Introduction
Egencia's flight search response time increase from 2 to 5 seconds during peak business hours is a critical issue that demands immediate attention. This performance degradation directly impacts user experience and could lead to decreased conversions and customer satisfaction. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Helps determine if it's a capacity issue or something more specific. Expected answer: Consistent across peak hours. Impact on approach: If consistent, focus on scalability; if varied, investigate specific time patterns.
Why it matters: Recent changes are often the culprit in sudden performance shifts. Expected answer: A recent update to the search algorithm. Impact on approach: If yes, focus on rollback or optimization; if no, look at external factors or gradual degradation.
Why it matters: Helps narrow down if it's a general issue or specific to certain use cases. Expected answer: More pronounced for complex business travel searches. Impact on approach: If segmented, focus on optimizing specific user flows; if universal, look at core infrastructure.
Why it matters: External dependencies can significantly impact performance. Expected answer: No recent changes in providers, but increased data volume. Impact on approach: If changed, investigate integration points; if not, look at data processing efficiency.
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