The Second Oldest Profession

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The Second Oldest Profession

• "Those who have knowledge, don't predict. Those
  who predict, don't have knowledge. "
• --Lao Tzu, 6th Century BC Chinese Poet

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How old is it?

• I-CHING---- a Chinese Oracle created more than
  4000 years ago.
• the world's earliest known intuitive
  decision-making system.
• The most intricate numerically-based oracle ever
  devised
• Ying vs. Yang? 0 and 1.
• Oracle of Delphi----the most successful
  prediction business in history

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Today
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A Look of MIS Prediction Industry
Venture Investors
IT Consultants
IT Managers
IT Strategists
News Media
IT Economists
MIS Researchers
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The Reign of Error

• 200 billion
• in (mostly erroneous) information each year
• 4,800 million
• revenues from just two IT consulting companies
  in InformationWeek Top 50

• Author says these experts whose advice we pay
  handsomely for routinely fail to predict the
  major events that shape our world
• Somebody says forecasting is the art of saying
  what will happen and then explaining why it
  didn't! "

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Future Imperfect
Chaos Complexity Theories
Determinism
Situational Bias

• Chaos Complexity Theories in MIS
• Decision-making process in information systems
• Forecasting forecasting? (e.g. stock market)
• Complex adaptive information systems
• Semi-Confusing Information systems in changing
  environments

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Voodoo Economics

• Governments make decisions based on faulty
  forecasts.
• Decision makers rely on faulty technology
  forecasts.

• Dirty (faulty) data can jeopardize your CRM
• Emerging technology for SCM
• Collaborative Planning, Forecasting
  Replenishment Technology (CPFR)

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The Last of the Tooth Fairies

• Therefore, just because we cannot predict it does
  not mean we can ignore the future.
• We need to learn how to pluck the gold nuggets of
  advice.
• "It is far better to foresee even without
  certainty than not to foresee at all. "
• ------ Henri Poincare in The Foundations of
  Science
• A pragmatic remark from one of the foundation
  builders of chaos theory

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Chaos and Complexity

• "Prediction is very difficult, especially if it's
  about the future."
• --Nils Bohr, Nobel Laureate in Physics

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Examples of Chaos and Complexity

• Weather
• Severe Storm Warnings
• Agriculture Planning
• Economics
• Government Policy Federal Reserve
• Elections Candidate Platform
• Most Investments

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Forecast Reliability

• Weather
• Forecasts with 10-14 day lead time are reasonably
  accurate
• Distant forecasts impossible to determine
• Economic
• On average not much better that chance

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Naïve Forecasting

• Assume No Change from Normal Levels
• Economics
• Highly volatile areas Naïve better
• Highly stable Forecasters better
• Middle Even
• Weather Follows Seasonal Norms
• Naïve forecast is close to 90 correct better
  than almanacs

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Chaotic Weather

• Chaos Amplifies Mistakes
• Chaos Has No Starting Point
• Based on Proven Science
• Chaos Theory
• Variability within bounds

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Chaotic Systems are Predictable

• Fine Print Accuracy decreases with lead time.

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Complex Economy

• No Natural Laws Governing Behaviors
• Cannot be Dissected into Component Parts
• Highly Connected with External Forces
• No Fixed Cycles

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Complex Systems are NOT Predictable

• Fine Print Your broker who says it is will be
  discussed later in the presentation

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MIS Application

• Naive Forecasting
• Decent reliability, mush less cost
• When in doubt, tomorrow will be the same as today
• Chaotic Systems
• Explore and understand chaotic problems
• Fuzzy logic, behavioral analysis
• Complex Systems
• Be aware, dont predict
• Informed Decisions
• Department policies
• Legislative procedures

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Appropriate Models, Methods, and Methodologies

• "Wall Street indices predicted nine out of the
  last five recessions ! "
• --Paul A. Samuelson in Newsweek, Science and
  Stocks, 19 Sep. 1966.

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Background

• Prediction of stock market has existed since its
  creation (400 years)
• Payoff is huge
• Stock market predictions inaccurate
• Complexity, chaos, speed
• Fundamentalists vs- technicians
• Random walk theory, EMH, etc.

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Example 1 15 minutes of fame

• Roger Babson Crash of 1929
• Chicken Little predictions
• Joseph Granville Granville Market Newsletter
• Psuedoscientific market analysis
• Market responded to his news
• Robert Precther Elliott Wave Theorist Newsletter
• Downfall came after 1987 due to continued gloom
  and doom predictions
• Elaine Garzarelli Black Monday (1987)
• Model simplistic future predictions inaccurate
• Huge reputation

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Lessons Learned

• Appropriately Use models
• Simplistic models cant account for everything
• Use informed, but cautious decision making
• Communication
• How do you get the word out?
• News letter, to the media
• Its all about presentation
• Prediction is a risky business
• Being a market guru is a short lived honor
• Repeat performances are rare
• Shotgun approach - If you predict a lot you are
  likely to hit it right once
• Making predictions made the individuals career
  high risk

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Lessons Applied

• Appropriately Use models
• Simplistic models cant account for everything
• Use informed, but cautious decision making
• Communication
• How do you get the word out?
• Conferences, journals, workshops
• Can you move your research area?
• Its all about presentation
• Prediction is a risky business (especially in
  MIS)
• Being a guru in an area is a short lived honor
• Especially if tied to technology
• Shotgun approach - If you predict a lot you are
  likely to hit it right once
• Making predictions showcases your credibility
• Focus on today with possibilities of tomorrow

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Example 2 - Peter Lynch

• Managed Fidelitys Magellan Fund 1977-1990
• Increased 2700 during his management
• Philosophy
• I dont believe in predicting markets
• Takes a systematic approach in areas that arent
  saturated
• Evaluates a lot of companies

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Lessons Learned

• Choose an appropriate methodology
• He works through bottom up fundamental analysis
  of individual businesses
• Use various methods to analyze the unknown
  problems
• Understand the Saturation Principle
• Stay out of the known zone
• Boring names disagreeable things
• Carve your niche
• Doesnt pay attention to the overall market
• Hedge your risk (low risk strategy with high
  reward payoff)
• Have several stocks that are conservative, have a
  few that are risky. The risky ones will make a
  big impact, but are minimized by the conservative
  picks.
• Work hard
• The person that turns over the most rocks wins
  the game

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Lessons Applied

• Choose an appropriate methodology
• Establish a concrete sound methodology
  appropriate for your research field
• Use various methods to analyze the unknown
  problems
• Understand the Saturation Principle
• Is the known zone of research saturated? Look at
  unkown or little known problems
• Boring names disagreeable things might be a
  hotbed for publications
• Carve your niche
• Understand the principles of the entire field,
  but focus on a specific area that intrigues you
• Hedge your risk (low risk strategy with high
  reward payoff)
• Have several projects that are mainstream
  (conservative), but dabble with some
  revolutionary (high risk) ideas.
• Work hard
• The person that turns over the most rocks wins
  the game

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Science Fact and FictionandThe Futurists

• The illusion of knowing whats going to happen
  is worse than not knowing
• James Utterback

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Background

• Seek to predict technology trends and their
  impact on society.
• Seek to predict the future of society in general.

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Motivation for Technology Forecasting

• Gain competitive advantages
• Identify business opportunities
• Allocate scarce resources appropriately
• Pure entertainment value (e.g., science fiction
  books)

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Example 1 Technology Forecasting

• Japans Ministry of International Trade and
  Industry
• Long range forecasting
• Panel of 3000 scientists, engineers and experts
• Study revealed that 75 of their predictions were
  wrong.

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Example 2 Technology Forecasting

• Microsofts reaction to the Internet
• The Internet? We are not interested in it.
  Bill Gates, 1993
• Sometimes we do get taken by surprise. For
  example, when the Internet came along, we had it
  as a fifth or sixth priority. Bill Gates, 1998

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Pros/Cons of Techniques

• Technological trends take uncertain twists that
  make prediction difficult.
• 80 of new products never see commercial success.
• Change can be rapid or take a long time.

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Pros/Cons of Techniques

• Social predictions tend to be wrong and are
  subject to situational biases, wishful thinking
  and political agendas.
• Society is a complex system that evolves and
  cannot be predicted.
• Sociology is the science with the greatest
  number of methods and the least results
• Henri Poincaré.

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Lessons Learned / Application

• "The herd instinct among forecasters makes sheep
  look like independent thinkers. "
• Edgar R. Fiedler in The Three Rs of Economic
  Forecasting-Irrational, Irrelevant and Irreverent
  , June 1977.

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More Lessons Learned / Application

• Must be critical thinkers and avoid the herd
  mentality.
• Develop sound theories that can be applied to
  various technologies.
• Technology is probably not in your theory.
• Dr. Bob Briggs

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More Lessons Learned / Application

• In times of change learners inherit the earth,
  while the learned find themselves beautifully
  equipped to deal with a world that no longer
  exists.
• Eric Hoffer

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Check the Unchecked Population

• The reason why population is hard to predict is
  because when I left my home country the
  population dropped by 10 percent."
• -- My 250-Pound Neighbor

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Background

• Human life expectancy
• From 25 to 47, took 200,000 years
• From 47 to 77 (in developed countries), took 100
  years
• Human population over 5 billion people
• Questions
• Can we feed us all? For how long?

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Is Global Famine Unavoidable?

• I call the disaster the Time of Famines and I
  say that the Time of Famine will be upon us by
  1975.
• Famine 1975!, by William and Paul Paddock,
  1967

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Malthus Prediction

• Population, when unchecked, increases in a
  geometrical ratio while subsistence increases
  only in an arithmetical ratio. Famine seems the
  be the last, the most dreadful resource of
  nature.

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Lessons Learned

• Never ignore major factors
• Underestimated the productivity of modern
  agriculture, the green revolution
• Population can be controlled via different ways
• Birth control

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Real Challenges to Predict

• Future births, the unborn
• Migration is driven by complex circumstances
• Economic hardship
• Civil war
• Governments immigration policies

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Population Predictability

• Twenty-year population forecasts could be
  accurate
• The bigger the target, the better the accuracy

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Lessons Learned

• Start with simpler situations
• Focus on specific area first
• Solving something is better than solving nothing

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Corporate Chaos

• The most effective style to fight is no style."
• -- Jin Yong, Famous Chinese Martial-Art Novelist,
  and Bruce Lee

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Background

• 70s, GEs elite group of 193 planners
• 70s, Eastern Europes planning economy
• From early 50s to late 70s, Chinas planning
  economy

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Did Long-Term Planning Really Help?

• 80s, Japans intrusion to Western markets with
  superior, low-cost products
• Crash of telecommunication industry, e.g.,
  Nortel, and Santera

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Why Did That Happen?

• Strong influence of international politics
• Dramatic change of social structures
• Impact of unpredictable events
• Unpredictability of organizations

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Lessons Learned

• Self-organization
• Empowerment decentralize the decision making
  procedure
• Guiding principles set up basic rules

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More Lessons Learned

• Go with the short-term benefit let the cash flow
• Natural reflexes no style is better than any
  style autonomic computing

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The Certainty of Living in an Uncertain World

• Computers in the future may weigh no more than
  1.5 tons.
• -Popular Mechanics (1949)

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Thinking Critically

• Credibility Assessment
• Is the forecast based on hard science?
• How sound are the methods used to make the
  projection?
• Does the forecaster have credible credentials?
• Does the forecaster have a proved track record?
• To what extent is my belief in a particular
  forecast influenced by my own personal beliefs
  and wishful thinking?

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Scientific Method

• Laws of Nature?
• Physics, Chemistry, Mathematics
• Behavior of Social Systems?
• Stock Market, Political Events

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Soundness of Methods

• Extending Trends
• Moores Law, Global Warming
• Cyclic Behavior
• Stock Market Crashes, Earthquakes

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Forecaster Credentials

• Physical credentials
• Appearance, Conviction
• Paper credentials
• Institution, resume
• Hyped-up credentials
• Role of the Media

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Forecaster Track Records

• Lucky Guess?
• Spray technique
• Million guesses, one has to hit
• Vagueness
• Nostradamus
• A lie?
• Revisionist history

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Biases

• What we want to hear?
• Similar imaginings
• Barnum effect
• Something for everyone

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Questions?

• "Those who have knowledge, don't predict. Those
  who predict, don't have knowledge. "
• --Lao Tzu, 6th Century BC Chinese Poet