Enterprise Healthcare Business Intelligence Platform Enhancement and Support System

The organization faces increased demand for developing, customizing, and supporting healthcare analytics solutions across a growing client base. Existing internal teams lack sufficient capacity for ongoing maintenance, client-specific modifications, and rapid feature deployment. This results in slower change request implementation, high overhead for support tasks, and a need for a dedicated, scalable support and development framework.

A global leader in healthcare data analytics, ML, and AI systems serving pharmaceutical companies, device manufacturers, health agencies, and medical researchers. The organization develops complex healthcare products and requires robust analytical and data management solutions.

• Establish a dedicated support and development team to handle change requests, customizations, and maintenance, enabling faster delivery of new features and updates.
• Achieve improved response times for support requests, targeting 8 hours for critical issues, 12 hours for major issues, and 24 hours for minor issues.
• Implement a streamlined change request review process with detailed impact analysis, cost estimation, and risk assessment to ensure alignment with deployment schedules.
• Standardize code review and quality assurance procedures for all development outputs, including SQL and web asset code, to maintain high standards of quality and efficiency.
• Develop a centralized, regularly updated project documentation and knowledge base to facilitate onboarding, knowledge sharing, and transfer across teams.
• Adopt flexible project management methodologies (Scrum or Kanban) tailored to client needs for efficient handling of varying scope and request volumes.
• Implement a process of detailed requirements gathering, scope validation, and testing early in the change process to prevent ambiguities and scope creep.

• A dedicated Client Delivery Team (CDT) function for operational support and development, acting as an on-demand bridge between client needs and product team.
• A change request management system that allows detailed impact assessment, estimates, and approval workflows prior to implementation.
• A code review process emphasizing best practices, including SQL guidelines, quality standards, and internal review procedures.
• An internal bug tracking and prioritization system that facilitates quick reporting, validation, and resolution of product bugs.
• A comprehensive knowledge base with versioned documentation, tutorials, and recurrent training sessions for rapid knowledge transfer.
• Flexible project management framework adaptable between Scrum, Kanban, or hybrid approaches.
• Standardized escalation and communication protocols with single points of contact to ensure clarity and efficiency.

• Client systems for real-time change request submission and status updates
• Bug tracking and ticketing platforms for issue prioritization
• Version control systems for code review and deployment
• Data sources and ETL pipelines for process optimization

• Response times within 8 hours for critical/blocker requests, 12 hours for major, and 24 hours for minor operational support requests
• High availability architecture with 99.9% uptime to support 24/7 operations
• Scalable infrastructure capable of handling increasing client base and data volume
• Secure data handling complying with healthcare data privacy standards like HIPAA
• Continuous integration and delivery pipelines to ensure rapid deployment of updates and features

This initiative is expected to significantly reduce time-to-market for new healthcare analytics features by enabling 2-week development cycles, improve customer satisfaction through faster support response times, and enhance overall system stability and quality. The structured approach will allow scalable support for an expanding client base, ensuring consistent high-quality service and increased operational efficiency in healthcare data management and analytics.