Introduction
The sudden 30% increase in support ticket volume for DXC Technology's Application Services in the last month is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and organization.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product ecosystem, user journey, and relevant metrics. From there, I'll generate data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.
Framework overview
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 often correlate with support ticket spikes. Expected answer: Yes, a major feature update was released. Impact on approach: If yes, I'd focus on the new feature's implementation and user education.
Why it matters: Helps identify if the issue is universal or segment-specific. Expected answer: The increase is primarily in enterprise customers. Impact on approach: If segment-specific, I'd tailor the investigation to that user group's needs and behaviors.
Why it matters: Support team changes can impact ticket volume and resolution times. Expected answer: No significant changes to the support team. Impact on approach: If no changes, I'd focus more on product and user-side issues.
Why it matters: Technical issues often lead to increased support tickets. Expected answer: Some intermittent performance issues have been noted. Impact on approach: If yes, I'd prioritize technical root cause analysis.
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