Introduction
The on-time delivery rate for Delivery Hero's grocery orders in Berlin has fallen below 80% this quarter, signaling a significant issue in our core service offering. This analysis will systematically identify, validate, and address the root cause of this performance decline, considering both immediate and long-term implications for our business.
I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into our product, user journey, and metrics. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan to resolve the issue and prevent future occurrences.
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: Seasonal factors could explain temporary fluctuations and inform our solution approach. Expected answer: No significant seasonal events correlate with the decline. Impact on approach: If seasonal, we'd focus on temporary adjustments; if not, we'd look at systemic issues.
Why it matters: Segmentation could reveal targeted issues affecting specific user groups. Expected answer: The decline is relatively uniform across user segments. Impact on approach: Uniform decline suggests a system-wide issue rather than user-specific problems.
Why it matters: Recent changes could be directly linked to the performance decline. Expected answer: A new route optimization algorithm was implemented last month. Impact on approach: This would shift our focus to technical issues and recent deployments.
Why it matters: Changes in our workforce could directly impact delivery performance. Expected answer: No major changes, but there's been an increase in courier turnover. Impact on approach: We'd need to investigate workforce management and retention strategies.
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