SCHOOL MANAGEMENT SYSTEM: A MANAGEMENT INFORMATION SYSTEM FEATURING ADAPTIVE WORKFLOW AUTOMATION WITH PREDICTIVE ANALYTICS AND FORECASTING

Abstract

This study introduces a School Management Information System (MIS) that incorporates adaptive workflow automation alongside predictive analytics and forecasting capabilities. The system is developed to address existing inefficiencies in administrative operations, alleviate staff workloads, and support data-driven decision-making. Prompted by challenges such as the burden of manual tasks and the lack of transparency in payment tracking at Bestlink College of the Philippines, the project seeks to improve operational efficiency, accuracy, and institutional transparency. The development of the system followed the Agile Scrum methodology, incorporating clearly defined roles, structured sprints, and iterative feedback to ensure continuous improvement. The system architecture was based on a microservices approach, promoting modularity and scalability, while enterprise architecture principles were applied to support the seamless integration of multiple functional modules. Key features of the system include real-time dashboards, adaptive workflow automation, predictive analytics models, and a receipt verification mechanism designed to enhance financial transparency. The resulting Management Information System (MIS) streamlined student data management, automated key administrative workflows, and introduced predictive capabilities that enabled proactive decision-making. The integration of AI-driven forecasting tools allowed administrators to anticipate trends and strategically prepare for future scenarios. Additionally, the receipt verification feature enhanced financial transparency by ensuring payment accuracy, thereby reducing concerns among students and parents. The integration of artificial intelligence and Agile development practices proved effective in meeting the dynamic needs of higher education institutions. Adaptive workflow automation increased responsiveness to evolving academic conditions, while predictive analytics supported more informed and strategic planning. The adoption of a microservices architecture, combined with DevOps principles, ensured that the system remained flexible, secure, and maintainable. Continuous feedback from stakeholders played a critical role in guiding iterative enhancements, underscoring the system’s adaptability and long-term value.