Introduction
The sudden 30% increase in transit times for Flock Freight's FlockDirect shipments last week 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 business.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into our product ecosystem, metrics, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan for validation and resolution.
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 shifts. Expected answer: Yes, there was a routing algorithm update. Impact on approach: If confirmed, we'd focus on the algorithm change as a primary suspect.
Why it matters: Ensures we're solving a real problem, not a data anomaly. Expected answer: Yes, measurement systems have been verified. Impact on approach: If not verified, we'd prioritize data validation before further analysis.
Why it matters: Helps isolate whether this is a FlockDirect-specific issue or a broader problem. Expected answer: No, other services are unaffected. Impact on approach: If confirmed, we'd focus exclusively on FlockDirect's unique features and processes.
Why it matters: Changes in demand or shipment characteristics could impact transit times. Expected answer: No significant changes noted. Impact on approach: If changes are identified, we'd investigate how these shifts might be affecting our system's performance.
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