By H. Murat GÜNAYDIN, Ph.D.
The technology forecasting studies which eventually led to the development of the Delphi method started in 1944. At that time General Arnold asked Theodor von Karman to prepare a forecast of future technological capabilities that might be of interest to the military (Cornish, 1977). Arnold got the Douglas Aircraft company to establish in 1946 a Project RAND (an acronym for Research and Development) to study the “broad subject of inter-continental warfare other then surface.” In 1959 Helmer and fellow RAND researcher Rescher published a paper on “The Epistemology of the Inexact Sciences,” which provide a philosophical base for forecasting (Fowles, 1978). The paper argued that in fields that have not yet developed to the point of having scientific laws, the testimony of experts is permissible. The problem is how to use this testimony and, specifically, how to combine the testimony of a number of experts into a single useful statement. The Delphi method recognizes human judgement as legitimate and useful inputs in generating forecasts. Single experts sometimes suffer biases; group meetings suffer from “follow the leader” tendencies and reluctance to abandon previously stated opinions (Gatewood and Gatewood, 1983, Fowles, 1978). In order to overcome these shortcomings the basic notion of the Delphi method, theoretical assumptions and methodological procedures developed in the 1950s and 1960s at the RAND Corporation. Forecasts about various aspect of the future are often derived through the collation of expert judgement. Dalkey and Helmer developed the method for the collection of judgement for such studies (Gordon and Hayward, 1968).
Fowles (1978) asserts that the word Delphi refers to the hallowed site of the most revered oracle in ancient Greece. Forecasts and advices from gods were sought through intermediaries at this oracle. However Dalkey (1968) states that the name “Delphi” was never a term with which either Helmer or Dalkey (the founders of the method) were particularly happy. Dalkey (1968) acknowledged that it was rather unfortunate that the set of procedures developed at the RAND Corporation, and designed to improve methods of forecasting, came to be known as “Delphi”. He argued that the term implies “something oracular, something smacking a little of the occult”, whereas, as a matter of fact, precisely the opposite is involved; it is primarily concerned with making the best you can of a less than perfect kind of information.
One of the very first applications of the Delphi method carried out at the RAND Corporation is illustrated in the publication by Gordon and Helmer (1964). Its aim was to assess the direction of long-range trends, with special emphasis on science and technology, and their probable effects on society. The study covered six topics: scientific breakthroughs; population control; automation; space progress; war prevention; weapon systems (Gordon and Helmer, 1968). The first Delphi applications were in the area of technological forecasting and aimed to forecast likely inventions, new technologies and the social and economic impact of technological change (Adler and Ziglio, 1996). In terms of technology forecasting, Levary and Han (1995) state the objective of the Delphi method as to combine expert opinions concerning the likelihood of realizing the proposed technology as well as expert opinions concerning the expected development time into a single position. When the Delphi method was first applied to long-range forecasting, potential future events were considered one at a time as though they were to take place in isolation from one another. Later on, the notion of cross impacts was introduced to overcome the shortcomings of this simplistic approach (Helmer, 1977).
According to Wissema (1982), unfortunately the Delphi method is also sometimes used for a normal inquiry among a number of experts. Delphi has found its way into industry, government, and finally, academe. It has simultaneously expanded beyond technological forecasting (Fowles, 1978). Since the 1950s several research studies have used the Delphi method, particularly in public health issues (such as, policies for drug use reduction and prevention of AIDS/HIV) and education areas (Adler and Ziglio, 1996; Cornish, 1977).
In the original Delphi process, the key elements were (1) structuring of information flow, (2) feedback to the participants, and (3) anonymity for the participants. Clearly, these characteristics may offer distinct advantages over the conventional face-to-face conference as a communication tool. The interactions among panel members are controlled by a panel director or monitor who filters out material not related to the purpose of the group (Martino, 1978). The usual problems of group dynamics are thus completely bypassed. Fowles (1978) describes the following ten steps for the Delphi method:
1. Formation of a team to undertake and monitor a Delphi on a given subject.
2. Selection of one or more panels to participate in the exercise. Customarily, the panelists are experts in the area to be investigated.
3. Development of the first round Delphi questionnaire
4. Testing the questionnaire for proper wording (e.g., ambiguities, vagueness)
5. Transmission of the first questionnaires to the panelists
6. Analysis of the first round responses
7. Preparation of the second round questionnaires (and possible testing)
8. Transmission of the second round questionnaires to the panelists
9. Analysis of the second round responses (Steps 7 to 9 are reiterated as long as desired or necessary to achieve stability in the results.)
10. Preparation of a report by the analysis team to present the conclusions of the exercise
Delbecq et al., (1975) argue that the most important issue in this process is the understanding of the aim of the Delphi exercise by all participants. Otherwise the panelists may answer inappropriately or become frustrated and lose interest. The respondents to the questionnaire should be well informed in the appropriate area (Hanson and Ramani, 1988) but the literature (Armstrong, 1978; Welty, 1972) suggest that a high degree of expertise is not necessary. The minimum number of participants to ensure a good group performance is somewhat dependent on the study design. Experiments by Brockhoff (1975) suggest that under ideal circumstances, groups as small as four can perform well.
Before deciding whether or not the Delphi method should be used, it is very important to consider thoroughly the context within which the method is to be applied (Delbecq et al. 1975). A number of questions need to be asked before making the decision of selecting or ruling out the Delphi technique (Adler and Ziglio, 1996):
· What kind of group communication process is desirable in order to explore the problem at hand?
· Who are the people with expertise on the problem and where are they located?
· What are the alternative techniques available and what results can reasonably be expected from their application?
Only when the above questions are answered can one decide whether the Delphi method is appropriate to the context in which it will be applied. Adler and Ziglio (1996) further claim that failure to address the above questions may lead to inappropriate applications of Delphi and discredit the whole creative effort.
The outcome of a Delphi sequence is nothing but opinion. The results of the sequence are only as valid as the opinions of the experts who made up the panel (Martino, 1978). The panel viewpoint is summarized statistically rather than in terms of a majority vote.
The Delphi method has got criticism as well as support. The most extensive critique of the Delphi method was made by Sackman (1974) who criticizes the method as being unscientific and Armstrong (1978) who has written critically of its accuracy. Martino (1978) underlines the fact that Delphi is a method of last resort in dealing with extremely complex problems for which there are no adequate models. Helmer (1977) states that sometimes reliance on intuitive judgement is not just a temporary expedient but in fact a mandatory requirement. Makridakis and Wheelright (1978) summarize the general complaints against the Delphi method in terms of (a) a low level reliability of judgements among experts and therefore dependency of forecasts on the particular judges selected; (b) the sensitivity of results to ambiguity in the questionnaire that is used for data collection in each round; and (c) the difficulty in assessing the degree of expertise incorporated into the forecast. Martino (1978) lists major concerns about the Delphi method:
· Discounting the future: Future (and past) happenings are not as important as the current ones, therefore one may have a tendency to discount the future events.
· The simplification urge: Experts tend to judge the future of events in isolation from other developments. A holistic view of future events where change has had a pervasive influence cannot be visualized easily. At this point cross-impact analysis is of some help.
· Illusory expertise: some of the experts may be poor forecasters. The expert tends to be a specialist and thus views the forecast in a setting which is not the most appropriate one.
· Sloppy execution: there are many ways to do a poor job. Execution of the Delphi process may loose the required attention easily.
· Format bias: it should be recognized that the format of the questionnaire may be unsuitable to some potential societal participants.
· Manipulation of Delphi: The responses can be altered by the monitors in the hope of moving the next round responses in a desired direction.
Goldschmidt (1975) agrees that there have been many poorly conducted Delphi projects. However, he warns that it is a fundamental mistake to equate the applications of the Delphi method with the Delphi method itself, as too many critics do. There is, in fact, an important conceptual distinction between evaluating a technique and evaluating an application of a technique.
On the other hand there have been several studies (Ament, 1970; Wissema, 1982; Helmer, 1983) supporting the Delphi method. A study conducted by Milkovich et al. (1972) reports the use of the Delphi method in manpower forecasting. The results of the comparison indicated high agreement between the Delphi estimate and the actual number hired and less agreement between quantitative forecasts and the number hired. Another study by Basu and Schroeder (1977) reports similar results in a general forecasting problem. They compared Delphi forecasts of five-year sales with both unstructured, subjective forecasts and quantitative forecasts that used regression analyses and exponential smoothing. The Delphi forecasting consisted of three rounds using 23 key organization members. When compared against actual sales for the first two years, errors of 3-4% were reported for Delphi, 10-15% for the quantitative methods, and of approximately 20% for the previously used unstructured, subjective forecasts.
In general, the Delphi method is useful in answering one, specific, single-dimension question. There is less support for its use to determine complex forecasts concerning multiple factors. Such complex model building is more appropriate for quantitative models with Delphi results serving as inputs (Gatewood and Gatewood, 1983). This point is supported by Gordon and Hayward (1968) who claim that the Delphi method, based on the collation of expert judgement, suffers from the possibility that reactions between forecasted items may not be fully considered. The need for the cross impact matrix method of forecasting integrated with the Delphi method is pointed out by many researchers (Gordon and Hayward, 1968; Gatewood and Gatewood, 1983; Adler and Ziglio, 1996). An improvement in forecasting reliability over the Delphi method was thought to be attainable by taking into consideration the possibility that the occurrence of one event may cause an increase or decrease in the probability of occurrence of other events included in the survey (Helmer, 1978). Therefore cross impact analysis has developed as an extension of Delphi techniques.
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