The challenge of delivering capital projects, including field developments, in accordance with objectives is well established—as is commentary regarding poor productivity, lack of innovation, and other such reasons. What is not well understood is why this occurs and, more importantly, how to address the underlying issue. There is a gap in the current approach to project delivery—the lack of acknowledgement and understanding that projects are production systems and thus should be managed as such. Currently, immense resources are invested in predicting final cost and project duration using techniques developed in the 1950’s and 1960’s, with little if any attention paid to the production system that will deliver the asset, including when and for how much. Further compounding the issue is that current methods, processes, and systems do not enable the application of rapidly evolving digital technologies, such as machine learning and IoT. The application of Operations Science, coupled with recent advancements in data science and digital technology, provides the foundation for a new approach to project delivery, an approach where production systems self-organize and self- optimize to reduce project risk, duration, cost, and expense.