Using process simulation to manage new product development pipeline throughput

New product development is complex. Companies often underestimate this complexity, and don't invest in efforts to fully understand their new product development system and the ramifications of running that system without control. New product development involves dedicated resources, from multiple disciplines, for often, long periods of time. These resources are precious and decisions about how they are utilized should be informed. Without visibility to the many intricacies of a company's new product development system, it is difficult to know when a pipeline is running out of control and how to fix it, until programs actually begin to fail. When the pipeline does not produce projects at a fast enough pace, frequently the response is to set ever more aggressive goals, resulting in even more pipeline inefficiencies. Inefficiencies arise from fragmented focus when resources are over-utilized. Slower tasks, infra-phase errors and late project errors occur when people are allocated to too many projects. It is often assumed that queue theory will prevail and natural shielding of resources will occur. Since the ability to multi-task is viewed as an asset in most companies, queues do not exist and over allocated resources will try to progress all of their work simultaneously in an attempt to meet their deadlines. This research provides a simulation model of a full new product development pipeline, incorporating this common organizational pathology, consistent with the literature and the researcher's experience. It shows how the attempt to push too many projects through the pipeline is often detrimental to pipeline throughput. This project considers the fact that queues do not occur in new product development and resources can be allocated greater than 100%. Decreased efficiencies have been incorporated in the model, for over-allocation situations, to demonstrate how the pipeline slows down, project execution quality declines and unplanned costs increase when resources are over-stretched.