Introduction
The sudden 30% increase in average resolution time for Acronis Cyber Protect support tickets over the past two weeks is a critical issue that demands immediate attention. This analysis will systematically investigate potential root causes, validate hypotheses, and propose targeted solutions to address this performance decline.
To tackle this problem, I'll follow a structured approach:
- Clarify the situation with key questions
- Rule out external factors
- Analyze the product and user journey
- Break down the metric
- Gather and prioritize relevant data
- Form data-driven hypotheses
- Conduct root cause analysis
- Validate findings and outline next steps
- Present a decision framework
- Develop a comprehensive resolution plan
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes could directly impact support ticket resolution times. Expected answer: Yes, a major update was released three weeks ago. Impact on approach: If confirmed, I'd focus on investigating the update's features and potential bugs.
Why it matters: Changes in team structure could affect resolution efficiency. Expected answer: No major staffing changes have occurred. Impact on approach: If true, I'd shift focus to process or technical issues rather than human resource factors.
Why it matters: Technical glitches could artificially inflate resolution times. Expected answer: Some intermittent issues have been reported with the ticketing system. Impact on approach: If confirmed, I'd prioritize investigating and resolving these technical problems.
Why it matters: Changes in ticket complexity could naturally lead to longer resolution times. Expected answer: There's been an increase in tickets related to a specific feature. Impact on approach: If true, I'd focus on that feature and related documentation or training.
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