Exploratory and normative technological forecasting: A critical appraisal

Abstract

Comparison of the still evolving approaches to “exploratory” and “normative” technological forecasting yields marked contrasts. In particular the simple schemes used by those trying to predict the technology of the future look pallid when matched against the intricate techniques designed by those who are allocating the resources that will create the future. Exploratory technological forecasts are largely based either on aggregates of “genius” forecasts (e.g., the Delphi technique) or on the use of leading indicators and other simple trend-line approaches. The practitioners of economic forecasting, in contrast, long ago recognized the need for multivariate systems analysis and cause-effect models to develop reliable predictions.

So-called “normative” forecasting is at the opposite extreme on the sophistication scale, fully utilizing Bayesian statistics, linear and dynamic programming, and other operations research tools. Here, despite the uniqueness, uncertainty, and lack of uniformity of research and development activities, the typical designer of a normative technique has proposed a single-format wholly quantitative method for resource allocation. Along the dimensions of unjustified standardization and needless complexity, for example, the proposed R & D allocation methods far exceed the general cost-effectiveness approach used by the Department of Defense in its program and system reviews.

For both exploratory and normative purposes, dynamic models of broad technological areas seem worthy of further pursuit. In attempting to develop “pure predictions” the explicit recognition of causal mechanisms offered by this modeling approach seems highly desirable. This feature also has normative utility, provided that the dynamic models are limited in their application to the level of aggregate technological resource allocation and are not carried down to the level of detailed R & D project funding.