Increasing the predictability of the Radar Front-End Engineering department at Thales NL

This research investigates methods to increase the predictability of the Radar Front-end Engineering (RFE) department at Thales NL. The current development process, combining the waterfall V, incremental, and iterative models, faces challenges in meeting budgets and deadlines due to bottlenecks like focusing too much on details, poor communication, and unrealistic timelines. The study identifies key areas for improvement, including implementing better Key Performance Indicators (KPIs), predictability calculations, and a comprehensive dashboard for real-time monitoring. Recommendations include refining management techniques, adopting the Analytical Hierarchy Process for further KPI optimization, and incorporating agile elements to increase flexibility. Despite limitations in data reliability and scope, the research provides actionable insights for enhancing the RFE department's project predictability.