Introduction
The sudden 30% increase in failed Interac Debit transactions at grocery stores last weekend is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and users.
I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product ecosystem. We'll break down the metric, gather relevant data, form hypotheses, and conduct a thorough root cause analysis. Finally, we'll develop a comprehensive plan to validate our findings and implement solutions.
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: System changes often correlate with performance issues. Expected answer: Yes, a minor update was pushed last Tuesday. Impact on approach: If confirmed, we'd focus on the update's components and rollout process.
Why it matters: Helps determine if this is a global issue or specific to grocery transactions. Expected answer: No, other merchant categories seem unaffected. Impact on approach: We'd investigate grocery-specific transaction characteristics or integrations.
Why it matters: Establishes the severity of the issue relative to normal operations. Expected answer: Usually around 2-3% failure rate. Impact on approach: A jump from 2-3% to 32-33% would indicate a severe problem requiring immediate action.
Why it matters: Ensures we're dealing with a real issue, not a reporting error. Expected answer: No changes to measurement or reporting systems. Impact on approach: If there were changes, we'd need to audit our data collection and reporting processes first.
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