Advisers

Wendyll P. Ojastro

Discipline

IT & management

Abstract

Hospitals face challenges in employee development due to fragmented HR processes, leading to unclear career paths and low staff motivation. The lack of a structured system for tracking skills, performance, and training creates inefficiencies and hinders workforce planning. To address this, the Hospital 2: Human Resources 2 system was conceptualized to provide an AI-powered platform for talent management. It centralizes employee profiling, automates performance evaluations, and delivers personalized career path recommendations to foster professional growth and improve organizational efficiency. The system was developed using Agile Scrum methodology to enable iterative development and continuous stakeholder feedback. Requirements were gathered through interviews, observation of HR workflows, and document analysis. A microservices architecture was adopted and aligned with TOGAF’s four domains, ensuring a scalable and secure design. DevOps practices with CI/CD pipelines facilitated continuous integration and deployment. Role-based access control was implemented to ensure secure and appropriate system access for HR administrators, employees, and managers. The system automated employee profiles, performance evaluation, training management, and AI-based career recommendations. Testing and user validation were described as showing improved tracking, lower HR workload, and greater visibility of career opportunities. No participant count, recommendation-performance metric, processing-time measure, workload comparison, or user-rating result was reported. The platform may support centralized talent development and career planning. However, claims of significant efficiency, transparency, engagement, or decision improvement require measurable evaluation and safeguards addressing recommendation quality, bias, privacy, and employee appeal or review.

Keywords

agile scrum, career development, workflow automation, human resource management, ai-based recommendation, talent management, microservices architecture