Delivery Driver Performance Evaluation Framework
Overview
This question evaluates a product manager's competency in designing fair, data-driven performance frameworks, covering metric design, data collection strategy, and causal/statistical reasoning to isolate operator impact from external factors.
Amazon
Jul 4, 2025, 8:28 PM
Product Manager
Technical Screen
Product / Decision Making
12
0
Design a Fair Driver-Performance Framework
Context: Amazon currently tracks only two measures per driver: (1) number of packages delivered and (2) total delivery time. Design a robust, fair framework to evaluate delivery-driver performance that accounts for factors outside the driver’s control and yields actionable insights.
Tasks
- Identify additional data to collect (e.g., route characteristics, weather, traffic, package weight/volume, customer feedback, vehicle type, stop density, promised delivery windows).
- Explain why each data point matters and how you would gather it.
- Propose quantitative metrics or a scoring model that fairly compares drivers operating under different conditions.
- Outline how to surface insights to drivers and managers and how to iterate on the system over time.
Hints:
- Normalize for outside-control factors (distance, urban vs. rural, real-time weather/traffic, peak season).
- Include leading (process) and lagging (outcome) indicators: safety incidents, on-time rate, customer satisfaction, fuel efficiency.
- Use statistical/ML techniques (e.g., regression, clustering) to isolate driver impact from external noise.
Solution
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