Introduction
The recent 15% drop in Aya Healthcare's travel nurse placement rate over the past quarter is a concerning trend that requires immediate attention. As we delve into this issue, we'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term and long-term implications for the business.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Changes in the placement process could directly impact the placement rate. Expected answer: Yes, we introduced a new matching algorithm. Impact on approach: If confirmed, we'd focus on analyzing the algorithm's performance and potential issues.
Why it matters: External demand changes could explain the drop in placement rate. Expected answer: Demand has remained relatively stable. Impact on approach: If demand is stable, we'd shift focus to internal factors or supply-side issues.
Why it matters: Changes in the available nurse pool could affect placement rates. Expected answer: The nurse pool has grown slightly. Impact on approach: If the pool has grown, we'd investigate why this isn't translating to more placements.
Why it matters: Competitive actions could be drawing nurses or healthcare facilities away from Aya. Expected answer: No significant changes in competitor offerings. Impact on approach: If competition isn't a factor, we'd focus more on internal processes and user experience.
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