Optimizing IT Ticket Management: Process Reengineering, Automation, Knowledge‑Base Pre‑position and Intelligent Q&A Integration

Background – The IT operations team faced a high volume of daily tickets, often exceeding 150 per week, which strained resources and reduced efficiency.

Problem Classification Governance – Issues were grouped by impact (financial settlement, system stability, product scenario, user experience, etc.) and prioritized, allowing targeted remediation of high‑priority categories.

New Solution Practice – Process reengineering introduced automated testing, cross‑department collaboration, and refined handling procedures, which initially lowered ticket counts but revealed that consulting and operational queries still dominated.

Knowledge‑Base Pre‑position – A knowledge‑base was integrated into the web system via IDs and tracking points; an interceptor parsed URIs or error codes, fetched relevant knowledge entries, and displayed guidance directly on the UI, reducing the need for manual assistance.

Intelligent Q&A Integration – An AI‑driven chatbot (慧言机器人) was trialed to answer frequent consulting questions. Data were stored in Elasticsearch, processed with NLP (IK tokenizer, stop‑word filtering), and matched using TF‑IDF and cosine similarity, with personalized responses based on business context.

Future Outlook – Ongoing experiments include deeper AI integration (e.g., ChatGPT) and continuous knowledge‑base enrichment, aiming to further cut ticket volume and improve user self‑service.