Tf-Intro and Methods

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TECHNOLOGY FORECASTING: A CONCEPTUAL FRAMEWORK

K. Vizayakumar

Professor & Head, Dept. of Industrial Engg. & Management

1. Planning and Forecasting :

Frequently there is a time lag between awareness of an impending event or lead and occurrence of that event. This lead time is the main reason for planning and forecasting. If the lead time is zero or very

small, there is no need for planning. If the lead time is long and the outcome of the final event is

conditional on identifiable factors, planning can perform an important role. In such situations forecasting

is needed to determine when an event will occur or a need arise, so that appropriate actions can be taken.

A lay person may question the validity and efficacy of a discipline aimed at predicting an

uncertain future. However, it should be recognized that substantial progress has been made in forecasting

over the past several centuries. There are a large number of phenomena whose outcomes can now be

predicted easily. The sunrise can be predicted, as can be speed of a falling object, the onset of hunger,

thirst of fatigue, rainy weather, and a myriad of other events. The evolution of science has increased the

understanding of various aspects of the environment and consequent by the predictability of many events.

If you can determine perfectly always or near perfectly, it becomes science and if you cannot, a forecast.

The ability to predict many types of events seems as natural today as will the accurate forecasting of

weather conditions in a few decades. The trend in being able to accurately predict more events,

particularly those of an economic nature, will continue providing a better base from which to plan.

Formal forecasting methods are the means by which this improvement will occur.

Successful forecasting is not always directly useful to managers and others. More than 100 years

ago, Jules Verne correctly predicted such developments on submarines, nuclear energy and travel to the

moon. Similarly in the mid 1800s, Charles Babbage not only predicted the need for computers, but also

proposed the design for one. In spite of the accuracy of these forecasts, they were of little value in helping

organizations to realize those possibilities or achieve greater success.

A second important point is the distinction between uncontrollable external events (originating

with the national economy, governments, customers, and competitors) and controllable internal events

(such as marketing or manufacturing decisions with the firm). The success of a company depends on both

types of events, but forecasting applies directly to the former, while decision making applies directly to

the latter. Planning is the link that integrates them. (Makridakis, et al., 1983).

During the late 1960s, many large organizations created formal planning groups and charged

them with predicting future environments and the organizations’ performances in those environments.

Since planning involves forecasting, this gave substantial impetus to studies of forecasting methods and

development of staff who were familiar with such methods.

Organizations will have little choice but to utilize formal forecasting methods to a much greater

extent than they have in the past, accepting their weakness and limitations and recognizing that managers

themselves cannot do any better. Moreover, the field of business forecasting will have to be enlarged to

include such areas as political forecasting, energy forecasting, technological forecasting, and related

fields. Because of the importance of these areas to several other aspects of business forecasting,



development of procedures that systematically incorporate these at the firm level into planning and

strategy will be essential. The planners, strategists and decision makers will need to understand and

accept that forecasting the future does not eliminate uncertainty and finding more effective ways to assess

its impact on future plans and strategies will be a major challenge to both forecasters and managers.

(Makradakis et al., 1983).

To draw a line between business forecasting and technological forecasting, business forecastinguses more quantitative techniques whereas technological forecasting uses more qualitative techniques. It

is not that business forecasting does not use qualitative techniques but it is viewed with relative

importance. In fact, it also depends on the factors forecasted. In business forecasting, the stress is on

physical quantities whereas in technological forecasting it is on the behavioral issues.

2. Uses of TF:

Technological Forecasting essentially tries to answer one or both of the following questions:

(i) When is a new development likely to be widely accepted,

(ii) What will be the likely developments in a given area of technology in the near future?

TF attempts to answer these questions with a high degree of confidence by approaching the

problem in a formal and systematic manner, and

(i) helps in long range planning

(ii) provides new directions for R&D

(iii) enhances understanding of competition

(iv) enhances understanding of consumer’s needs

(v) helps to make strategic decisions

It is also found that the high product technology firms such as chemical, machinery,

transportation, fabrication, etc. which are also capital intensive, find TF crucial to their companies and use

it regularly. Where as companies such as food, apparel, construction which are of low technology in

nature, feel TF as unimportant (Balachandra, 1980); Coats (1989) enlists four expectations one might

have from a forecaster.

(i) Announcement of the coming of a specific event :

- not only the occurrence of event, more than that the implications of the event and the

implications for activities before, during, and after the event. Say, what may happen if an accident occurs

in a particular Nuclear power plant ? Or if an earthquake of certain intensity occurs at a place ? Or the

floods of certain volume occur.

(ii) Offering of aids to decision making :

- In the domain of decision making, there is an increasing ability to identify knowledge gaps and

crucial uncertainties, to suggest plausible practical and useful activities to narrow those ignorance gaps



and to reduce uncertainty on the one hand, or to act more rationally in so far as the uncertainties cannot be

reduced.

(iii) Offering of direction for action :

- It is possible, through technological forecasting, to offer strategic directions. The difficulty

arises due to biases or ideological objectives. A forecaster must struggle to be neutral in drawing

conclusions.

(iv) More Sophistication in dealing with Complexity :

- Tools of complexity to explain, explore, present and analyze complex situations are abound.

Managers of the industry, either public sector or private sector, often face the need to make

decisions for which they lack necessary knowledge. The decisions to be made may be when they have to

switch over to newer technology which is more promising but risky. Which type of technology they

should borrow? In which sector the new investments have to be made? and so on. Obviously, the

manager or decision-maker should have sufficient knowledge to take decisions, may be regarding the rate

and direction of technological change; why the company is becoming less competitive – due to less

investment or wrong investment? Is the technology changing faster than the consumer’s interests? These

questions and issues that they may face are generally broad and vague for solving by intuition or even by

analytical methods. This is also due to the large gap in the knowledge available. This is where

technological forecasting helps the managers in making better decisions regarding future (Ayres, 1989).

However, one cannot say that technological forecasting is fully evolved, particularly, in terms of methods

and techniques available. Measurement of technological change is still a challenge to the forecasters.

Though, recently some methods are evolving (Martin, 1987; Triplett, 1985; Alerander and Mitchel,

1985). They are yet to be verified thoroughly and established.

3. Technology Dynamics :

Development of technological forecasting methods may also depend on the evolving new and

challenging technologies. Technology will never be static. It goes on changing. The rate of change is

increasing exponentially and is discussed in other chapters. As new technologies evolve, technology

paradigm also will change. Take the case of manufacturing technology. After the industrial revolution, the

paradigm was mass-production technologies, then it is automation in manufacturing and later

Numerically controlled machining process. Now it is Hi-Tech, mainly Flexible manufacturing systems,

Cellular manufacturing systems. This process goes on and on. It is best explained in Fig. 1. The figure is

self-explanatory showing the linkage between Technological development and economic development

and with consumers, it falls into a closed loop, a positive feed back loop which has the characteristics of

exponential growth.

Technology Paradigm

Engineering Technological Occupational Structure Economic Institutional

Technologies Motive Motive Adoption

Income Redistribution

Consumer Demand

Fig. 2. Technology Dynamics (Taken from Dror, 1988)



This unending growth in technology in the foreseeable future, will make the industry to look

more towards technological forecasters to get the prior information about these developments.

4. The Indian Context

Though the technological forecasting is talked about in India for more than two decades now, it is

not adopted by the industry in a big way. In fact, Department of Science and Technology, Government of India has taken a lead to propagate by funding several training programmes. It also took initiative to set

up several schools/departments of Future Studies in established universities where in technological

forecasting is an important part of the curriculum. It is reported that many R&D Institutions like National

Institute of Science, Technology and Development Studies NISTADS and Government institutions like

Technology Information, Forecasting, and Assessment Council (TIFAC) are extensively using these

techniques in their studies. With the changing industrial and economic environment, the flow of new or

improved technologies to India is creating a very high competitive environment to the Indian

entrepreneurs. Therefore, it is expected that they have to look for signals that provide them knowledge

about the emerging or flowing technologies sufficiently in advance. This is where the importance of

dissemination of knowledge and practice of technological forecasting lies.

The following techniques, useful for technological forecasting, are discussed here.

1. Trend analysis

2. Brain Storming

3. Scenario Generation

4. Analogy

5. Relevance Trees, and

6. Delphi



TREND ANALYSIS

Trend Analysis uses extrapolation techniques to forecast a future growth of technology, say, capability of

technology at a future period of time. It generates the trend curves based on the past data and extends

them into future, say 1 year, 2 years, 5 years, etc. However, using trend curve for a very long period is notdesirable as it may not be able to absorb the internal dynamics. It is generally suggested that the trend

curves are projected into future for a period equivalent to the time period for which the past data is

available. However, the confidence in the forecast decreases as the period increases.

Trend curves are generated using the following techniques:

Linear extrapolation

Exponential extrapolation

Curve fitting

Regression analysis, etc.

A particular technique may be chosen based on the past data or the past behaviour of the technology. Like

in Business Forecasting, a measure of the error may also be used to determine which method is suitable

for a particular technology situation.

1. Linear Extrapolation

Here, parameter, chosen to represent technology, is plotted linearly against time and the trend line thus

obtained is extrapolated into future. There are several examples in nature where technologies or

technological parameters increase linearly. For example, food production in India is increasing near

linearly as shown in fig. 3.

This trend line can be extrapolated into future, say 2001, 2002, 2005, and so on. And the expected value

of the food grain production in the country can be obtained.

2. Exponential Trend

Forecasting by exponential smoothing method is very popular in business and sales forecasting. Here,

semi log plots are used with logarithms of technological parameter, which then becomes a linear plot.

This linear plot is then extrapolated to obtain the forecast in logarithmic values and later converted to

obtain the estimated values. The speed of the computers, in terms of MHz, is an example for

exponentially changing technical capability. One would observe several such parameters in practice.

Double exponential trend is used in situations where the fluctuations are more.

Here also, the parameter values are converted to logarithms and plotted to obtain a linear trend. Some

specific examples where this is fitted well are the lasers ad their output energy, and R & D efforts for

further improvement.



Fig. 3 Food P roduction in India

0

5 0

10 0

15 0

20 0

25 0

1 95 0 1 96 0 1 9 70 1 9 80 1 99 0 2 0 00

Year

M

i l l i o n

t o n n e s

3. Curve Fitting and Regression

The curve fitting is desirable when large volume of past data is available. Linear trend is developed by

using a first order polynomial. Once the trend is obtained, it can be extrapolated for the required period of

time and the forecast can be made.

In simple regression, Two parameters of variables are considered, one, a dependent variable and another

an independent variable. A trend line is obtained as relationship between the two variables. For

forecasting purpose, time as independent variable and a technological parameter as dependent variable are

considered so that the value of the technological parameter can be forecasted for a future time point.

Higher order curve fitting can also be used where the trend is of complex nature.

Conclusion:

Trend analysis is a simple quantitative technique that requires large volume of past data. However, its

forecasts or future trends are valid for a short range of time. Trend is not generally used for long rangeforecasting.



BRAIN STORMING

1. Definition :

Brainstorming has been defined as a process of pooling minds to generate ideas which hopefullyrepresent either expert knowledge or collective opinion each with a high probability of being correct.

2. Concept :

It has often being assumed that “two heads are better than one”. Corollary to this would be the

statement that “N+1 heads are better than N heads”. Often the state of intellectual development

concerning a complex issue is such that we do not have detailed information. Thus we look for the

aggregate input generated through interactive process of a group for judgment and decision-making.

Brainstorming was popularized by the American advertising executive Alex Osborn in the 1930s. It was

used to overcome status in business meetings by having all suggestions written down without criticism

until all ideas had been noted.

3. Features :

The basic features of brainstorming are :

1) It is a group technique.

2) It promotes and supports idea generation and divergent thinking.

3) It is a creative problem solving technique.

4) Its use results in large number of ideas or possible solutions to a stated problem.

5) The central principle of the technique is that of deferred judgment.

The principle of deferred judgment is crucial in a brain storming exercise. It is considered more than the

conscious suppression of criticism, it is a state in which ideas are dreamed up without self-criticism and

presented to other group members who accept the ideas without internal or external evaluation.

4. Advantages and Disadvantages :

The advantages of a brain storming exercise are :

1) The group interacts and compensates for the bias of individual member of the group.

2) Knowledge of one member of the group may well be compensated for ignorance or

speculation on the part of other members.

The disadvantages are :

1) Opinion can be highly influence by an individual who talks the most and the loudest.

2) The influence of one or more dominant individuals can be most upsetting to the group.



3) In brainstorming, if the session is not organized properly it would result in a “bull

session” in which more discussions take place for the interest of some members or a

group rather than the problem.

4) Often there are strong pressures for group conformity or avoidance of unpopular and/or

minority viewpoints.

5. Methodology :

The classical brainstorming exercise involves a small group, a well-defined problem, and prior

awareness of the problem by the group, a coordinator, a secretary, and a blackboard. The session may last

for 6-9 minutes. The classical rules are :

1) The coordinator should remind the group of problem at hand and the rules for

brainstorming.

2) Ensure that all participants join in the discussion and the coordinator will suppress his /

her own ideas as long as the group is generating ideas. The coordinator will inject new

ideas only when the group does not.

3) No criticism of ideas can be allowed.

4) Keep the ideas short and develop full details later.

5) The coordinator writes short, two-word description of all ideas on the black board, and

the secretary keeps detailed record.

6) If needed the coordinator may reread the ideas to stimulate the group to generate more

ideas.

Many minor variations in brainstorming exercise may occur. In one case for example the participants may

supply ideas in writing to the coordinator prior to the meeting which will be presented to the group

without mentioning the source. In some cases the problem may not be announced to the group in advance.

In yet another case instead of one, a series of meetings could be organized if the problem is of complex

nature and needs more than one session. It is also possible to replace much of the verbal aspect of brain

storming with written communication. The resulting exercise is often called a “brain writing” exercise. In

this the participants write their ideas on a sheet of paper. Usually up to three ideas from each are

expected. The sheet is passed on to another member and the ideas originally developed by one member

are further developed by another and so on. When the cycle is complete, and each participant receives his

own sheet back, the first phase of the session is over.

In the second phase, the ideas of first phase are revised. Again, a variety of ideas and variations in the

way of conducting are possible. Sometimes, the papers may be kept in a pool rather than circulated, and a

member who takes a sheet from the pool also puts a sheet in the pool. The member further expands upon

the ideas written in the collected papers and elements contained there.

6. Preparation Required :

To be effective, a brain storming session must be preceeded by a careful preparation of the

problem and a warm up session.



Extremely broad statements of the problem should be broken down into more easily manageable

statements. This may either be mutually agreed upon by the participants or prepared by the coordinator

following certain steps. Certain guidelines for the systematic steps are available in the form of checklists,

attribute listing, and morphological approach.

Checklists : It helps in checking various possibilities intrinsic to the problem, in order to avoid bias in

the process of search. Questions like who, what, when, how, where and why could be asked. Hence,various dimensions of the problem could be explored without ignoring some which could be of crucial

nature. Another type of checklist prepared by Osborn himself asks questions like; put to other uses ?

Adapt ? Modify ? Minify ? Substitute ? Rearrange ? Reverse ? Combine ?

Attribute Listing : To explore new uses of a product or for example to evaluate an advertising theme for

a product or modification, attribute listing has been found to be a valuable ingredient in brainstorming

session.

Morphological Analysis : It is to structure the problem by means of a matrix. The attributes are divided

into two major sets, each representing one axis of the matrix. Each cell then represents a forced

relationship to be brain stormed.

7. Warm-up Session :

A warm-up session helps an individual to cast-off his biases and prejudices of everyday life and

tunes his/her to be in non-evaluative mode. Depending upon the experience and mood of the group this

session may last for 30 to 90 minutes. A warm-up session may include an “Introduction Discussion”.

Here, the ground rules of the brainstorming exercise are outlined, the principle of deferred judgment is

discussed, and the queries from the participants are answered. It may last for 5 to 15 minutes.

‘Group Building’ follows the introduction session. Here, the group members come to know each other

and interact by introducing themselves, or discussing on related / unrelated issues for 5 to 30 minutes.

‘Individual Warm Up Brainstorming’ is tried in order to provide a feel to the group members the principle

of postponed judgment who might not have participated in brain storming exercises earlier. Here, a topic

of general interest to the group members could be taken for brainstorming. It may last for 5 to 10 minutes.

‘Non-verbal Puzzles and Exercises’ help to stimulate ability to imagine in a non-verbal way. It may last

for 5 to 10 minutes.

‘Interactive Warm-up’ is a mini-brainstorming session in which any popular topic is brain stormed.

Afterwards the output is discussed for hitch hiking, which is the process by which the tendency to react in

an evaluative manner to an idea is reduced and residual emotions and evaluations are developed towards

producing additional ideas. It may take 10 to 20 minutes. “Reinforcing Warm-up” session discusses any

additional technique to be used in the main brainstorming session later. It can take up to 20 minutes.



8. Brain Storming Subroutines :

Trigger Session : It is a group idea generating process in which members work for a period independently

producing a list of ideas. At the end of the given time, each person reads out his list, thus generating

stimuli for the rest of the group to produce more ideas. Sometimes a second group of observers are asked

to jot down observations and any idea that occur.

Recorded Round Robin : It is better suited to small groups. Here, each member receives a sub problem

and three blank cards. He writes the problem on each card and adds one-idea to each card. The cards are

then passed on to other members of the group to add new ideas.

Wildest Idea : Here, wildest idea becomes the starting point for brain storming session. These are then

brainstormed to produce practical ones.

Reverse Brainstorming : An Osborn – type brainstorming requires solutions to stated problems. In a

reverse brain storming exercise, the group is expected to anticipate problems for implementation of a

solution to another problem.

The above stated subroutines could be followed depending upon the experience, creativity, and situational

requirement. One may try as many techniques as possible.

9. Evaluation of Ideas of Brainstorming Session :

Many ideas of a brainstorming exercise may be wishful thinking having little practical relevance.

Such ideas could be listed separately for a morphological analysis and classification. Other ideas have to

be screened for their merits for the problem in hand. The client could also be a part of the session or at

least he / she could be present in the session. Further, the ideas could be classified under ‘A’, ‘B’ or ‘C’

categories depending upon their novelty, practicability and other merits.



SCENARIO GENERATION

1. Defining Scenario :

A “scenario” or “future history” is a narrative description of a potential course of developments

which might lead to some future state of affairs. Scenario is a narrative sketch of hypothetical sequence

of future events. A scenario can be very powerful if constructed under the hand of an experienced and

talented author, as it can carry the eloquent narrative prose. Some of the famous scenario writes include

the names like Herman Kahn, Anthony Miner and Paul Ehrlich.

The scenarios describe scene by scene one or more mental images (computers also getting used

lately) of the future For the method to be informative, these images should be detached, self consistent

and real.

2. Scenario Writing :

Kahn and Wiener, through their book “The Year 2000” popularized the concept of scenarios.

Though little methodology was available on how to develop them, the book marked a beginning of

scenario writing. The relevance of scenarios lies in the fact that plans and forecasts are based explicitely

or implicitly on assumptions about the future. Our assumptions about ‘true’ future have been far from

correct or complete. Therefore, the scenario concepts also could be described as contingency planning

which has long been practiced by governments and business organizations. Hence, a scenario would

mean a “possible future” not the “most probable future”. The scenario would present a number of possible

alternatives each one based on certain assumptions and set of conditions. It is then up to the decision

maker to assess the validity of assumptions in deciding which scenario is most likely to become reality.

3. Scenario Development :

Scenarios consist of a set of statements about future events and trends developed around some

underlying theme. For a scenario to be persuasive and thus usable as a basis of planning, it is important

that these statements be consistent with the theme, and internally consistent with each other. The writer

could follow the following steps in writing a scenario.

i) Develop a framework, what happens to each sector of the environment ? What trends

should be considered ? Will they continue or change, when and in what way? Are there

decision points for critical decisions? Who will make the decision?

ii) Forecast the technology / technologies to be considered. When will it be deployed ? What

is the scale of adoption ? What are the impacts on entrepreneurship and on the framework

trends and events ? What are the specific decision points ?



iii) Plot the scenario. Identify events that cold trigger decisions, select a small number of

sequences of events and decisions. Check for consistency.

iv) Write the scenario. Fill in the outline developed in the previous steps by a verbal

narrative describing the events.

4. Techniques :

From the age of “wise oldmen’s forecasts”, the industry and governments have now been using

more objective techniques to create vignettes of the future world. Among the better known techniques for

generating “more objective” scenarios are (1) consensus (2) iteration through synopsys, and (3) cross

impact matrices.

In the consesus technique, groups of experts in various fields are asked what major events they

might anticipate in a specified future period. The expert interact though Delphi process. One may

summarize the method as a consensus of “wise old men”. However, the biases introduced by the present

are not completely ruled out. In most cases the data is non quantitative. Also, the wishful thinking of

experts may influence the forecasts. The method “Interaction through synopsis” is designed to increase

interdisciplinary consistency in the scenario. It consists of developing independent scenarios for each

discipline and then modifying the descriptions through an interactive process which makes the scenarios

compatible with one another. However, problems may arise in cases when some disciplines like

sociology remain compartmentalized because of the difficulty of estimating their effect on other fields.

Cross-impact matrices is a powerful method of scenario generation. Girdon and Helmer (1969)

describe the method as a “…. Method of analysis which permits the orderly investigation of the effects of

potential interactions among items in a forecasted set of occurrences. It requires a methodical questioning

about the potential impact of one item, should it occur, on the others of the set in terms of mode of

linkage, strength of linkage, and time when the effect of first on the second world be expected. ……. It is

then possible to perform an analysis which revises the initial estimates of probability of the items in the

set.” The advantages and disadvantages of the three are as given in Table 3.

Table 3 : Advantages and disadvantages of different techniques

Method Advantage Disadvantages

1. Consensus Decreases bias Only some items are considered.

technique Interaction is absent.

2. Interaction Increased Lack of definable relationships

through interdisciplinary between disciplines

synopsys consistency

3. Cross-impact Internal Subjective assignment of

Matrices consistency values and biases



Criteria for Judging Scenarios :

In judging scenarios, four basic criteria are used :

1. Responsive : Scenarios should not be merely exercises in creatively designed to stimulate

management’s vision. Scenarios should be developed in the context of the specific strategic issues facingmanagement. It must be remembered that the scenarios will have to be used in conjunction with specific

stratic alternatives to generate and evaluate outcome scenarios. The elements, events, and trends, and the

form in which the scenario is presented should be responsive to this need. It is wise to start by explicitly

formulating the purpose of the scenarios at every stage.

2. Comprehensiveness : All the relevant environments should be addressed in the scenario, not just

the economic factors. The scenario should not simply describe alternative futures which may face the

organization; they should also develop the “time line” the path of events which would lead upto that

future. Separate your personal beliefs of what you think is “likely” to happen from the need to develop

scenarios, which will expose potential risks and test underlying assumption.

3. Documentation : The background material used in developing each scenario should be available

to the Planner / Manager. The model structure should be explicit and understandable. Any included

statements of fact should be correct and supported. All underlying assumptions should be explicit.

Available evidence which would support or limit the assumptions should be included. Events should be

specified in terms of what, when, where and, how.

4. Plausibility : The final risks in any strategic decision must be borne by the Manager. No matter

how good a scenario may be technically, it must, however, be internally consistent. It must address real

issues, and the assumptions and path by which that future can evolve from the present must be clear.

Thus, scenarios can be very effective tools in focussing managerial attention and in highlighting

opportunities and risks in planning. To be effective, scenarios must be plausible, well documented,

internally consistent and relevant to the decisions. It is too easy to dismiss the issue by asserting that

scenario development is an ‘art form’ and can only be learned by doing.

The potential uses of scenarios are much broader. They can aid in contingency planning, in

exploring the possible magnitude and sources of forecast errors, and in judgemental forecasting to reduce

the problems of “anchoring”.



FORECASTING BY ANALOGY

Analogy involves a systematic comparison of the technology to be forecast with some earlier

technology that is believed to have been similar in all or most important respects.

An analogy will be strengthened if there are several historical cases with parallel outcomes that

can be compared to the present case to be forecast.

The use of analogies is subject to the following problems.

(1) The lack of inherent necessity in the outcome of historical situations. Here, a forecaster may

discover a “model” historical situation, which is then compared with the situation to be forecast. If the

two situations are sufficiently similar, the forecast would be that the current situation will turn out as the

model situation did. However, the current situation will not necessarily follow the pattern of model

situation. Analogies are based on the assumption that there is a “normal” way for people to behave and

given the similar situations, they will act in a similar way. However, there is no guarantee that people

today will act as people did in the model situation. Hence the forecast is at most probable, never certain.

(2) The Historical Uniqueness: No two historical situations are ever alike in all respects. Thus it is

important to be able to say which respects are important and which can be ignored. Hence, a systematic

means for comparing model situations with each other and with the current situation is essential.

(3) The Historically conditioned awareness. Even though a historical situation may be judged to be

sufficiently similar to the present situation to be called analogous, people may be aware of the previous

outcome and act differently in order to secure a more preferred outcome. Hence it violates assumption

that there is a “normal” way for people to behave and that they always behave that way.

Dimensions of the Analogies:

We wish to compare a historical or model situation with a current situation in order to develop an

analogy between the two. Since we are primarily concerned with the technological change, it is important

to compare the two situations on the basis of the factors that affect technological change: the invention of

some device or procedure, or adoption of the invention, and wide spread diffusion of the invention.

The following list of factors have affected technological change and it therefore provides a

suitable basis for comparing situations for a possible analogy:

1. Technological, 2. Economical, 3. Managerial, 4. Political, 5. Social, 6. Cultural 7.

Intellectual, 8. Religious – Ethical, 9. Ecological.



The Technological Dimension:

Technologies do not exist in isolation; every technology exists to perform some function desired

by people. There are usually alternate ways of performing the same function that compete the technology

in question. The technology must also draw some supporting technologies. Finally, the technology must

mesh with the complementary technologies that perform the other function.

The technology used as “model” has to be superior to its competing technologies or else it would

not have succeeded. The forecaster should identify the competing technologies in the model situation and

in the current situation to be forecast and compare these.

A technology must draw on other technologies for support in such things as production,

maintenance, energy supply, and transportation. It should be compatible with complementary

technology, usually in terms of input and output. In examining the technological dimension, one must

look beyond the physical hardware to the theories behind both the model technology and technology to be

forecast.

The Economic Dimension :

Technology is intended to perform some function and will be useful only if people are willing to

pay for it. The forecaster must look at the ability and willingness of the relevant people, in both model

and present case to pay for the present technology. The relevant cost which is the cost of deploying the

entire situation includes the cost of research and development, capital investment, manufacturing costs

and maintenance costs. However, in developing the analogy we are concerned not with the rupee cost but

with cost of each as a fraction of the total resources available to those supporting the projects. The

following are important :

(1) We must look at the financial resources available for mobilizing the resources.

(2) Market comparison, that is to compare the demand for the technology in terms of market size.

(3) Compare the economic climates in terms of economic theories.

The Managerial Dimension :

It is necessary to compare the levels of managerial capability in the model and current situations

relative to the size and complexity of the task.

The size depends on the number of people to be managed and their geographical spread.

Complexity is measured by the number of different types of activities involved and the number of

locations to which these must be carried out. By seeing whether the complexity of the model task is

greater or lesser than the complexity of the tasks managed previously the management can decide its

future. Finally it is necessary to compare the managerial techniques. The ability to manage larger projects

comes from better managerial techniques and procedures – managerial “technology”.

The Political Dimension :



The basic questions about the interaction of politics and technological change are who gets

benefited ? and, who gets hurt ? Those who benefit from the technological change will try to encourage it;

those who suffer from it will try to stop it. Hence it is necessary to compare the relative political power of

the people who benefit and who get hurt out of it.

In addition to direct winners and losers, there may be people who have nothing against the

technology itself but who oppose it because it hinders political goals they support. The forecaster mustcompare them in terms of the avenues of the support or opposition “legitimately” open to various groups.

The Social Dimension :

Every technological change occurs within the society and it acts on and is acted upon by that

society. Hence the forecaster must compare a model situation with the present situation in terms of

society into which the innovation was or will be in introduced.

The people making up a society can be characterized in terms of total population, age

distribution, geographic distribution, income distribution, urban / rural distribution and so on. In

comparing the two possibly analogous situations the important consideration is not the absolute number

but the relative sizes. The comparison must be made on the basis of the relevant portion of the society.

Institutions include family, schools, churches and government. The traditions are customs of a society

bind it together and reflect its self-image. Thus, in comparing two technological changes for a possible

analogy the forecaster must take into account how each fits in with the traditions and customs of the

society into which it was or will be introduced.

Cultural Dimension :

This dimension deals with the values, attitudes and goals of the society into which innovation is

to be introduced. These values are like health, comfort, physical security, economic security,

productiveness, honesty, fairness, charitableness, courtesy, freedom, justice, beauty, cleanness of

concise, intelligence and professional recognition. Different societies and people at different times and

places have ranked these in differing order of importance. Since values provide a rationalization for

action they will affect technological change. This may come about in two ways. The values subscribed

to by a society may favour or inhibit change. Conversely a proposed technological change may retain or

enhance an important value. Thus a society may be favorably or unfavorably dispose towards change. In

general, or a society may oppose or support a particular change because of the technological impact and

values subscribed to by the society. A comparison between two technologies for a possible analogy must

take social values into account. Two societies must be compared on the basis of the general effect of their

values on innovation and on the basis of specific reactions to particular innovation that may affect

important values.

Intellectual Dimensions :

Intellectual leaders are decision makers of private and public organizations. These are the people

who speak on behalf of prestigious institutions, and opinion leaders such as editors, poets and writers.

They may support or oppose the technological change. Their effect on technological change depends

upon the extent to which their leadership is followed b others. So, forecaster must examine two things



here. First examine the extent to which intellectual leaders have following and second look at the way in

which the two technologies effect and are effected by the values and goals of the intellectual leadership. If

intellectual leaders have no impact on particular technology these dimensions can be omitted from

consideration.

Religious and Ethical Dimensions :

These Dimensions have two components (1) Beliefs that guide ethical judgements and (2) the

institutions which propagate or formulate ethical beliefs. Beliefs may affect a technology change in two

ways. First, people may oppose or favour technology change on general ground. Some religions do not

want to use the particular technology by their people. Second people may oppose or favour a particular

technology change because the technology may impact unfavorably or favorably on religious doctrine.

Ecological Dimensions :

These dimensions depend on level of ecological damage that is acceptable to the people involved.

All the changes to the natural environment are considered. Analogists should take into account the

possibility that the technologies to be compared represent improvements in the ecology, as well as the

possibility of their representing threats.

Conclusions :

The above are various dimensions that are considered to forecast with analogy. All the above

dimensions are not necessary in each and every case. Forecaster should always check each dimension to

ascertain whether or not it is important.



TECHNOLOGY FORECASTING THROUGH TREES

The concept of Tree is to explode an activity into its sub-activities representing a tree and its

branches. To understand this concept well, let us take a single assembly activity, say the case of a

refrigerator and its parts :

Refrigerator

Compressor Door Main frame

This appears to be like a tree having several branches.

This concept is used in several areas of problems such as decision making, development of

objectives, development of alternatives, resource-allocation and so on. Depending on the application, they

are called as decision tree, objectives tree, alternative tree, resource – allocation tree etc. However, it is

generally called as “Relevance tree as the relevance sub-activities are exploded from the main activity.

This provides a broad morphological analysis. It helps in not only listing various sub-activities or options

but also provides a way of thinking about technical alternatives against potential changes in the

environment and the user’s concerns (Swager, 1973).

There are mainly three types of relevance trees :

1. Vertically structured relevance tree called relevance tree

2. Horizontally structured relevance tree called Perspective tree

3. Quantitative relevance tree called PATTERN (Honey-well).

The Relevance tree approach is an attempt to return to a natural philosophy in which the

relevancy of a single action can be connected to the objectives of the disciplines as a whole. A model of

the discipline which the final relevance tree represents may not be accurate and complete. It may change

as new data are collected. A properly constructed relevance could provide :

(i) A method for communicating the way activities lead to the main objective

(ii) A means of displaying the assumptions and interdependence

(iii) A basis for objectively assessing priorities with a minimum of bias

(iv) A pedagogical tool which draws together current view, directions and interests of the

activity and its practitioner

(v) A framework for comparing large scale alternative programmes.



Each item on the tree is referred to as a branch. The point from which several branches depend is

a node. Thus, except for these at the top and bottom of the tree, each branch depends from a node and

each has a node from which several other branches depend. There is no requirement that each node has

the same number of branches.

The characteristics of relevance tree are

(i) hierarchical structure (ii) branches depending from a node must be exhaustive (iii) branches

depending from a node must be mutually exclusive (iv) branches form goal and sub goals in a

normative study.

Relevance trees can be used to identify problem and solutions and deduce the performance

requirements of specific technologies. However, they can also be used to determine the relative

importance of efforts to increase the technological performance (Martino, 1973).

1. Relevance Tree : Most of the above discussion is applicable here. However, an example is taken here

to explain this approach better and to enhance the understanding of the approach. The example istaken from Martino (1983).

The Figure 12 shows the relevance tree of an automobile. At the top of the tree is the

‘automobile’. The first level consists of the three elements of the automobile. One of these elements is

further subdivided at the second and lower levels. The other two elements could be subdivided in the

same way.

AUTOMOBILE

PROPULSION STRUCTURE CONTROL

INTERNAL INTERNAL EXTERNAL ELECTRIC

COMBUSTION COMBUSTION OMBUSTION

SECONDARY

BATTERY HYBRID

STRAIN FREON OTHER

ORGANIC

PRIMARY FUEL SECONDARY THIRD INDUCTION

BATTERY CELL BATTERY RAIL FROM BURIED

CABLE

Fig. 12 Relevance Tree showing the major components of an automobile



1.1 Relevance Tree for Normative Forecasting

For normative forecasting, the relevance tree must be viewed as goals and subgoals. Each node isa goal for all branches and the goal is satisfied when its branches are satisfied. The branches of relevance

trees used for normative forecasting will be either problems or solutions.

The Solution Tree has both “and” and “or” nodes. The “or” nodes are the most common. At each

level more than one alternative solutions are possible and a single solution, any one among them, is

sufficient to achieve the next higher level. IN some cases, two or more partial solutions must be

implemented if the higher level solution is to be achieved indicating “and” node.

A problem tree contains only “and” nodes and all the branches (problem) must be solved to

achieve the next higher level.

Normally in technological forecasting, mixed trees, that is containing both problems and

solutions are used.

All these trees depends on the purpose and one cannot find any “universal” tree even for a

specific technology. The tree is designed based on the purpose.

2. PERSPECTIVE TREE

Swager (1969) proposed a tree similar to relevance tree to anticipate future developments

considering the political, social and economic environment and called it Perspective tree. This is

originally named as horizontal relevance tree (Jantsch, 1967). Perspective tree attempts to help one

anticipate relevant factors is three domains :

(i) The external environment, including technology in general,

The environment domain is external to the company and is the one which includes changes and

events – economic, social political and technological (except the technology under study).

(ii) The technology under consideration and available to the institution in question, and Technology

domain includes technical changes available or potentially available to the company or its

competitors for accomplishing technical advances in the business or technology under study.

(iii) Utilities and functions as seen by the user,

The perspective tree provides a way of thinking, abut technical alternatives against potential

changes in the environment and the user’s concerns. It becomes a way of structuring miniscenarios about

numerous aspects of the future (Swager, 1973). It is a qualitative approach to thinking about the future for

purposes of planning and policy development that seeks to discover and anticipate situations rather than



to devise means for reacting to them. A perspective tree, as shown in Fig. 2, is a diagram which

graphically links relevant factors through three domains of concern.

This method is particularly useful in identifying threats and opportunities or policy options which

are subject to further ordering and evaluation.

2.2 Steps in Development and Use of Perspective Trees

Swager (1973) suggested seven steps in preparing perspective trees.

i) Define initial scope :

The scope of the forecast has to be defined at the beginning. The scope may be in terms of

physical product or characteristics of that product or the utilities of the product. Unless, the scope is

clearly stated, the forecast may lead to either a very narrow or very wide aspects. For example, take the

case of electrical automobile. While making technological forecast, one may not think about alternative

automobiles that may compete with electric automobiles instead one may restrict to a narrow forecast of

changes associated with electric automobiles. On the other hand, one may also go for the forecast of

country’s economy peoples’ purchasing power etc. that may also affect electrical automobile.

ii) Develop initial lists of relevant factors :

Once the scope is defined, the relevant factors are listed in the three domains. This may be done

by intuitive understanding of a person or through group activity such as brain storming.

iii) Make array using initial categorization :

Lists of initial factors may include broad macro-level aggregate terms or micro level disaggregate

terms. In order to list precise factors, they are systematically categorized, often under sub headings. For

example, environment factors may be subdivided into social, economic, political and technological

factors.

iv) Fill gaps and identify new factors :

While categorizing into sub-domains and listing the relevant factors, one may find gaps or even

the scope as narrow. Therefore are has to fill the gaps by identifying the new factors even extending the

scope if necessary.

v) Assemble initial forecasts and Purge Array :

The factors listed are nothing but forecasts. After examination one may fix some of the factors as

redundant or irrelevant. Such factors have to be eliminated. The general criteria used for this purpose are :

(a) the forecast change will become significant beyond the time horizon of concern, (b) forecasts are not

relevant because they are included implicitly in other gross forecasts, and (c) even major change of a

factor will not have significant impact on any of the functions or utilities. Quantification of the forecasts

will help make the factors more explicit.



vi) Search for Relationship and Identify Perspective Trees :

This a search for sets of changes in the environment that can be related to sets of changes in

technology through the logic of the utilities and functions. This is achieved through a series of questions,

say what other forecasts in the environment are related and reinforcing or countervailing ?

What deterministic forecasts in technology are related ? Through which utilities and functions ?

What conditional forecasts in the technology domain are related ? Through which utilities and

functions ?

What possibilities of technical change are related ?

Through which utilities and functions ?

The relationships that are found here are expressed as a tree or a partial tree.

vii) Translate to specific threats and opportunities :

Each perspective tree represents area of potential change. As such, each represents a threat or

opportunity depending on the present position of the company.

One of the roles of technological forecasting is the identification and evaluation of potential

change to which a business must respond. The perspective-tree provides a way to develop surveillance

procedure that gives reasonable assurance that the threats and opportunities facing a company will be at

least identified. With such identification , a management team has the opportunity to take better

decisions.

3. PATTERN :

Pattern (Planning Assistance Through Technical Evaluation of Relevance Numbers), which uses

a requirements or need-oriented relevance tree to aid corporate decision makers to identify critical

technology areas requiring upgrading to support the development of future system programmes, is

developed at Honeywell, USA and originally used for planning in the military area (Jantsch, 1973).

However, this method is very flexible and is applicable to any are decisions have to be made under

uncertainty.

The procedure or methodology of PATTERN consists of 6 basic steps.

i) develop relevance tree

ii) develop criteria

iii) assign the weightages

iv) develop relevance numbers

v) evaluation of alternatives

vi) preparation of the report



Relevance tree of the problem under study is developed as discussed earlier.

Criteria provide a basis for evaluation of the alternatives identified through relevance tree.

Criteria may be considered as priority objectives, bases of judgement, and/or reasons for change or

upgrading. The general criteria may be to reduce the costs, increase profits, increase safety, increase the

life of equipment, minimize the pollution emission etc.

Weightages are assigned to each criteria so that their relative importance can be determined. The

total weightages (sum of the wieghtages of all criteria) must be equal to 1. Judgemental techniques can

be used to arrive at the weightages to be assigned. The weightages are also given to variables or

alternatives.

Relevance numbers are determined based o the weightage.

The alternatives are evaluated, i.e. computed using relevance numbers and a decision is taken to

implement a better alternative. The alternative which gives highest relevance number need not be taken as

the best one. Because the practical implications such as capital required may have to be analysed. It is

possible to add such aspects also in the criteria, however, all implication of a problem solution or decision

can not be taken into criteria while analysing the problem.

Once the decision is made, report is prepared providing the analysis and results of the study and

also the recommendation.

j=n k=m

R I =wI Σ Σ WS j * Ck , i = 1, …. l.

j=1 k=1

For two levels :

n m p

R I = WI Σ Σ Σ WS j * WSSk * Ca, i = 1, … 1

j=1 k=1 a=1

and so on.





the future. In the second round the participants receive the suggestions from the first round and are asked

to specify the year in which they expect the suggested events to occur. Thus, the time horizon becomes

their rating scale. The monitor team receives every one’s response and calculates a measure of the central

tendency and of the dispersion (usually the median and inter-quartile range) for each suggestion. In the

third round, all the suggestions, the statistical measures, and any written comments are sent back to the

panelists. Given the feedback of group response, they re-estimate when the events will occur. Reanalysis

of the statistics usually indicates a narrowing of the inter-quartile range, thereby, indicting that there is agreater degree of consensus among the participants. Additional round can generate greater precision, but

most Delphi exercises do not generally go beyond four rounds, since little extra information of narrowing

of opinion is achieved for the effort expended.

2.2 Decision – Analysis Delphi :

A newer use of Delphi process has been made to the process of decision-making. Turoff (1970),

while developing the idea, calls it “Policy Delphi”. He has however, correctly pointed out that Delphi in

such uses is not a decision-making tool, but rather a decision-analysis tool.

In this type of Delphi exercise, the planning horizon is held constant, and the participants evaluate

various objectives or alternatives according to their importance, desirability, feasibility, ease of

implementation, or probability of occurrence. The rounds are fairly similar to the forecasting alternative

solutions. In the second round, he rates each alternative for its importance, and feasibility, etc. The third

round consists of a re-rating, given the statistical feedback of the ratings from the second round. At the

end of the rounds, the alternatives can be assessed for the degree of consensus and their worthwhile-ness

according to different rating criteria.

A review of literature indicates many applications of the Delphi technique. Some interesting

applications are in the following areas :

i) Forecasting

ii) Gathering current and historical data not otherwise accurately available

iii) Evaluating possible budget allocation

iv) Delineating the pros and cons associated with potential policy options

v) Developing causal relationships in complex economic or social phenomena

vi) Distinguishing and clarifying real and perceived human motivations

vii) Exposing priorities of personal values and social goals

viii) Setting corporate goals and objectives,

ix) Generating and evaluating alternative strategies

x) Exploring urban and regional planning options, and

xi) Planning health care systems.

2.3 Guidelines for Conducting a Delphi Study :

The following guidelines should be followed while conducting a Delphi Study.

1. All members should agree to serve on the panel.

2. The procedure for conducting the study should be explained to the panelists in detail.



3. If possible, the panelists should be paid at the usual consultancy rate.

4. Every panel member should be assigned a code number.

5. Two copies of each questionnaire should be sent to the panelists in each round so that he can

retain a copy for his own record.

6. The questionnaire should be easy to understand.

7. It should not contain too many statements. A practical limit has been suggested to be 25.

8. Statement should neither be very lengthy nor very short. Optimum word length has been found inone case as 25 for familiar events. It has to be higher for unfamiliar events.

9. Contradictory forecasts should be included to initiate debate.

10. Injection of moderator’s opinion should be avoided because it has been found to substantially

bias the results.

11. A statement should not contain possibility of occurrence of compound events.

12. A statement should not be ambiguous

13. When editing the respondent’s comments for clarity, the intent of the originator should not be

lost. Similarly, when editing from round to round, meaning of a statement should not be changed.

14. Occasionally, by keeping track of how different subgroups of a respondent group vote on specific

items, it is possible to know how polarizations are taking place.

15. The questionnaire should be presented on any willing expert outside the respondent group.

16. Delphi responses can be processed by a computer.

2.4 Guidelines for selecting Delphi Panelists

A general principle for selecting a panel for a Delhi study is that a variety must be introduced to

avoid bias. Therefore the panelists should belong to different schools of thought, different age groups,

different institutions, different geographical locations, and different sexes, etc.

If the subject matter for a Delphi study concerns an organization only, then, naturally, most of the

panel members will be chosen from within the organization. However, external members must be

included whenever they are likely to contribute greatly to the thinking process.

Internal members most naturally have deep knowledge of the organization. They must maintain

the secrecy. Since the top managers of the organization are usually a very busy set of persons, the internal

members may be chosen from among the managers who are about 2-3 levels lower in the organizational

hierarchy.

External members are expected to be outstanding in the relevant field. They may be selected from

peer judgments, suggestions from internal experts, and suggestions from other panel members.

2.5 Advantages

Delphi is always preferable to any other method whenever a consensus of judgment of a large

number of informed individuals is desired. Compared to the committee meetings, Delphi has the

following advantages :

i) The undue influence of dominant or eloquent personalities is absent.

ii) One need not publicly contradict prestigious personalities.



iii) The tendency to be carried away by majority opinion is absent.

iv) One can always change his views since anonymity is preserved without causing any

embarrassment to himself.

v) Diversified opinions of many informed individuals will always be collected in this

process.

vi) It economizes on the time required by busy individuals since questionnaires can be filled

up at the individual’s convenience.vii) It is relatively cheap to administer.

viii) It facilitates conceptualizations of difficult phenomena.

ix) It has no geographic and scheduling restrictions to get participants together.

x) It has shown high success in encouraging group and individual considerations of factors

that might otherwise be dismissed or neglected in planning.

The other advantages which are claimed for Delphi are the following :

a) It has great utility in obtaining results when no other methodology is appropriate.

b) It is a creative technique which encourages innovative thinking. Hence it is applicable to

ill-structured problems.

c) By generating a consensus of opinion, it facilitates a change in an individual’s social

values and the overall climate of the organization.

d) Ratings from Delphi studies provide quantitative scores for evaluations which can aid the

choice of a course of action.

e) The two-way communication in a Delphi study facilitates understanding and learning on

the part of the participants.

f) The Delphi consensus may lead to a commitment which will lead to easier

implementation. Moreover, a Delphi exercise may be used to identify roadblocks to

implementation.

g) It blends the subjective and objective, the rational and the extra-rational.

h) Delphi has been reported that it has been linked with such other aids as simulation-

games, role-playing, cross-impact matrix, trend extrapolation, and scenario writing.

i) It is very flexible, and is applicable to many situations.

2.6 Common Pitfalls of Delphi

Delphi is not without certain drawbacks albeit it’s many advantages. Most of the drawbacks

originate due to deficiency in the design of the Delphi study by inexperienced monitor teams. The

following is a list of the manor deficiencies :

(a) The inability to make the Delphi objectives specific,

(b) The inability to identify and motivate many “informed individuals” to participate,

(c) The inability to stimulate response,

(d) The inability to appreciate and highlight consensus and divergence,

(e) The inability to refrain from imposing monitor views and preconceptions of a problem upon

the respondent group by over specifying the structure of Delphi,

(f) Though advanced as a structured communication devices, the method suffers from the

following:



i) the communication is too restricted for many problem situations,

ii) the requirement of written feedback editing, and distribution places a high cost on the

communication of ideas, and

g) Delphi panelists often give inconsistent views (Mohapatra et al., 1984).

Over the years, many variations on classical Delphi have been allowed. Some of these variants

are the following :

a) An initial list of events, or some information on the problem context, can be provided to the

panelists.

b) The panelists may be asked to suggest 10%, 50% and 90% likely dates of events (instead of

the conventional most likely date of occurrence). Median of the 50% date is taken as the

median of the group response, whereas the spread between the medians of 10% and 90%

dates is taken as the interquartile range of the group response.

c) On-line real-time Delphi can be practiced if facilities exist. Here the concept of a round

becomes redundant. A panelist directly keys in his scores and is informed of the updated

group response immediately.

d) Direct interaction among the panelists may be allowed.

e) The number of rounds (the stopping criterion) for Delphi study can be determined by

examining if the stability of group response has been achieved. This can be done by studying

the histograms of responses for individual statements from round to round, or by analyzing

the changes in the co-efficient of variation between rounds, or even by carrying out statistical

significance tests for comparing the variances of group response between rounds.

2.7 Conclusion

Over the years, popularity of Delphi and its variants is growing. With new applications of Delphi

studies and its variants and with continued research on its methodological aspects, one hopes that it would

become an important tool in the hands of planners. With careful use, well-thought-out design, and

integration with other techniques, Delphi and its variants can help collect opinion of a large group of

experts in the ill structured areas of forecasting, objective setting, and long range planning.

Documents

Tf-Intro and Methods