Scaled Agile Value Stream Delivery Process Optimization in Software Development Companies

The thesis research investigates the critical role of metrics in optimizing Scaled Agile Value Stream Delivery within software development companies. Through examining existing practices, emerging trends, and the experiences of industry professionals, this study aims to provide valuable insights and recommendations for organizations seeking to improve their value stream performance. The research explores various aspects of value stream management, including the use of Agile Release Trains, Program Increments, and Value Stream Mapping. It also investigates the challenges organizations face in implementing Scaled Agile Framework and the strategies to overcome these challenges. A key focus of the research is on the use of metrics to measure and optimize value stream performance. The study examines traditional metrics as well as novel metrics that can provide unique insights into collaboration, innovation, and customer satisfaction. Additionally, the research explores the use of data analytics and emerging technologies to enhance value stream optimization. The research found that effective value stream management is crucial for successful Scaled Agile implementation, with key challenges including complexity, data quality, and resistance to change. Another key finding was the organizations are increasingly leveraging data analytics and emerging technologies like AI and machine learning to optimize their value streams and gain a competitive advantage. This research provides a foundation for future studies that can further refine the understanding of value stream optimization in the dynamic and evolving landscape of software development.