Organizations operate under ongoing pressure to conduct product development (PD) in ways that reduce errors, improve product designs, and increase speed and efficiency. Often, managers are expected to respond to this pressure by implementing process improvement programs (PIPs) based on best practices elsewhere (e.g., in another part of their organization or in another industrial context). Successful PIP implementation depends on two criteria: (a) demonstrating (symbolic) success by meeting externally imposed deadlines and producing mandated artifacts and (b) sustaining the expected (substantive) changes in their employees' underlying beliefs and practices. Given the mixed success of PIPs in nonmanufacturing contexts, identifying factors that contribute to both symbolic and substantive implementation is important to both researchers and practitioners. We explore this challenge through an in‐depth field study at a PD company (DevCo) that implemented a PIP across its 11 PD projects. We examine DevCo's change message to implement the PIP, how DevCo's engineers experienced it, factors that impeded implementation, and factors that could improve substantive success. Along with this empirical evidence, we leverage organizational change concepts to facilitate effective PIP implementation in new contexts such as PD. We distill our findings into eight propositions that expand theory about effectively transferring PIPs across contexts.
This paper proposes the integration of two systems engineering analysis tools, the Design Structure Matrix (DSM) and Network Analysis (NA), to study task interactions in a Product Development Process (PDP). The DSM is a matrix-based systems engineering tool that analyzes task sequences to improve PDP execution. Using NA metrics to measure properties of information flow helps to identify important product development tasks and interactions that constrain PDP execution. Project managers can use these data to structure team integration mechanisms or to identify coordinating mechanisms for groups of concurrently scheduled PDP tasks. Functional managers and process architects can use these data to identify important or overloaded tasks. They can also evaluate whether tasks like stage gates and design reviews are acting as effective information flow regulators in the PDP. This new Systems Engineering approach provides a rigorous decision support tool for managers who must alter ideal task sequences due to specific schedule, budget, and expertise constraints encountered on their projects.
Distributed product development teams require integration of expertise from multiple technical disciplines and, in some companies, geographical and organizational diversity as well. Systems engineering methodologies can be applied to measure and support the effectiveness of knowledge sharing in complex, time sensitive development environments. In addition, effective knowledge sharing can reduce the incidence of failed coordination and adverse events. In this paper, three conceptual frameworks are proposed to help address these issues. Concepts of knowledge clusters, multiple dimensions of expertise, and information foraging are shown to affect structure, process and timing of team behaviors and project outcomes. These frameworks provide systematic analysis and usable knowledge sharing tools to coordinate knowledge transfer across expertise boundaries within a product development team. Specific methods can be used to move information across these boundaries to improve information alignment and organizational efficiency.
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