A structured approach to measuring and optimizing the organizational architecture in global product development projects. (September 2020)

• Record Type: Journal Article
• Authors: Kherbachi, Sonia; Yang, Qing; Khan, Sher Zaman
• Is Part Of: Concurrent engineering, research and applications. Volume 28:Number 3(2020:Sep.)
• Page Start: 161
• Page End: 174
• Publication Date: 2020-09
• Subjects: global product development project -- organization optimization -- clustering -- design structure matrix -- similarity matrix; Production engineering -- Periodicals; Concurrent engineering -- Periodicals; 621.39
• DOI: 10.1177/1063293X20929388
• Languages: English
• ISSNs: 1063-293X

Abstract

In global product development projects, coordinating complex technical communication among teams across time zones in the overlapping process is a fundamental challenge. To optimize a global product development organization to reduce the negative impact of time separation on coordination, this article presents an innovative approach to solve two key problems: how to quantify the coordination among distributed teams and how to identify efficient global product development organization. We build structural models to capture the coordination dependency strength among global product development teams from the time separation and overlapping process perspectives, employing the design structure matrix method. Then, we analyze the factors that influence synchronous and asynchronous communication due to time separation. We also apply the random walk method to identify a team similarity matrix, taking into account the direct and indirect dependency relationships among teams associated with their performed activities. Finally, we use the team similarity matrix as an input to a spectral clustering algorithm to identify the clustering strategy for the global product development organizational architecture, yielding and reinforcing several managerial insights, including how to analyze the coordination among global product development teams as well as how the offshoring costs impact the clustered organization.