Introduction
The sudden drop in sequencing accuracy for Oxford Nanopore's PromethION 48 device last week is a critical issue that demands immediate attention. As we delve into this product execution problem, I'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term implications for our product strategy.
To tackle this challenge, I'll start by asking clarifying questions to gather essential context. Then, I'll rule out basic external factors before diving deep into product understanding, metric breakdown, and data analysis. This will lead us to form data-driven hypotheses, conduct a thorough root cause analysis, and ultimately develop 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 performance issues. Expected answer: Yes, a software update was rolled out two weeks ago. Impact on approach: If confirmed, we'd prioritize investigating the update's impact.
Why it matters: Sequencing accuracy can be sensitive to environmental variables. Expected answer: No significant changes reported in lab conditions or reagents. Impact on approach: If true, we'd focus more on device-specific issues rather than external factors.
Why it matters: Helps identify if the issue is universal or specific to certain conditions. Expected answer: The drop is more severe in long-read sequencing applications. Impact on approach: We'd investigate factors specific to long-read sequencing protocols.
Why it matters: Hardware issues could contribute to accuracy problems. Expected answer: No significant increase in maintenance events or replacements. Impact on approach: If confirmed, we'd shift focus from hardware to software or procedural issues.
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