Introduction
Honor's caregiver matching algorithm has experienced a 15% decrease in successful placements over the past month, indicating a significant issue in the core functionality of the platform. This analysis will systematically investigate potential root causes, generate data-driven hypotheses, and propose a strategic plan to address the problem.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Seasonal trends could explain the fluctuation and impact our solution approach. Expected answer: No significant seasonal variation observed in previous years. Impact on approach: If seasonal, we'd focus on adapting to cyclical demands rather than fixing a sudden issue.
Why it matters: Identifying affected segments could point to specific issues in the matching criteria. Expected answer: The decrease is more pronounced in urban areas and for specialized care needs. Impact on approach: We'd prioritize investigating urban-specific factors and specialized care matching algorithms.
Why it matters: Recent changes could directly correlate with the performance drop. Expected answer: A minor update was pushed to improve matching speed two weeks ago. Impact on approach: We'd focus on analyzing the impact of this update and potentially rolling it back.
Why it matters: Ensures we're comparing apples to apples and not facing a data anomaly. Expected answer: No changes in measurement or reporting methods. Impact on approach: Confirms the issue is with placements, not data reporting, focusing our efforts on the matching process.
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