Introduction
The sudden spike in negative feedback from clients about Andela's talent matching process is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product ecosystem, metric breakdown, and data analysis. From there, I'll form and validate hypotheses, conduct a root cause analysis, and propose a comprehensive resolution plan.
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 sudden spikes in feedback. Expected answer: Yes, we updated the algorithm two weeks ago. Impact on approach: If confirmed, I'd focus on the algorithm change as a primary hypothesis.
Why it matters: Helps identify if the issue is universal or segment-specific. Expected answer: The spike is more noticeable among enterprise clients. Impact on approach: I'd prioritize investigating enterprise-specific factors in the matching process.
Why it matters: Pinpoints the exact pain points in the matching process. Expected answer: Clients are reporting mismatches in technical skills and project requirements. Impact on approach: I'd focus on the skill assessment and project requirement gathering stages of the matching process.
Why it matters: Ensures the spike isn't due to changes in measurement methodology. Expected answer: No changes in feedback collection methods. Impact on approach: If confirmed, I'd rule out measurement issues and focus on actual process problems.
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