Executive Summary
A major BFSI client in the US streamlined its IT operations using Qinfinite’s AI-powered SaaS platform, which automated key processes, enhanced decision-making capabilities, and significantly reduced operational costs.
Introduction
Qinfinite, developed by Quinnox Inc., is designed to optimize IT operations with automation and real-time analytics, addressing challenges faced by enterprises such as high workload, inefficient problem management, and extended support requirements.
The scope of the 12 (4 Onsite: 8 Offshore) member support team was:
- L2/L3 Application Support
- Support Window: 16 x 5
- Number of Applications: 12
- Number of Processes: 27
Problem Statement
The client’s IT support team managed .NET and Mainframe applications but faced several challenges:
- Overloaded Team: The team was stretched with a 16% additional workload, affecting their performance and efficiency.
- Extended Support Requirements: There was a need to extend the support window from 16×5 to 24×7, which was not feasible with the existing setup.
- Inefficient Problem Management: Lack of detailed insights led to prolonged issues and ineffective problem resolution.
- High Turnaround Time: Longer turnaround times for business requests impacted overall operations.
Knowledge Retention Issues: High attrition rates led to significant knowledge loss within the team.
Solution Implementation
Discovery and Knowledge Graph
A dedicated Qinfinite instance was provisioned for the BFSI track, which performed comprehensive discovery across IT infrastructure, applications, and support groups, focusing on .NET and Mainframe applications. This discovery phase facilitated the creation of an enriched Knowledge Graph (KG), integrating business processes and stakeholder data to provide a holistic view of operations.
The Knowledge Graph enhanced IT operational intelligence by mapping complex relationships between IT assets, processes, and stakeholders. In the client’s deployment, the Knowledge Graph enabled a comprehensive visualization of the IT landscape, integrating application, infrastructure, and code domain insights. This integration allowed for a holistic view of how IT elements interacted and impacted business functions. By enriching this graph with business process data, user roles, and ownership information, the platform facilitated a deeper understanding of dependencies and potential vulnerabilities. This enriched context significantly aided in proactive problem management, impact analysis, and strategic decision-making, ensuring that IT operations were aligned with business priorities and capable of adapting swiftly to emerging challenges.
ITSM Analytics and Automation
The Qinfinite ITSM Analytics generated Cluster Analysis that reported repetitive incidents and service requests. Automation scripts were developed using Qinfinite’s Service Catalog, allowing for low-code/no-code setup and manual execution to ensure correctness. Intelligent Incident Management was configured to map specific intents to respective automations, leading to end-to-end automation of catalog request tasks.
Intelligent Incident Management (IIM) in Qinfinite leverages advanced AI algorithms to streamline the resolution of IT incidents and service requests. By automatically detecting the intent of incoming tickets and mapping them to predefined resolution procedures, IIM enhances operational efficiency and reduces human error. This automated system not only categorizes and routes incidents more accurately but also identifies and resolves recurring issues, leading to significant improvements in Mean Time to Resolution (MTTR) and overall IT service quality. Through continuous learning and adaptation, IIM optimizes response strategies over time, ensuring that IT support evolves in tandem with enterprise needs
BizOps
Routine start-of-the-day and end-of-the-day tasks were automated. Additionally, the Qinfinite BizOps module was used to implement real-time business process visualization, particularly tracking customer claims through various systems, which significantly aided in monitoring and optimizing the claims process.
Results and Benefits
- Operational Efficiency: Automation of 42% of ticket volume and routine tasks significantly reduced manual efforts and streamlined operations.
- Reduced MTTR: Mean Time to Resolution improved across ticket types, with incident tickets showing the most significant decrease.
- Enhanced Decision-Making: Real-time visualization through BizOps enabled proactive business decisions to optimize processes and meet SLAs.
- Scalability and Flexibility: The success of initial automations set a precedent for expanding automation across other ITSM tasks.
