In the future, it is unlikely that complex system products will compete solely on the basis of technical performance. What will differentiate such systems and their developers is the ability to balance all the dimensions of product performance, including product pricing and timing (which are functions inclusive of development cost and cycle time). Furthermore, this balance must be congruent with customers' perceptions of value. Once this value is ascertained or approximated, complex system developers will require the capability to adjust the design process to meet these expectations. The required amount and sophistication of project planning, control, information, and flexibility is unprecedented. The primary goal of this work is a method to help managers integrate process and design information in a way that supports making decisions that yield products congruent with customer desires and strategic business goals. This work consists of three parts. Part one contains two exploratory studies that further understanding of complex system product development processes. One study explores process iteration and seeks to explain why some aircraft development programs do not address iteration with existing project planning and control methods. The other study examines sources of risk, classifying these into six categories (cost, schedule, performance, technology, business, and market risks) and building causal frameworks to represent their relationships. Both studies point to avenues for improving existing process models and in some cases reveal process characteristics requiring new methods. These results, while derived from projects in the aerospace industry, are highly applicable across a variety of complex system development projects. Part two entails an effort to model some of the characteristics observed in part one. After a review of four types of dependency structure matrices (DSMs), notably the activity-based or schedule DSM, extensive data are collected from an uninhabited aerial vehicle (UAV) design process. Part two thus describes how to build a DSM model and provides data for example applications of the detailed models developed in part three. Based on the foundational work of parts one and two, part three develops a new methodology and models for understanding product development process cost, schedule, and performance. The methodology complements activity-centric schedule models such as DSM in that activities provide direct contributions to process cost and schedule and design performance. This approach sets the stage for integrated cost, schedule, and performance analyses. A cost and schedule model is presented first, and it is extended to account for the effects of activities on product performance. The stochastic, simulation model generates distributions of possible cost, schedule, and performance outcomes. These distributions represent uncertainty and are analyzed in relation to impact functions and targets to determine levels of risk. The model outputs enable the exploration of the costs and benefits of several management options and yield interesting insights. The goal is to improve product development planning and control though the capability to balance cost, schedule, and performance appropriately. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
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