New product development (NPD) projects are typically managed through a series of screens, or gates, where ideas compete for resources. Ideas are carved into projects, and these projects are reviewed, and approved or terminated through the screening process so that only the best performing projects continue to subsequent stages of design, development and testing, and are released into the market place (Krishnan and Ulrich 2001; Terwiesch and Ulrich 2009). Most large innovative organizations deal with more than one NPD project at a time and typically engage in product pipeline management (PPM), where a set of active projects are evaluated together while they traverse through a sequence of such screens. Key decisions in a R&D pipeline are: screen thresholds, complexity of projects, resource allocation and capacity adjustment biases. We explore the impact of structural and behavioral aspects of these decisions through a simulation based analysis of a pharmaceutical dataset. Results establish concave relationships between value created at the end of pipeline and the resource allocation and complexity allocation biases, indicating optimizability and a limit for front loading practices.