Introduction
Insurance providers operate in highly customer-centric environments where service speed, accessibility, and reliability directly impact customer trust. High volumes of support tickets, SLA violations, and manual intervention often lead to delays and poor customer experience. This case study highlights how an insurance provider transformed its support operations through self-service enablement, automation, and workload optimization. By restructuring IT support processes and introducing intelligent automation, the organization improved service efficiency, reduced operational effort, and enhanced customer trust.
Customer
An insurance provider managing high-volume application support operations across multiple channels, including web, voice, email, and automated alerts.
Business Objective
- Improve customer trust through faster and seamless support
- Reduce SLA violations in response and resolution
- Optimize support workload across L1, L2, and L3 teams
- Enable self-service and automation-led support
- Reduce dependency on manual intervention
Scope of Services
- Ticket data analysis across time, volume, and channels
- Incident vs service request classification and optimization
- SLA compliance analysis (response and resolution)
- Skill-based workload and demand analysis
- Identification of automation and self-service opportunities
- Implementation of BOT, RPA, and auto-healing use cases
- Enablement of self-help and self-service platforms
Key Insights from Analysis
- 3,100 total tickets analyzed
- ~96% tickets converted to incidents (2,988) → poor classification
- SLA violations:
- 527 response breaches
- 589 resolution breaches
- Majority tickets originated from web (2,289)
- High dependency on manual support across channels
Workload & Skill Observations
- Operations contributed 45% of total ticket volume
- Finance & Supply Chain accounted for 44%
- Top skills in demand:
- Oracle EBS (44.9%)
- .Net/C# (20.7%)
- Oracle 4GL (19.7%)
- Strong opportunity for L3 → L2 → L1 shift-left model
Detailed Findings
- Poor ticket classification between incidents and service requests
- High volume of P3 tickets (78%) indicating inefficiency in prioritization
- SLA response violations higher than resolution → process gaps
- Lack of structured service catalogue and self-service adoption
- Repetitive issues (data updates, training, access issues) suitable for automation
Benefits
- Reduced manual ticket handling through self-service
- Improved SLA compliance and response efficiency
- Better workload distribution across support levels
- Enhanced visibility into support operations and performance
- Improved customer experience and trust
Impact
- 48.11% of tickets identified for automation/self-service impact
- 37% overall effort optimization achieved
- Significant reduction in repetitive support workload
- Improved SLA adherence and faster response times
- Enhanced customer satisfaction through seamless support experience
