Understanding the Effects of Product Architecture on Technical Communication in Product Development Organizations

Understanding the effects of product architecture on technical communication in product development organizations by Manuel E. Sosa, Steven D. Eppinger, and Craig M. Rowles

This paper examines the impact of architectural decisions on the level of defects in a product. We view products as collections of components linked together to work as an integrated whole. Previous work has established modularity (how decoupled a component is from other product components) as a critical determinant of defects, and we confirm its importance. Yet our study also provides empirical evidence for a relation between product quality and cyclicality (the extent to which a component depends on itself via other product components). We find cyclicality to be a determinant of quality that is distinct from, and no less important than, modularity. Extending this main result, we show how the cyclicality–quality relation is affected by the centrality of a component in a cycle and the distribution of a cycle across product modules. These findings, which are based on analysis of open source software development projects, have implications for the study and design of complex systems.

Read Paper

Factors that Influence Technical Communication in Distributed Product Development: An Empirical Study in the Telecommunications Industry

Factors that influence technical communication in distributed product development : an empirical study in the telecommunications industry by Manuel E. Sosa, Steven D. Eppinger, Michael Pich, David G. McKendrick, and Suzanne K. Stout

Understanding the communication process in product development organizations has been recognized as a key element to improve product development performance. It is particularly interesting to study information exchanges in geographically distributed product development teams because of the highly interdependent nature of design organizations. AAdditionally, the use of electronic-based communication media has changed how development teams communicate. By studying the way product development teams use various communication media (face-to-face, telephone, media), we assess how the process of exchanging technical information is influenced by factors such as geographic dispersion, organizational bonds, and degree of team interdependence. We develop a theoretical framework that allows us to formulate several hypotheses about how these factors influence both communication frequency and media choice. We use empirical evidence from the telecommunications industry to test our hypotheses. We confirm previous results about the obstructive influence of distance on technical communication. However, we found that such negative effects may be mitigated by other factors such as the recognizing of highly interdependent team members, the existence of strong organizational bonds, and the use of electronic communication media.

Read Paper

Modeling Impacts of Process Architecture on Cost and Schedule Risk in Product Development

Modeling Impacts of Process Architecture on Cost and Schedule Risk in Product Development by Tyson R. Browning and Steven D. Eppinger

To gain competitive leverage, firms that design and develop complex products seek to increase the efficiency and predictability of their development processes. Process improvement is facilitated by the development and use of models that account for and illuminate important characteristics of the process. Iteration is a fundamental but often unaddressed feature of product development (PD) processes. Its impact is mediated by the architecture of a process, i.e., its constituent activities and their interactions. This paper integrates several important characteristics of PD processes into a single model, highlighting the effects of varying process architecture. The PD process is modeled as a network of activities that exchange deliverables. Each activity has an uncertain duration and cost, an improvement curve, and risks of rework based on changes in its inputs. A work policy governs the timing of activity execution and deliverable exchange (and thus the amount of activity concurrency). The model is analyzed via simulation, which outputs sample cost and schedule outcome distributions. Varying the process architecture input varies the output distributions. Each distribution is used with a target and an impact function to determine a risk factor. Alternative process architectures are compared, revealing opportunities to trade cost and schedule risk. Example results and applications are shown for an industrial process, the preliminary design of an uninhabited combat aerial vehicle. The model yields and reinforces several managerial insights, including: how rework cascades through a PD process, trading off cost and schedule risk, interface criticality, and occasions for iterative overlapping.

Read Paper