Our client, a leading IT managed services provider, supports multiple enterprise customers across different industries, each with unique SLA requirements. They faced increasing challenges in efficiently managing service requests, predicting SLA breaches, and scaling their operations while ensuring seamless customer experiences. Their existing ticketing system lacked automation, dynamic SLA adjustments, and predictive insights, leading to delayed responses and missed SLAs.
Challenges
Multi-Tenancy Complexity: Managing service requests for multiple clients within a shared environment required customized SLA handling, security controls, and data segregation.
Real-Time SLA Breach Prediction: The absence of proactive monitoring made it impossible to predict SLA breaches before they happened, leading to frequent escalations.
High Volume Case Management & Routing: With over 10,000 daily cases, manual assignment caused inefficiencies, often routing cases to the wrong support teams, increasing resolution times.
Data Silos & Limited Visibility: Customer data was spread across multiple systems (CRM, legacy ITSM tools), making it difficult for agents to access complete case histories and provide efficient support.
Solutions
Implementation of a Dynamic SLA Engine: We built a custom SLA Engine within ServiceNow that dynamically adjusted SLA thresholds based on customer tier, issue severity, and region. This engine leveraged ServiceNow Business Rules and Flow Designer to ensure SLAs adapted in real time, minimizing breaches.
AI-Powered SLA Breach Prediction: Using ServiceNow Predictive Intelligence, we trained AI models on historical case resolution times and key factors impacting SLA adherence. The system now proactively alerts support teams when an SLA is likely to be breached, allowing them to take corrective action before escalation.
Automated Case Routing with Kafka: We implemented an event-driven case management system by integrating ServiceNow CSM with Kafka. This allowed real-time streaming of cases to the correct teams based on workload balancing, agent expertise, and customer priority, significantly improving response times.
Unified Customer Data Hub: We developed a data integration layer using ServiceNow Integration Hub, synchronizing data from CRM, ITSM, and legacy systems into a single view. This enabled agents to access complete customer histories, reducing redundant questions and improving resolution efficiency.
Benefits
- Improved SLA compliance through predictive intelligence and proactive alerts.
- Faster ticket resolution times due to AI-driven case routing.
- Reduced manual workload with automated case assignment and workflow optimization.
- Enhanced customer satisfaction as agents had complete case visibility.
