Issues in Technological Forecasting

Published on by Joannes Vermorel.

Business forecasting, of course, comes in all shapes and sizes.

What I want to talk about for the next few minutes is forecasting that contains a technological element. In a case like this, a forecast deals with the characteristics of the technology itself—such things as levels of technical performance, like the speed of a military aircraft, the power of a future possible engine, the accuracy or precision of a measuring instrument for example.

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

Importantly of course, technological forecasting usually deals only with useful machines, procedures or techniques—excluding from this definition those commodities, services or techniques intended only (or mainly) for luxury or amusement purposes.

Recitation of Alternatives

There really is no alternative to forecasting, and that is the main purpose of the presentation of alternatives—to show just that.

The point is that if a decision maker has several choices open to him, he will choose among them on the basis of which provides him with the most desirable outcome—thus his decision is based on a forecast.

The only alternative open to him is whether the forecast is obtained by rational and unambiguous methods or by intuitive means.

The virtues of using rational methods of forecasting are as follows:

  1. They can be taught and learned
  2. They can be described and explained
  3. They provide a procedure able to be followed by anyone who has absorbed the necessary training, and in some cases,
  4. These methods are even guaranteed to produce the same forecast regardless of who uses them!

The main benefit of using a rational method to forecast is that those forecasts can always be reviewed by others (including at any subsequent time in the future), and they can be checked for consistency.

Commonly adopted, and accepted, methods of technology forecasting include the Delphi method, forecast by analogy, growth curves and extrapolation.

Normative methods, such as relevance trees, morphological modes and mission flow diagrams are also used.

Studies of past forecasts have shown, not surprisingly, that that the most frequent reason why a forecast goes wrong is that the forecaster has ignored related fields.

Hence the value and wisdom of combining forecasts. The point is that a given technical approach may fail to accurately forecast because it has been superseded by another technical approach—which the forecaster ignored.

Yet another problem that often occurs is that of inconsistency between forecasts. Therefore it makes sense to combine the forecasts of different technologies rather than trying to select and utilize just one. What happens then is that the strengths of one method may balance out, and compensate, for the weaknesses of the other.

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