A Smart Maritime HR Analytics Framework for Talent Forecasting and Operational Efficiency

Resumen

The maritime sector is going through a dynamic change, shaped by globalization, digitalization and changing operational requirements that result in major challenges in workforce planning, retaining talent and aligning skills. Maritime organizations face challenges with traditional HRM practices, such as reactive decision-making, which prevent them from predicting manpower shortages, optimizing crew deployment, and improving individual employee performance in dynamic operations. Random Forest Algorithm for talent forecasting, attrition prediction, performance prediction and Genetic Algorithm for workforce allocation and crew optimization. The proposed model brings together and combines various HR and operations data sources, such as employee competencies, performance records, training logs, employee attrition metrics, competency maps, employee schedules, and operational workload metrics, to create actionable human resource intelligence. These include advanced analytical tools like machine learning powered forecasting, workforce segmentation, predictive attrition modelling, and optimization algorithms, enhancing talent acquisition planning, anticipating skill shortages, and enabling efficient workforce deployment in maritime operations. The framework is also built around the concept of adaptive decision support which enables the organizations to align their human capital strategies to operational requirements, safety requirements and organizational sustainability. In conclusion, the proposed framework offers a comprehensive and structured solution that integrates predictive talent analytics with operational optimization, empowering maritime organizations to optimize productivity, reduce employee disruptions, streamline retention efforts, and enhance operational resilience. Moreover, the framework also enables informed management decisions based on real-time analysis, thus helping to create a more agile, efficient and sustainable maritime workforce ecosystem. The study provides a conceptual framework for maritime HRM systems that the potential of AI-driven analytics to impact the future of workforce management and operational efficiency in the maritime industry.The research also sets the stage for intelligent maritime HRM systems and emphasizes the importance of AI-powered analytics in shaping the future of maritime workforce management and operational efficiency.