Introduction
The doubling of average turnaround time for Turnitin's Originality Check on high school submissions 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 degradation.
To tackle this problem, I'll employ a structured approach that encompasses issue identification, hypothesis generation, data analysis, and solution development. My goal is to not only resolve the immediate concern but also to implement preventative measures for long-term system stability and user satisfaction.
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 processing times. Expected answer: Yes, there was a minor update to the algorithm two weeks ago. Impact on approach: If confirmed, we'd prioritize investigating the update's effects.
Why it matters: A sudden increase in volume could strain system resources. Expected answer: Submission rates have remained relatively stable. Impact on approach: If stable, we'd focus more on internal system issues rather than external factors.
Why it matters: Changes in measurement could create false alarms. Expected answer: No changes to the metric definition or measurement. Impact on approach: If unchanged, we'd rule out data integrity issues and focus on actual performance problems.
Why it matters: Seasonal patterns could explain temporary performance issues. Expected answer: It's not a typical high-volume period for high schools. Impact on approach: If confirmed, we'd need to look deeper into system-specific issues rather than external factors.
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