report on “the fortune sellers” mis 696a october 23, 2002

Report on “The Fortune Sellers”

MIS 696a

October 23, 2002

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

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

Chapter 1: “The Second Oldest Profession”

Economics

Financial Services

Technology

Business Planning

Weather

Population

Futurists

Fortune Telling

Chapter 2: “When Chaos Rains”

Weather Forecasting & Chaos Theory The Interaction The Result What’s in for us as researchers?

“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

$35 Billion Losses/year Due to Weather

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Weather Forecasting

Variables – have we considered them all?

Data – is it “precise”?

Top Forecasters:• UK’s National

Meteorological Office

• US’s National Weather Service (NWS)

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

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

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

Long Term Weather Forecasting

Patterns are decieving …

There’s an almost infinite number of weather patterns that could result from any of the persistent environmental conditions or combinations of conditions.

Value of Weather Forecasting Forecasts have value…from 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 …

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

Learning for us as Researchers

Beware of deceiving patterns; it’s 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”!!

Chapter 3: “The Dismal Scientists”

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

another, economics....

Background

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

The Leading Intellectuals of the 19th Century were Economists

Adam Smith

John Stewart Mills

Karl Marx

“The Dismal Scientists”, A Name that Stuck

The Term “Dismal Scientists” comes from Thomas Malthus’s 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

Everyone Wants to Predict the Economy, Most Really Try

European Governments

International Corporations Japan

United States Government

The Problem with Forecasting the Economy

Its not chaotic, just Complex!• It’s 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

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

The Ironic mix of Economics and Information Science

The funny thing about economics is that it requires so much information, even information science can’t help it!

Of course, it doesn’t help that Economics doesn’t have a full complement of natural laws, people act erratically, (although experimental economics is helping that).

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.

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.

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.

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

Predicting the Market…

Technicians Vs. Fundamentalists

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

Fundamentalists

Estimation of a stock’s 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

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

15 Minutes of Fame

Roger Babson – Crash of 1929

Elaine Garzarelli – Black Monday

Joseph Granville – Granville Market Letter

Robert Prechter – Elliot Wave Theorist

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”

“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

Is the Market Rational?S

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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

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

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

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

A way of conceptualizing IS Research as a System

the emergent interactions between the behavioral subsystem and the technological subsystem

Research Culture • values, norms,

traditions • editors, reviewers,

colleagues • tenure committees • funding agencies

the behavioral subsystem

the technological subsystem

Research Technology • knowledge:theories,

frameworks, concepts

• reasoning: positivist, interpretive, critical, and other methods

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.

MIS Researcher:Average 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.

Chapter 5: “Checking the ‘Unchecked Population’”

Why Predict the population? Factors that effect population Current prediction techniques and

accuracy How can MIS help?

Why predict the population?

Applications Infrastructure

Planning Govt Policy Budgeting Marketing

Parameters Growth rate Emigration Average age Male-Female ratio Health

Factors

Economics Weather Political climate Culture War

Emigration Health Male-Female ratio Growth rate Average age

Current status

Forecasts quite accurate Prediction effect on predictions

• AIDS Case

• GM Food Case

How can MIS help?

Databases Data mining, patterns Meaningful correlations Micro level planning

Implications for MIS Research

Effect of external factors on MIS • Economy

• Technology

• Culture

Awareness and Diversification

MIS

TECHNOLOGYPEOPLE and

ORGANIZATIONS

MIS as an Interface

Chapter 6: Science ------ Right or Wrong??

Computer program Virus

Painkiller Drug

Powder War

Robot Enemy

Science and Human beings

Science Fiction

“the first seeds of the idea were shown by that great, fantastic author, Jules Verne”

--Konstantin Tsiolkovsky

Science Fiction & Prediction Science fiction spawned

science prediction

Science prediction emerged as a specialized field in 1960s

(H.G.Wells “the Time Machine”)

80% Science prediction failed

Much more promisesNew habitat

Programmable dream

Longer life expectancy

Robot slave

Out of blueElectricity

Telephone

Light bulb

Cellular telephone

Compact disk

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

Technological Lock-in

Creative destruction

Technological Darwinism Path

Technological synergies

Unworkable Concepts

Unknown applications

Unproved Value

Chance event

A few success technologies

Tens of Millions of Research Project

Unworkable Concepts

First computers Hot fusion Superfluidity

Unknown Applications

MASER Laser Fiber Optics

Unproved Value

Market success depends on customers’ perception of value

Nintendo

Technological Synergies

Technological Lock-In Win standard, win the game

VHS vs Betamax

Microsoft’s success

Chance Events

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

Where is MIS?

Multiple, Interdisciplinary Science

Young research domain also with unpredictable future

Resolve the real-world problem

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

Chapter 7: “The Futurists” Futurists predict societal changes. Mission Impossible?

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 methods…We must reject the possibility of social science that would correspond to the theoretical physics.

--------Karl Popper

...),,( 321 XXXFSociety

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.

What’s 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.”

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.

Zhuge Liang 诸葛亮 The greatest Chinese wisdom,

strategist, politician, inventor, futurist, and

the earliest “FORTUNE SELLER”. (AD 200)“孔明未出茅庐，而知三分天下” Foretell(sell) the Three-Kingdom Era to

Liu Bei, and became the military counselor & premier of Shu Kingdom.

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.

魏蜀吴三足鼎立

Yes! That’s my direction!

Question?

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

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.

What else?

Let’s introduce Zhuge Liang’s brother….

Post Zhuge Liang 事后诸葛亮

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

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.

Chapter 8: “Corporate Chaos”

History of corporate planning• 1970 GE had a planning department

staffed with193 planners

• BCG’s growth share matrix

More recently

Management idea• Strategy Space – a two dimension grid

• 1990 Reengineering

Why planning and forecasting• Foresight gives a company potentials

Organization is unpredictable

A complex system• Highly interacted

Irrational decision making• Lack sufficient information

• Have faulty memories

Can’t expect laws of management • Formulas are not useful

Organization is not directly controllable

Attempt to control unintended results

Can’t control innovation• Innovation comes naturally

• Control stifles innovation

Self-organization• Flexibility at the lowest level

Future

Anything is possible

Future possibility bounded by the present reality

Opportunity

Two type of opportunities Type I: conventional wisdom

• More obvious

Type II: breakthrough• A discontinuity, an innovation, a quantum leap

• Hard to see

Vision

Discover type II opportunities Future – not fixed entity

• What can be done today?

• Shape the future by vision, courage and wisdom

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?

Guideline 2 - Intelligence

Definition• quickly adapt to the environment and learn to

capitalize on new opportunities

What affects the organization learning process?• Information sharing

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

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

Guideline 4 - Mutation

Definition: • Accident can provide a quantum leap

Methods:• Hire executive from outside the company’s

industry

• Explore the inner workings of unrelated industries

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

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

Guideline 5 - Symbiosis (Cont)

Applications in MIS research:• Collaborate with different people

• Example• CMI: IBM, AT&T, US Navy, NSF

Guideline 6 - Competitive challenge

Evolve to become tough and resilient in a competitive environment

Applications in MIS research:• Position ourselves in a competitive

environment

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

Chapter 9: “The Certainty of Living in an Uncertain World”

Think Critically

Scientific Basis

Methodology

Credentials

Track Records

Personal Biases