Balancing Early Value Creation with Long Term R&D Decisions: Lessons from Robotics Innovation

Abstract

Abstract This paper provides a unique perspective and suggests an original methodology for complex, long-term research and development (R&D) project delivery, on the intersection of model-based systems engineering and agile rapid iteration methodologies, within the context of robotics innovation. It synthesizes best practices and experiences from the past years, offering key principles for future robotic innovation. It also aims to explore the lessons learned from open innovation environments in complex robotics projects, providing insights into this state-of-the-art approach that integrates model-based systems engineering with agile methodologies to foster early value creation. Anonymized real-world robotics projects are analyzed, their strengths encountered, and the invaluable knowledge gained is shared, avoiding long-term business decisions in R&D becoming imprecise and viewed as sunk costs, with negative Net Present Value (NPV) years after their inception. By leveraging an eco-system approach, the research highlights how the new combined methodology can lead to successful commercial robotics outcomes with significant early value creation.