Like the stock market, the MIS research domain is
  multifaceted, dynamic, and the product of a
  multitude of participants. As researchers, we
  can prolong our 15 minutes by identifying
  trends, actively working to shape the future,
  recognizing the community side of research, and
  developing a sound research strategy.

41
Chapter 5 Checking the Unchecked Population

• Why Predict the population?
• Factors that effect population
• Current prediction techniques and accuracy
• How can MIS help?

42
Why predict the population?

• Applications
• Infrastructure Planning
• Govt Policy
• Budgeting
• Marketing

• Parameters
• Growth rate
• Emigration
• Average age
• Male-Female ratio
• Health

43
Factors

• Economics
• Weather
• Political climate
• Culture
• War

• Emigration
• Health
• Male-Female ratio
• Growth rate
• Average age

44
Current status

• Forecasts quite accurate
• Prediction effect on predictions
• AIDS Case
• GM Food Case

45
How can MIS help?

• Databases
• Data mining, patterns
• Meaningful correlations
• Micro level planning

46
Implications for MIS Research

• Effect of external factors on MIS
• Economy
• Technology
• Culture
• Awareness and Diversification

47
MIS as an Interface
MIS
TECHNOLOGY
PEOPLE and ORGANIZATIONS
48
Chapter 6 Science ------ Right or Wrong??

• Computer program Virus
• Painkiller Drug
• Powder War
• Robot Enemy

49
Science and Human beings
50
Science Fiction

• the first seeds of the idea were shown by that
  great, fantastic author, Jules Verne
  
• --Konstantin Tsiolkovsky

51
Science Fiction Prediction

• Science fiction spawned science prediction
• Science prediction emerged as a specialized field
  in 1960s
  
• (H.G.Wells the Time Machine)

52

• 80 Science prediction failed

Much more promises New habitat Programmable drea
m Longer life expectancy Robot slave Out of b
lue Electricity Telephone Light bulb Cellular
telephone Compact disk
53
Science prediction---high-stakes

• 160 billion on research per year
• 2.5 million scientists involved
• 33 million patents and
• 1 million more each year
• 80 new products failed

54
Technological Darwinism Path
Unworkable Concepts
Unknown applications
Unproved Value
Chance event
Technological synergies
Creative destruction
Technological Lock-in
55
Unworkable Concepts

• First computers
• Hot fusion
• Superfluidity

56
Unknown Applications

• MASER Laser Fiber
  Optics

57
Unproved Value

• Market success depends on customers perception
  of value
  
• Nintendo

58
Technological Synergies
59
Technological Lock-In

• Win standard, win the game
• VHS vs Betamax
• Microsofts success

60
Chance Events

• World War II deferred semiconductors while
  hastening aerospace, nuclear power, radar
  

61
Where is MIS?

• Multiple, Interdisciplinary Science
• Young research domain also with unpredictable
  future
  
• Resolve the real-world problem

62
What should MIS researcher do?

• Everyday constructs the future
• Failure is the mother of success
• Sell powerful tools to Fortune Seller
• Doubt other results and try to synergies with
  other results
  

63
Chapter 7 The Futurists

• Futurists predict societal changes.
• Mission Impossible?

64
Are Social Changes Predictable?

• Society is a complex system that is affected by
  almost everything.
  
• All of these forces are unpredictable, then
  society itself must be unpredictable.
  
• There can be no prediction of the course of human
  history by scientific or any other rational
  methodsWe must reject the possibility of social
  science that would correspond to the theoretical
  physics. --------Karl Popper

65
Principles of Social Predictions

• History does not repeat itself.
• Major social trends, movements, and revolutions
  surprise those closest to the event.
  
• Social theories are necessarily weak and
  ephemeral in their application to social
  phenomena.
  
• Social predictions are subjective and
  accordingly, susceptible to situational bias,
  political agendas and wishful thinking.
  
• Social predictions tend to be wrong.

66
Whats Wrong in Futurology?

• Beliefs about futurology movement
• There is no single futures
• We can influence the future
• We have a moral obligation to use our capability
  to anticipate and to influence the future.

• However, it is not necessarily what futurists
  actually do.
  
• It will be. OR It can be.

67
Social Prediction Is Dangerous

• Evil side to social prediction
• The misuse of prophecy by demagogues to control
  the masses in order to achieve their master plan
  for society, which they claim is inevitable or
  inexorable.
• The cost of failed social programs can be immense.

68
Zhuge Liang ???

• The greatest Chinese wisdom,
• strategist, politician, inventor, futurist, and
• the earliest FORTUNE SELLER. (AD 200)
• ??????,??????
• Foretell(sell) the Three-Kingdom Era to Liu Bei,
  and became the military counselor premier of
  Shu Kingdom.

69
Fortune Seller And Buyer

• Futurists foretell and sell the societal trends
  to accomplish their political ambition.
  

• Political leaders choose and buy the appropriate
  and promising Fortune as their direction.
  

Yes! Thats my direction!
70
Question?

• The future is unpredictable.
• Shall we predict or not?
• And how?

71
What should we do in research?

• Review others ideas with suspect.
• Be sensitive of details and chances.
• Be adaptable of the uncertainty.
• Base our research on firm scientific theory and
  model.
  
• Action is more important than prediction.
• Sell and promote our ideas.

72
What else?

• Lets introduce Zhuge Liangs brother.

73
Post Zhuge Liang ?????

• Originally, Post Zhuge Liang is a person who
  always say I told you or You should have
  
• For example, CIA after 9/11

74
Do We Need Post Zhuge Liang?

• Yes, we do!!!
• Future is never independent with the past.
• We cannot make sound prediction without
  understanding the past experience, no matter
  success or failure.
  
• How to collect, integrate and analyze the
  information?
  
• MIS can help us.

75
Chapter 8 Corporate Chaos

• History of corporate planning
• 1970 GE had a planning department staffed
  with193 planners
  
• BCGs growth share matrix

76
More recently

• Management idea
• Strategy Space a two dimension grid
• 1990 Reengineering
• Why planning and forecasting
• Foresight gives a company potentials

77
Organization is unpredictable

• A complex system
• Highly interacted
• Irrational decision making
• Lack sufficient information
• Have faulty memories
• Cant expect laws of management
• Formulas are not useful

78
Organization is not directly controllable

• Attempt to control unintended results
• Cant control innovation
• Innovation comes naturally
• Control stifles innovation
• Self-organization
• Flexibility at the lowest level

79
Future

• Anything is possible
• Future possibility bounded by the present
  reality
  

80
Opportunity

• Two type of opportunities
• Type I conventional wisdom
• More obvious
• Type II breakthrough
• A discontinuity, an innovation, a quantum leap
• Hard to see

81
Vision

• Discover type II opportunities
• Future not fixed entity
• What can be done today?
• Shape the future by vision, courage and wisdom

82
Guideline 1 - Self-organization

• Give authority, skills, and freedom to employees
  at all levels to their jobs
  
• Applications in our teaching activities
• Are the students self-organized?
• As a teacher, can we give a student certain
  flexibility?
  

83
Guideline 2 - Intelligence

• Definition
• quickly adapt to the environment and learn to
  capitalize on new opportunities
  
• What affects the organization learning process?
• Information sharing

84
Guideline 2 - Intelligence (cont)

• As a MIS researcher, what can we do?
• Impact of IT on information distribution
• Impact of IT intra-organization collaboration
• Data warehouse and data mining can help
  organization to learn from historical data
  

85
Guideline 3 - Natural reflexes

• Prepare for unexpected surprise event
• Methods
• what-if questions
• Use what-if questions in our research
• Identify the reasons for unexpected results

86
Guideline 4 - Mutation

• Definition
• Accident can provide a quantum leap
• Methods
• Hire executive from outside the companys
  industry
  
• Explore the inner workings of unrelated
  industries
  

87
Guideline 4 - Mutation (Cont)

• Application in MIS research
• MIS is an interdisciplinary study
• A broad knowledge background will be helpful
• Advantages of the diversified research areas in
  our department

88
Guideline 5 - Symbiosis

• Mutually beneficial relationships between
  organizations
  
• Supply Chain Management
• As a MIS researcher, what can we do?
• research on the inter-organization collaboration

89
Guideline 5 - Symbiosis (Cont)

• Applications in MIS research
• Collaborate with different people
• Example
• CMI IBM, ATT, US Navy, NSF

90
Guideline 6 - Competitive challenge

• Evolve to become tough and resilient in a
  competitive environment
  
• Applications in MIS research
• Position ourselves in a competitive environment

91
More thinking

• Uncertainty in research
• Unexpected factors, unexpected results
• What can we do?
• Good literature review
• What if questions
• Concepts and tools from other areas
• Research partnership

92
Chapter 9 The Certainty of Living in an
Uncertain World

• Think Critically
• Scientific Basis
• Methodology

• Credentials
• Track Records
• Personal Biases