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,
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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
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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)
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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
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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.
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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.
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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.
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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.
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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.
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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.
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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 ?
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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
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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”.
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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.
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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 :
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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
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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.
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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.
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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
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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
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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.
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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
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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.
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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.
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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.
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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:
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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.
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