JUA Pulse System Modernization Project

• Feyisayo Muraina-Taiwo led a project to modernize the JUA Pulse system during an internship at Brown & Brown Insurance.
• The JUA Pulse system is central to benefit calculation and claim adjudication.
• The project aimed to address inefficiencies in the outdated JUA Pulse system that impacted benefit processing speed and accuracy.
• Feyisayo's role included data analysis, stakeholder engagement, and providing insights for the IT team's decision-making.

Project Background

• The JUA Pulse system faced several operational challenges including manual processing inefficiencies.
• Agents spent up to one hour per statement due to manual creation of commission statements.
• There were inconsistencies in benefit calculations which led to errors in claims and commission payouts.
• The system lacked integration with other internal platforms, forcing agents to manually transfer data and heightened the risk of data entry errors.

Project Goals

• Goals included identifying and documenting inefficiencies in benefit calculation and commission statement processes.
• Goals included engaging with stakeholders to gather functional requirements and aligning business needs with technical capabilities.
• Provide the IT team with a clear, data-backed recommendation on whether to integrate the system or develop a standalone solution.

Planning and Initiation

• The project’s scope was focused on the benefit calculation and commission statement processes.
• Key milestones included completing stakeholder interviews and process mapping by the end of Month 1.
• Another milestone was conducting data analysis and identifying key inefficiencies by the middle of Month 2.
• A final milestone was delivering a finalized report with recommendations by the end of Month 3.
• Interviews were conducted with agents, benefit managers, and IT staff to understand workflows and pain points.
• Historical data from the JUA Pulse system was analyzed to quantify time spent on manual processes and frequency of calculation errors.
• Agents manually pulled data from multiple systems and adjusted errors post-processing.

Execution and Monitoring

• Agents spent an average of 45–60 minutes manually compiling commission statements.
• Approximately 12% of statements had discrepancies due to manual data entry issues.
• The lack of integration with other platforms increased processing time and error rates.
• A detailed process map was developed to visualize the end-to-end workflow, highlighting bottlenecks and redundant steps.
• Weekly meetings were held with the IT team to evaluate integration vs. standalone solution.
• Performance benchmarks were established to track progress and identify any emerging issues.

Achievements and Impact

• Documentation and analysis provided a clear understanding of the system's weaknesses and potential improvements.
• The IT team determined that platform integration would be the most cost-effective solution for long-term efficiency gains.
• The proposed changes were projected to reduce statement processing time from 60 minutes to 15 minutes through automation.
• Calculation errors were expected to decrease by at least 25% through better data handling and integration.
• Agent satisfaction was expected to improve by reducing workload and increasing payment accuracy.

Lessons Learned

• Balancing business requirements with the IT team’s technical capabilities was a significant challenge.
• Initial disagreements on integration vs. standalone development were resolved through consistent communication and data-backed insights.
• Process mapping and data analysis are powerful tools for uncovering inefficiencies and building stakeholder consensus.
• Open and transparent communication ensured stakeholder alignment and confidence.

Project Conclusion

• The JUA Pulse Modernization project improved operational efficiency by uncovering key system inefficiencies and providing a clear path toward integration.
• The project streamlined benefit calculation and claim adjudication and also enhanced agent satisfaction and reduced calculation errors.
• Feyisayo strengthened skills in data analysis, process optimization, and stakeholder engagement through this experience.