A comparison of the methods of technological forecasting

Industrial Marketing Management E.V.A.F., L o n d o n a n d Elsevier Publishing C o m p a n y , A m s t e r d a m - Printed in the N e t h e r l a n d s

A C O M P A R I S O N OF THE M E T H O D S OF T E C H N O L O G I C A L FORECASTING P. D. W i l m o t

SUMMARY

This paper is a brief critical analysis of how each of the existing methods of technological forecasting influences conclusions as to the nature of future developments. It is suggested that the basis of all technological forecasting is a systems analysis in which parameters are subjected to a trend extrapolation to determine how the system may develop in relation to the purpose for which that system exists. Morphological analysis is a means of searching for alternative systems to fulfil the same need and the extent to

INTRODUCTION

In recent years many methods of technological forecasting have been reported in the literature. However, little analysis has been made of the nature of these techniques or of how to relate one to another. A closer examination of the principles and assumptions on which they are based may point out the extent to which each is applicable. The purpose of this paper is to investigate the bases in order to indicate to the industrial manager how tangible steps may be taken to apply these methods. We take our classification from the following exhaustive list provided by Jantsch (1967): Intuitive thinking Brainstorming Delphi analysis Utopia and science fiction Ind. Mark. Manage., 1 (1971)

which any new system is likely to supplant the existing one can be determined by a trend extrapolation of parameters in a similar way as for the original. It is maintained that all other methods of technological forecasting are merely ways of comparing separate analyses of the above type, individual steps in the above processes or ways of quantifying these analyses to greater accuracy. Even in order to select targets in normative forecasting, this basic process must be followed. It is shown diagrammatically how each of the above methods are correlated.

Exploratory forecasting Extrapolation of time series Learning curves Contextual mapping Morphological research Scenario writing Historical analogy Elements of probabilistic forecasting Economic analysis Operational models Aggregated level Normative forecasting Decision matrices Relevance trees Systems analysis Feedback techniques

95

INTUITIVE THINKING

Brainstorming This technique is widely known. It consists of the convening of a panel of persons who can be expected to have original thoughts on the subject under review and who are allowed to discuss the matter freely. Although the unstructured nature of the meeting is usually emphasised, a good deal of preparation before the event and analysis after the event is required by the chairman and convening secretary. Not of least importance are the definition of the scope of the discussion and the selection of the panel. If one examines the nature of information that comes out of such meetings, it is often found that the mode of thought applied in this type of study is similar to that used in morphological analysis. However, some elements of trend extrapolation are employed. If morphological analysis is closely analogous, in order to perform it, the problem must first be broken down into its constituent parts. Therefore a systems analysis is clearly employed as a preliminary stage. The mechanism of brainstorming has been examined quite closely with the interesting conclusion that practice in brainstorming tends to lead to an increase in the yield of new ideas from further brainstorming sessions (Meadow et al., 1959). If morphology is the principle technique involved, it may also follow that this technique can improve with practice. We must here conclude that brainstorming in itself is not a basic technique, but a method of applying a set of techniques.

Delphi Analysis If an organisation wishes to practice technological forecasting today, the first thought is often to resort to Delphi analysis, i.e. the method of questioning a panel of experts according to a carefully structured series of questionnaires which permit independent original speculation as well a feedback to other members of the panel. This method is often held to be related to brainstorming. Analysis of the basic forecasting activities employed indicates that the fundamentals are the same, although reference to literature is possible, and probably a greater element of trend extrapolation is employed. The method is thus a derived technique as is brainstorming. The results of the classic example of the study by the Rand Corporation are shown in Fig. 1 (Gordon and Helmer 1964). 96

Utopia and Science Fiction This method may be quickly dismissed as a "oneman" Delphi. The feedback element is, of course, lacking, compared with the Delphi study. This method is again a derived technique. EXPLORATORY FORECASTING

Extrapolation of Time Series It is almost natural for man to think in terms of trends in time. Thus we try to see the future by looking for the trend in the past. Many technological forecasting enthusiasts denigrate this method, but the past is the one thing really known. The basis of a trend extrapolation is the assumption that the human motives that applied to change in the system in the past will also apply in future. Selection of the right criteria are therefore important. Reference to Figs. 2 and 3 will demonstrate what is meant (Boorer, 1969). If man wishes only to fly faster, then Fig. 2 shows the trend, but if the real criterion is aircraft productivity, the relationship is entirely different, as in Fig. 3. Discontinuity in a trend may not be a weakness in the technique of trend extrapolation, but rather an indication that either the wrong criterion was chosen to begin with or the criterion has changed. With regard to the basic nature of the technique, it is difficult to see any way in which trend extrapolation is derived from other methods, and it must be accepted as a fundamental technique. An assumption that the trend will be followed can lead to morphological examination and normative tarP. D. Wilmot is currently head of market ersearch and technological forecasting at the Plastics and Additives Division of CIBA-GEIGY Ltd. at Basel and is member of the Council of the Electrical Research Association of Great Britain. Formerly, Mr. Wilmot, a physicist, worked five years in the exploratory and applied research departments of Monsanto Chemicals and six years as Development Chemist for International Nickel Ltd. He has been Sales Development Manager of CIBA (ARL) Ltd. at Cambridge; Chairman of the Organising Committee of the First National Industrial Marketing Conference organised by the Industrial Marketing Council at the University of Sussex in 1966; Founder President of the European Technological Forecasting Association (EVAF TF Division); and member of the Industrial Marketing Council.

Ind. Mark. Manage., 1 (1971)

1970-

Desalination of water on commercial scale. Simple and effective human fertility control. New synthetic materials for very light construction. Automated language translation. Transplant of organs. Reliable weather forecasting. Control data storage with side access for information retrieval.

1980-

New comprehensive quantum-particle-relativity theory. Implantation of synthetic organs. Acceptance of non-narcotic drugs to modify personality. Stimulated emission of X or Gamma Rays by laser principle. Primitive artificial life. Mining of ocean floor. Regional weather control.

1990-

Synthetic protein for food on economic scale. Expansion of use of physical or chemical treatment for psychotic cases. General immunisation by biochemical means against bacteria and virus infection. Genetic engineering to control hereditary defects. Use of ocean farming to produce 20% of world's food.

2000-

Biochemicals to stimulate growth of new organs and limbs.

2010-

Drugs to increase intelligence.

2020-

Direct interaction between brain and computer. Chemical control of ageing to extend life span by 50 years. Two-way communication with extraterrestrials. Breeding of intelligent animals for low-grade labour. Manufacture of elements from subatomic building blocks economically. Control of gravitational field. Education by recording information directly on the brain. Long duration coma to permit form of time travel.

Never

Use of telepathy and E.S.P. in communication.

Fig. 1. One of the earliest Delphi Analyses undertaken by Rand Corporation in 1964 was concerned with forecasting scientific breakthroughs. A panel of more than 80 experts was questioned, over four rounds. The above events were forecast with a high degree of convergence at the most probable dates as the analysis proceeded. gets. A comparison of the trend with phenomena following the same trend can lead to the analogy technique. Learning Curves

When first made, a forecast has a large element of inaccuracy, but as more information is acquired, Ind. Mark. Manage., 1 (1971)

the forecast approaches a prediction. A plot of accuracy versus time is a learning curve. This is particularly useful in forecasting quantitative parameters such as costs (Sommers, 1965). This technique is hardly a basic forecasting technique. It is a methodology for quantifying further a forecast once it has been made. 97

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Fig. 3. Graphs of productivity and operating costs over the same period show no discontinuity, indicating that the criteria of productivity and operating costs are more valid than that of speed at the period when the discontinuity occurs in Fig. 2.

Contextual Mapping, The technique o f linking one field o f development with another so as to show the relevance of a series o f related innovations to different areas o f use is 98

Fig. 4. This contextual plot shows how advances in coordination chemistry may have repercussions in other fields. called contextual mapping (Enke, 1965). The diagram so produced is similar in fact to a relevance tree but is in a different schematic form. The thought processes involved are essentially systems analysis with an element of m o r p h o l o g y and trend extrapolation. A n example o f the contextual map is shown in Fig. 4.

Morphological Research One of the fundamental methods of forecasting is morphological research, in which a system is broken down into its basic parameters (Zwicky, 1962). The number of forms the parameters can take are then considered, and the information thus derived can be presented in matrix form. The various combinations that are possible indicate the n u m b e r of forms a system can take. A necessary preliminary step in drawing up the matrix is a systems analysis, but the breakdown of the parameters into their various forms and their correlation are fundamental thought processes. The m e t h o d is thus a basic one. A n example of a morphological matrix is shown in Fig. 5 (Hawthorne, 1969). Scenario Writing The composition o f a wide-ranging picture or series of pictures o f the future, by drawing on existing forecast and correlating them (Kahn, 1965), is not a fundamental method. It is closely related to conIntl. Mark. Manage., I (1971)

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Fig. 5. This figure shows a morphological matrix of the parameters involved in metal shaping. The combination linked in the diagram represents explosion forming. Some combinations derived from this diagram do not yet exist in practice today.

Forecasting on an Aggregate Level In the technological forecasting which is most widely discussed, we are concerned with "breakt h r o u g h s " o f pace setters. However, the determination of rate of diffusion o f a new technology t h r o u g h an industry is equally o f interest to technological forecasting (Mansfield and Hensley, 1960). To analyse the rate is not so much a basic method o f technological forecasting as a process o f quantifying the probabilities of interaction o f various trends and is thus related to the immediately foregoing techniques. NORMATIVEFORECASTING

Decision Matrices textual m a p p i n g and perhaps Delphi analysis.

Historical Analogy The forecast o f change by reference to a similar succession of events in the past is called historical analogy (Mazlish, 1965). In order to c o m p a r e two different systems, something o f a systems analysis is called for. The method also draws on the trend extrapolation approach. It m a y be regarded more as a derived than as a basic technique.

In this m e t h o d a matrix is made for each o f a set o f proposed projects. The capability o f the organisation to cope with each task in the project is assessed, and the total rating for the matrix quantifies the ability o f the organisation to achieve success in the project. It is clear that the innovation must first be recognised. The method is thus a technique of evaluation of the probability o f a successful innovation. A typical matrix is shown in Table I (Smalter, 1964; Esch, 1965).

Elements of Probabilistic Forecasting In technological forecasting we are concerned with changes of technology level. Probability calculation can be used to assess the degree o f likelihood o f the emergence o f a new technology by weighing the socio-economic factors militating for and against the innovation (Mansfield and Hensley, 1960). However, this treatment does not enable one to discover new possibilities. They must be k n o w n before any calculations are made. This technique is thus a means o f quantifying a technological change once it has been identified.

TABLE I This matrix is a means of assessing priorities in the U.S. national defence and aerospace programmes. Under the heading of criteria, a panel of experts assessed the weighting out of unity to be given to the three aspects listed. In a similar fashion they estimated the weighting of each of these criteria in the non-combat, military and exploration fields. In order to obtain an assessment of the priorities of these three latter fields of effort, they obtained the sums of the products of the weightings for each field. "Items on Level A" refers to the relevance tree of Fig. 6 for which these data were obtained. The priorities 0.22, 0.58, 0.20 are often called Relevance Numbers.

Economic Analysis E c o n o m i c analysis, again, is a means of quantifying the effects o f the forecast and is not a basic method of approach.

Operational Models Operational models aim at correlating the variables in a situation. They are really a special f o r m o f m a n y o f the operations carried out under the heading o f economic analysis. As such they are quantifying methods for technological forecasting and are not basic studies in themselves.

Ind. Mark. Manage., 1 (1971)

Criteria

Insuring national survival Demonstrating credible posture Creating favourable world opinion

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Relevance Trees Once a major target has been defined, the subsidiary innovations needed to achieve the target may be systematically analysed and correlated by means of a relevance tree. The selection of the original target is where the basic forecasting is involved. This decision can be made simply at random, or it can be derived from a combination of systems analysis, trend extrapolation and morphological analysis. A relevance tree is shown in Fig. 6 (Esch, 1965).

Relevance Numbers This is a method of rating the priorities of a number of innovative needs in a relevance tree and is thus related to a decision matrix (Esch, 1965).

Systems Analysis In order to think clearly about the parameters which change, it is necessary to give very careful thought to what are the basic features of a system and what role it plays (Lundberg, 1964). Before morphology or trend extrapolation can be considered, this analysis is necessary. It must therefore be considered that systems analysis is a basic method.

Feedback Techniques A forecast is no prediction and can never be one hundred per cent correct. However, if the likely precursor events to the major change predicted are carefully monitored, one may determine in advance when and if the technology will go one way or another (Lenz, 1962). This is clearly not a basic forecasting technique but is a valuable aid to improving the probability of the forecast. CONCLUSIONS

We may thus conclude that out of all the techniques 100

mentioned above only a small number are of direct value in the actual forecasting of events, the remainder being means of quantifying them in terms of magnitude or time after they have already been conceived. To be more specific the basic techniques appear to be: 1) Systems analysis. What is the real object of the system? The problem is reduced to its significant factors. 2) Trend extrapolation. How do the characteristics of the system change with time, so as to meet changes in the demand for its function? The assumption is made that the demand will follow a steady trend and that the parameters of the parts encounter no discontinuities in time. 3) Morphological analysis. How many ways may the parts of the system be assembled? Each of these parts have parameters which change with time as technology progresses. I f one or several of the parameters in a new form of system develop in such a way as to produce a combined effect closer to the current human need than is the case for existing systems, then the new form of the system takes over. The suggested relationships between the different methods are presented in Figs. 7 and 8. In Fig. 7 the methods used to discover forecasts are schematically related. In Fig. 8 the methods which quantify these forecasts in some way are treated in a similar way. All persons concerned with decision making in a technological advanced industry more or less carry out technological forecasting exercises without dignifying them with this title. If, however, it is proposed giving more attention to the advances in techniques, it is clearly not necessary to start with Ind. Mark. Manage., 1 (1971)

-~ SYSTEM I ANALYSIS

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L'analyse morphologique est une m&hode qui permet de trouver d'autres syst6mes pouvant satisfaire les mSmes besoins. Une analyse pour extrapolation dans la direction de l'6volution "trend analysis" permettra de reconna~tre si l'un de ces syst6mes est susceptible de supplanter le syst6me initial. I1 est affirm6 que les autres m6thodes de pr6vision technologique ne sont que des comparaisons d'analyses du type d6crit ou des m6thodes de quantification plus pr6cise de ces analyses. MSme la s61ection de buts dans la pr6vision normative fair appcl ~t cette technique de base. La corr61ation entre les diverses m6thodes mentionn6es est explicit6e pour des diagrammes. ZUSAMMENFASSUNG Ein Vergleich der Methoden technologischer schau.

Vor-

a Delphi analysis The first step might well be to carry out a rigorous systems analysis of the role of the goods or services of the organisation, identifying the parameters which really determine the advances of these systems, e.g. cost per passenger mile or speed of service in a self-service restaurant (whatever the system) examining the trend and crosschecking with morphological analyses. When the ideas come out, that is the time to carry out quantitative exercises and select norms. Your Delphi analysis can be used even at the end of the exercise in order to check the validity of your arguments and confirm trends.

Dieser Vortrag analysiert die bekannten Methoden der technologischen Vorschau (Technological Forecasting), die zur Verfiigung stehen, um die miSglichen Zukunftsentwicklungen voraussehen zu k6nnen. Es wird vorgeschlagen, der technologischen Vorschau eine Systemanalyse zugrunde zu legen, um eine Extrapolation der Parameter vorzunehmen. Diese Analyse zeigt, wie die Tendenzen des Systems wahrscheinlich verlaufen werden, um die voraussichtlichen Bedfirfnisse zu decken. In einer weiteren Phase werden morphologische Analysen durchgeRihrt, um die Vorteile verschiedener Systeme gegeneinander abzuw~igen. Alle technologische Vorschaumethoden lassen sich auf obige grundlegende Analysen zuriickfiihren. Selbst beim "Normative Forecasting" beniitzt man dieses Vorgehen, um die Ziele feststellen zu k6nnen. Aus den Diagrammen geht hervor, welche Beziehungen zwischen den einzelnen Systemen bestehen.

RI~SUMI~

REFERENCES

L a Comparaison des Mkthodes de Pr~vision Technologique.

Bickner, R. E. (1964). The Changing Relationship Between the

Cet article est une analyse des m6thodes de pr6vision technologique en usage actuellement. II est sugg6r6 que toutes les pr6visions de ce genre sont basses sur l'analyse de l'effet que produisent les extrapolations des param6tres dans la direction du "trend" sur le r~sultat recherch6.

March. p. 206. London; Iliffe. Cetron, M. J. (1969). Braille: A Case Study to Get a "Feel"

RELEVANCEj NUMBER

~ DECISIONMATRIX

PROBABILITY TECHNIQUES

FEEDBACKTECHNIQUES (MONITORING)

Fig. 8

Ind. Mark. Manage., 1 (1971)

Air Force and the Aerospace Industry, Memorandum RM4101-PR. Santa Monica; Rand Corp. Boorer, N. W. (1969). The Future of Civil Aviation. Futures. for a Corporate Research and Development Programme, Technological Forecasting, a Practical Approach. p. 219.

New York; Gordon and Breach. Enke, S. (1965). Using Costs to Select Weapons. J. Am. Econ. Assoc. 55. p. 416. 101

Esch, M. E. (1965). Planning Assistance Through Technical Evaluation of Relevance Numbers (Pattern), Proceedings of 17th National Aerospace Electronics Conference. Dayton, Ohio. p. 346. Gordon, T. J. and Helmer, O. (1964). Report on Long Range Forecasting Study, P-2982. Santa Monica; Rand Corp. Hawthorne, E. P. (1969). Morphological Methods Applied to Metal Working Processes, Symposium on Technological Forecasting. University of Birmingham. Jantsch, E. (1967). Technological Forecasting in Perspective. p. 119. Paris; O.E.C.D. Kahn, M. (1965). On Alternative Worm Futures; Issues and Themes, Report HI 525 D. Harmon on Hudson; Hudson Institute.

Lenz, R. C. (1962). Technological Forecasting, Report ASDTDR 62-414. No. AD-408,085. Clearing House for Federal Scientific and Technical Literature. Lundberg, B. K. O. (1964). Pros and Cons of Supersonic Aviation in Relation to Gains and Losses in the Confined Time~Comfort Consideration. J. R. Aeronaut. Sot., 68. p. 611.

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Mansfield, E. and Hensley, C. (1960). The Logistic ProcessTables of the Stoichastic Epidemic Curve and Applications. J. R. Stat. Soc., 1960. p. 332. Mazlish, B. (1965). The Railroad and the Space Programme An Exploration in Historical Analogy. Cambridge, Massachusetts; M.I.T. Meadow, A. and Parnes, S. J. (1959). Evahtation of Training in Creative Problem Solving. J. Appl. Psychol. 43. p. 189. Smalter, D. J. (1964) The Influence of Department of Defense Practices on Corporate Planning. Manage. TechnoL 4. 2. Sommers, R. (1965). Costs Estimates as Predictors of Actual Weapon Costs--A Study of Major Hardware Articles, Memorandum R M 3061 PR. Santa Monica; Rand Corp. Zwicky, F. (1962). Morphology of Propulsive Power. Pasadena; California Institute of Technology.

Ind. Mark. Manage., 1 (1971)