A global manufacturing company

Problem Statement

Analyze and enhance performance of the IT Ticket Operations’ support center by:

• Determining reasons for volatility in Key Performance Indicators (KPIs)
• Tracking of IT Server’s Ticket and Trigger notification data
• Predicting drop in performance to take preventive action for ticket/trigger details
• Acquiring ability to notify alarming trends of factors affecting KPIs to operation leads

Analytics Led Approach

• Identified variation in KPI by defining control limits obtained after treating outliers in data
• Used Linear Regression models to predict KPI values using significant factors and services impacted affecting KPI performance
• Created warning limits for significant factors using regression equation
• Developed excel dashboard to monitor daily KPI performance with warning signals for breaches

Business Impact

• Reduction in effort spend on KPI performance monitoring and analytics by 40%
• Developed models for KPI prediction with accuracy of around 87%
• Consolidated view of KPI data with relevant factors in excel dashboard
• Inputs to operations team for KPI performance improvement

Critical Success Factors

• KPI prediction with high accuracy of 87%
• Critical inputs to Operations Team for KPI performance improvement
• Data flow and Incidence chart for typical IT Operations’ support center processes across the board for the client