Technological Forecasting

Henry C. CoTechnology and Operations Management, California Polytechnic and State University

What is Technological Forecasting?

Technology forecasting is forecasting the future characteristics of useful technological machines, procedures or techniques.

Items which depend on popular tastes rather than on technological capability are excluded. Thus commodities, services or techniques intended for luxury or amusement are excluded from the domain of technological forecasting.

The forecast does not have to state how these characteristics will be achieved.

What Characteristics?

Levels of technical performance, like speed of a military aircraft, the power in watts of a particular future engine, the accuracy or precision of a measuring instrument, the number of transistors in a chip in the year 2015, etc.

Dates and probabilities of breakthrough events, technical parameter trends, technology substitution rates, technological impacts, and to some extent, market growth trends.

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Elements of Technological Forecasting1. Technology being forecasted.2. Time of the forecast – a single point,

or a time span.3. Statement of functional capability

– a quantitative measure of its ability to carry out the function.

4. Statement of Probability of achieving a given level of

functional capability by a certain time; or Probability distribution over the levels

that might be achieved by a specific time.

What are we forecasting?

A specific technical approach, or a more general technology?

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What’s the difference? Specific technical approach–means of solving a

problem/performing a particular function. For example, Piston engines and jet engines

are two different technical approaches of the technology of powering aircraft;

Incandescent lamps, fluorescent lamps, and arc lights are different technical approaches to the technology of providing illumination.

A technical approach may be further subdivided. e.g., jet engines can be divided into turbojets and turbofans.

Functional vs. Technical Parameter

Functional parameters – directly measure the extent to which the technology satisfies the user’s needs (speed, power, etc.)

Designers adjust combination of technical parameters (e.g., turbine inlet temperature and compression ratio) to achieve the functional parameters desired by the engine user.

Technological Forecasting (Henry C. Co)

Perf

orm

an

ce

Effort (funds)

Physical limit of technology

Foster, Innovation: The Attackers Advantage, Summit Books, 1986

Why Forecast Technology?

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Why Forecast Technology? To maximize gain from events

external to the organization. To maximize gain from events that are

the result of actions taken by the organization.

To minimize loss associated with uncontrollable events external to the organization.

To offset the actions of competitive or hostile organizations.

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Why Forecast Technology? For purposes of production and/or

inventory control. For facilities and for capital planning. To assure adequate staffing. To develop administrative plans/policy

internal to an organization (e.g., personnel or budget).

To develop policies that apply to people who are not part of the organization.

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For Decision Making Identifies limits beyond which it is not possible to go. Establishes feasible rates of progress, so that the

plan can be made to take full advantage of such rates; the plan does not demand an impossible rate of progress.

Describes the alternatives that can be chosen. Indicates possibilities that might be achieved if

desired. Provides a reference standard for the plan. The plan

can thus be compared with the forecast at any later time to determine whether it can still be fulfilled or whether, because of changes in the forecast, the plan must be revised.

Furnishes warning signals, which can alert the decision maker that it will not be possible to continue the present activities.

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Technological Forecast Is Self-altering Weather forecast must be correct if it is to

be useful. Technological forecast is self-altering.

A self-altering forecast is one that, by virtue of having been made, alters the outcome of the situation.

Suppose someone forecasts an undesirable situation. Then suppose a decision-maker accepts the forecast and acts to prevent the undesirable situation. Clearly the forecast did not come true. Was it a bad forecast?

It is even more important that forecasters educate forecast users to the idea that the goodness of a forecast lies in its utility for making better decisions and not in whether it eventually comes true.

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Contour Map of the Future

Future fans out as a wedge-shaped terrain of peaks/valleys of threats/opportunities

Probability of following any one given pathways into the future is small, but the sum of the probabilities of all the different discrete pathways through the terrain = 1.

Forecaster’s job is to map out the contours (threats and opportunities) of the future’s terrain and show the potential routes through it so the decision maker can judge the best path.

Forecaster’s Dilemma: the finer the details used to describe the pathway through the terrain, the lower the probability of that exact pathway being followed and that particular terrain being traversed as the future unfolds.

(after Porter et al, 1991)

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Process and Philosophy

There is no such thing as a value-free forecast; Its influence starts with where and how we search for and select our input data and continues on through how we analyze and interpret the results.

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Methods of Forecasting

1. Growth curves and Extrapolation 2. Leading indicators3. Causal models4. Probabilistic models5. Environmental Monitoring

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Extrapolation Assumption: Time series data from the past

contains all the information needed to forecast the future.

The forecaster extends a pattern found by analyzing past time series data.

For example: A technological forecaster who was attempting to forecast aircraft speed would obtain a time series of aircraft speed records, find a pattern (trend), and extend to the future to obtain a forecast.

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Trajectory of Tech Innovation

Technological performance often follows an S-shaped curve

Perf

orm

an

ce

Effort (funds)

Physical limit of technology

Foster, Innovation: The Attackers Advantage, Summit Books, 1986

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The Pearl-Curve (Excel)

Productivity (passengers-miles/hour) of Commercial Aircrafts

Curtis C-46Douglas DC-2

Douglas DC-3Boeing 247D

Ford, 5-AT-B

Boeing 747

Tupolev TU-144

Boeing 707-320BDouglas DC-8

Douglas C-124CBoeing C-97A

Lockheed 649Douglas DC-4

Ford, 4-AT-B0

50000

100000

150000

200000

250000

300000

350000

1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975

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The Pearl-Curve (Excel)

Substitution of Coal for Wood as Source of Energy

0%

20%

40%

60%

80%

100%

120%

1840 1860 1880 1900 1920 1940 1960 1980 2000 2020

Year

% P

enet

rati

on

Coal Wood Predicted % Coal Predicted % Wood

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Leading Indicators Assumption: The time series of interest

shows the same behavior as another time series (the leading indicator), but with a known time lag. Thus, what the leading indicator is doing today will be matched by the time series of interest at a specific time in the future.

The forecaster uses one time series to obtain information about the future behavior of another time series.

For example: A weather forecaster uses “turning point” in the time series of barometric pressure to forecast a future turning point in the amount of precipitation.

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Causal Models Assumption: The cause-effect linkages in the

topic of interest are known and can be expressed mathematically or in some similar fashion (e.g., a mathematical model).

Incorporates information about cause and effect relationship, involving some fundamental laws in physics.

For example: A forecast of solar eclipse is based on a causal relationship, involving some fundamental laws of physics.

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Probabilistic Models Instead of producing a single-valued

forecast, probabilistic models produce a probability distribution over a range of possible values.

Example: The probability of rain tomorrow may be stated as, for instance, 30%. This means that over the range of possible outcomes, rain and no-rain, the associated probabilities are 30 and 70%, respectively.

Environmental Monitoring

Forecasts based on trends or growth curves require continuity between the past and the future.Forecasts based on causal models require the consistent operation of the causal factors.

Environmental Monitoring of precursor events made it possible to forecast the eventual development of breakthrough technologies.

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(after Fahey & Narayanan, 1987)

Forecasting a technological breakthrough requires that precursor events be identified and used to provide advance warning.

Process of Monitoring

1. Collection2. Screening3. Evaluating4. Threshold-setting

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1. Collection Aircraft engine company (1930): Concerned about

possible threats to its business of reciprocating aircraft engines.

The firm's technological forecasters track patents granted in the field of aircraft propulsion.

Patent granted in 1930 to Flying Officer Frank Whittle (Royal Air Force) for an aircraft engine based on the jet principle. Air is drawn in through a turbine compressor, fuel is

burned in the compressed air, and the combustion gases are used to drive a turbine, which in turn drives the compressor, while providing some net thrust to propel the aircraft.

This important signal must be screened for significance.

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2. Screening The jet engine patent is clearly significant to an

aircraft engine company. It is potentially a disruptive technology. The forecaster should search further for past signals.

1910: Henri Coanda proposed a jet propulsion system in which the compressor would be driven by a reciprocating engine instead of by an exhaust turbine (ramjet).

1913: French Engineer Rene Lorin proposed a jet engine in which the compression is derived entirely from the aircraft’s forward velocity, eliminating the need for a compressor (turboprop).

1921: Maxine Guillaume received a French patent on a jet engine with a turbine-driven compressor similar to Whittle’s design.

1929: A. A. Griffith of the Royal Aircraft Establishment proposed that a turbine engine be used to drive a propeller for providing aircraft propulsion (turbojet).

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3. Evaluating What does this mean to my

organization? If it represents the start of a trend or

pattern, would it affect our mission? Would it make a product obsolete? Would it alter a production process? Would it have an impact on a

customer? A supplier?

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Whittle’s Patent For Whittle’s engine to work, a compression

ratio of 4 to 1 and a compressor efficiency of 75% would be required. The turbine blades would have to withstand a temperature of 1500F. Thus a forecaster would be interested in seeking information on these parameters.

A 1923 report published by Dr. Edgar A. Buckingham (National Bureau of Standards) showed that only at speeds above 500 mph would the jet engine be competitive in fuel economy. Hence the forecaster would also be interested in tracking aircraft speed.

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4. Threshold-Setting As evaluation continues, the evidence for

one or more hypothesis will become stronger and stronger. When the confirming signals show that the hypothesis has exceeded its threshold, it is time to make a breakthrough forecast.

Thresholds passed by 1938: Whittle’s engine requires compression ratio of 4 to 1 and compressor efficiency of 75%. Turbine blades would have to withstand a temperature of 1500F. In 1931, compression ratio and compressor

efficiency were 2:1 and 65%, respectively. By 1935, these had reached 2.5:1 and 65%.

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In 1935, Hans von Ohain obtained a German patent on a turbojet engine similar to Whittle’s; received support from the Heinkel company for development of a jet engine.

In 1936, Whittle founded Power Jets Ltd. To develop an engine according to his design.

In 1938, the U.S. Army Air Corps laboratories at Wright Field (Dayton, OH) began a 5 year program of development of gas turbines for jet engines. NACA began a program of compressor development. RAE began work on a turbocompressor based on Griffith’s 1929 design.

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Hans von Ohain’s jet engine achieved flight in 1939.

Whittle’s engine flew in 1941. In 1940, the Caproni-Campini CC-2 flew with a

Coanda-type jet engine. In 1942, a U.S. aircraft flew using a jet engine

developed by General Electric. That same year saw the flight of German jet aircraft that was no longer experimental but a combat aircraft.

Technological Breakthrough

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Forecasting a Breakthrough Breakthroughs in technology do not come as “bolts

from the blue.” Breakthroughs are the end result of a chain, or even

a network of precursor events, and these events give warning of a breakthrough is coming.

Forecasting a technological breakthrough requires that precursor events be identified and used to provide advanced warnings. The monitoring process is designed to help the forecaster answer two question: Which events are precursors? What do the precursors do?

See Martino, J. P., “Using Precursor as Leading Indicators of Technological Change,” 32: 341-360 (1987).

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Forecasting a Breakthrough Involves a systematic search for these

precursor, coupled with an evaluation of the significance of the precursor.

The forecaster seeking advanced warning of a breakthrough must search all the relevant sectors of the environment in order not to miss important signals of coming breakthroughs.

The signals found must be synthesized into possible patterns of change, and the forecaster should continue to search for additional signals suggested by the hypothesized patterns.

It is important to search for both confirming and disconfirming signals.

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Precursor Events There are many precursor events leading to

a breakthrough. For instance, there are many precursor

events between the unpredictable scientific breakthrough of 1905 and the eventual commercial use of atomic power in 1956. Not all these precursor events provided positive

signals. Some, such as the impracticality of atomic energy

plants using particle accelerators, were false negative signals.

Some, such as the possibility of fusing light atoms into moderately heavy ones, pointed in the wrong direction.

Nevertheless, atomic energy was not an unheralded event.

Year Event1905 Mass-energy equivalence.

Publication of a paper by Einstein establishing theequivalence of mass and energy

1906 Isotopes of radioactive elements.Discovery of chemically identical elements with differentradioactive properties.

1911 Atomic structure.Experiments by Rutherford showed that the mass of anatom is concentrated in a positively charged nucleus.

1913 Isotopes of non-radioactive elements. Discovery of isotopesthrough differences in physical properties.

1919 Mass spectroscopy.Accurate determination of the masses of the isotopes.

1920s Mass defect (packing fraction).Discovery that the mass of a nucleus is less than the sum ofthe masses of the constituent particles.

1932 Discovery of the neutron.New particle, same mass as the proton, but sharing noelectric charge.

1938 Fission of uranium nucleus.Uranium atoms split into roughly equal halves.

1939 Chain reaction hypothesized.If neutrons are emitted during fission, further fissions cantake place.

1942 Chain reaction produced.Actual demonstration of fission by neutrons emitted fromearlier fissions.

1945 Atomic bombs.First use in warfare.

1956 Commercial nuclear power generation.Actual power plant generating electricity from nuclearenergy.

Precursors to Commercial Use of Atomic Power