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Product Management Root Cause Analysis Question: Investigating factors behind Delivery Hero's declining on-time grocery delivery rate in Berlin

Why has the on-time delivery rate for Delivery Hero's grocery orders fallen below 80% in the Berlin market this quarter?

Data Analysis Problem Solving Operational Strategy Food Delivery E-commerce Last-Mile Logistics
Data Analysis Root Cause Analysis Logistics Delivery Optimization Product Operations

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)

  • Looking at the timing, I'm thinking there might be a seasonal component. Has this decline coincided with any particular events or changes in Berlin's calendar?

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.

  • Considering user segments, I'm curious if this decline is uniform across all customer types. Are we seeing any differences in on-time delivery rates between, say, frequent users and occasional buyers?

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.

  • Thinking about recent changes, have we implemented any new features or processes in our delivery system in the past quarter?

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.

  • Regarding our delivery partners, has there been any significant change in our courier network or their working conditions recently?

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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