Abstract
This experience report analyses a one-year project focused on building a distributed real-time analytics system using edge computing and machine learning. The project faced critical setbacks due to a “big-bang” integration approach, where all components–developed by multiple geographically dispersed partners–were merged at the final stage. The integration effort resulted in only six minutes of system functionality, far below the expected 40 min. Through root cause analysis, the study identifies technical and organisational barriers, including poor communication, lack of early integration testing, and resistance to top-down planning. It also considers psychological factors such as a bias toward fully developed components over mock-ups. The paper advocates for early mock-based deployment, robust communication infrastructures, and the adoption of top-down thinking to manage complexity and reduce risk in reactive, distributed projects. These findings underscore the limitations of traditional Agile methods in such contexts and propose simulation-driven engineering and structured integration cycles as key enablers for future success.