Research Article Published: August 24, 2025 Volume 1, Issue 6

Proactive Real-Time Monitoring of Workday Integrations Using Event-Driven Architecture for Global Supply Chains

Authors

Rajesh Nair*1

Affiliation: Department of Information Systems, Indian Institute of Technology Delhi, India

Anil Mehta1

Affiliation: Department of Information Systems, Indian Institute of Technology Delhi, India

Arjun Patel1

Affiliation: Department of Information Systems, Indian Institute of Technology Delhi, India

Abstract

The increasing complexity of global retail supply chains demands reliable enterprise resource planning (ERP) integrations to prevent disruptions in operations. Traditional Workday monitoring approaches rely on retrospective audits, limiting their ability to provide timely responses to failures. This study introduces an event-driven architecture (EDA) framework that integrates Java Message Service (JMS), RabbitMQ, and Workday's Core Connector and Enterprise Interface Builder (EIB) to enable real-time monitoring and predictive analytics.

By transforming passive event logs into actionable insights, the framework supports proactive detection and mitigation of integration failures. A case study with a multinational retailer demonstrated a 25% reduction in supply chain disruptions, 40% decrease in downtime, and 67% improvement in incident response times.

These results validate the scalability and effectiveness of EDA as a foundation for resilient ERP integration monitoring in large-scale enterprise environments.

Keywords

Predictive Monitoring Supply Chain Integration Enterprise Resource Planning (ERP) Real-time Event Processing Integration Monitoring Workflow Automation Enterprise Systems Message Queue Architecture System Integration Architecture Integration Failure Prevention

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How to Cite

APA Style:

Nair, R., Mehta, A., & Patel, A. (2025). Proactive Real-Time Monitoring of Workday Integrations Using Event-Driven Architecture for Global Supply Chains. International Journal of Advanced Research in Engineering and Related Sciences, 1(6), 25-32.

IEEE Style:

R. Nair, A. Mehta, and A. Patel, "Proactive Real-Time Monitoring of Workday Integrations Using Event-Driven Architecture for Global Supply Chains," International Journal of Advanced Research in Engineering and Related Sciences, vol. 1, no. 6, pp. 25-32, 2025.

References

  1. Workday Inc., Workday Studio: User Guide, Workday Community, 2020. [Online]. Available: https://community.workday.com
  2. Workday Inc., Integration Guide: Core Connector and EIB, Workday Community, 2019. [Online]. Available: https://community.workday.com
  3. J. Smith, "Data Transformation Strategies in ERP Systems," Journal of Enterprise Integration, vol. 12, no. 3, pp. 45–60, 2018.
  4. A. Brown and K. White, "Improving Latency in ERP Data Workflows," Proceedings of the International Conference on ERP Systems, 2019.
  5. M. Taylor, "Event-Driven Architectures in Modern IT Systems," IT Journal, vol. 45, pp. 120–130, 2017.
  6. D. Johnson, "Leveraging EDA for Real-Time Monitoring," Journal of Distributed Systems, vol. 30, pp. 75–90, 2018.
  7. Oracle Corporation, Java Message Service Specification 2.0, Oracle, 2017. [Online]. Available: https://docs.oracle.com
  8. RabbitMQ, RabbitMQ Documentation: Overview and Best Practices, RabbitMQ, 2020. [Online]. Available: https://www.rabbitmq.com
  9. Workday Inc., Prism Analytics Overview, Workday Community, 2020. [Online]. Available: https://community.workday.com
  10. P. Roberts, "The Role of Machine Learning in Predictive Analytics for ERP Systems," AI in Business Systems Review, vol. 18, no. 4, pp. 200–215, 2019.
  11. F. Garcia and L. Kumar, "Message Queuing Systems: A Comparison of JMS and RabbitMQ," International Journal of Computing Technologies, vol. 25, no. 2, pp. 89–98, 2018.
  12. C. Zhao, "Designing Scalable Dashboards for ERP Monitoring," Journal of Systems Engineering and Analytics, vol. 7, no. 3, pp. 134–145, 2019.
  13. Workday Inc., Security Best Practices for Integration System Users, Workday Community, 2019. [Online]. Available: https://community.workday.com
  14. J. Martin, "Comparative Analysis of Event-Driven Architectures and Batch Processing in ERP Systems," Journal of ERP Studies, vol. 10, no. 4, pp. 75–92, 2017.
  15. R. White, "Challenges and Opportunities in Real-Time Data Processing for Supply Chains," Global Logistics Journal, vol. 21, pp. 45–59, 2018.
  16. B. Patel and T. Gupta, "Machine Learning Techniques for Anomaly Detection in Integration Pipelines," Proceedings of the International Conference on Data Analytics and AI, 2019.