Abstract
Decades after its observation and description by T. P. Wright (1936), unit cost improvement is a well-documented characteristic of production processes. Since that time, however, it has remained chiefly an empirical phenomenon. Cost analysts have few objective tools to apply to the prediction of cost improvement in future production programs. This problem is particularly acute in the aerospace industry. In this arena, prime contractor and government cost analysts must provide estimates for multi-billion dollar programs involving new products and technologies, which may not be entering production for years. Current methodologies involve the use of analogies and standards that are subjective and often difficult to justify. The research described in this paper, making use of a dataset comprised of 30 diverse aerospace programs, investigated whether parametric methods can be employed to model variation in cost improvement. Using a simple theory of cost improvement based on the scale, complexity, and design stability of the products, it found that parametric models may have utility in predicting the cost improvement of future programs.