DEVELOPMENT AND IMPLEMENTATION OF AN ENHANCED OCCUPATIONAL HAZARD MANAGEMENT SYSTEM: CASE STUDY RWANDA SOCIAL SECURITY BOARD

The study's main focus is the establishment of an intelligent software system augmented with Artificial Intelligence for improving occupational hazard management at RSSB, which is crucial in promoting safety and compliance with regulatory frameworks, particularly in risky organizations. The proposed system is intended to facilitate critical processes such as hazard reporting, risk assessment, and safety training, which have been major challenges due to manual handling. By leveraging technologies like data analytics, the system aims to enhance the accuracy, speed, and efficiency of identifying and controlling hazards. Current issues observed, analyzed, and discussed in the study include existing delays and inefficiencies in RSSB's work, data inaccuracies, and low user engagement. The proposed methodology follows a system analysis and design approach, incorporating automation and data integration to streamline processes. Drawing lessons on scaling up best practices in hazard management, the study recommends RSSB adopt a robust Hazard Management System. Such a system would address the current inefficiencies and provide a structured, technology-driven framework to ensure proactive and effective hazard management. The adoption of an HMS would not only improve the accuracy and timeliness of hazard reporting but also foster a culture of safety and compliance within the organization. By integrating advanced AI tools and analytics, RSSB can significantly enhance its capacity to manage occupational risks, ensuring a safer working environment for all stakeholders. This study provides actionable recommendations for policymakers, officials, and safety practitioners to prioritize and implement these improvements for sustainable workplace safety.