Ticket Analysis
How might we enable HR teams to handle tickets more effectively by automating repetitive tasks and providing accurate, AI-driven knowledge through a scalable and seamless experience?
My Role
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Timeline
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Impact
Lead Product Designer
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15 months
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With the help of Ticket Analysis, we observed a 70% reduction in ticket volume, 40% increase in employee self service and 30% reduction in ticket resolution time.
The Overview
​Conversations with our customers revealed a significant gap in the HR ticket resolution process: agents were overwhelmed with repetitive, time-consuming tickets, leading to SLA escalations. To address this, we leveraged Generative AI to bridge the gap by automating knowledge generation. This shift aimed to reduce the workload on agents, enhance efficiency, and improve the overall employee experience.
Business Need
HR agents were dealing with an overwhelming volume of employee queries, leading to SLA escalations and burnout. The manual process of sifting through tickets to craft solutions was inefficient and exhausting. We needed to introduce an intelligent solution that would not only reduce the load on HR agents but also enhance the overall employee experience by promoting self-service.
Goal
Our goal was to create an AI-powered dashboard that would help agents quickly analyze ticket clusters and generate knowledge articles in seconds, reducing repetitive tasks while maintaining high-quality solutions. We aimed to encourage employees to rely on a comprehensive knowledge base for self-service and drive high adoption of the Ticket Analysis feature as a key value driver in our product suite.
Challenges
We encountered challenges with version control and edge cases, requiring mid-project adjustments to user flows. Aligning design with development was difficult, as the focus often shifted to functionality over user experience, necessitating ongoing collaboration.
Impact
70% Reduction in Ticket Volume
40% Increase in Employee Self-Service
30% Reduction in Ticket Resolution Time