Product design question
In a home delivery type of business, design specific technology/software features that would improve the overall accuracy of the delivery time estimates.
- Uber
- Product design
- Medium
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What this question tests
Tests product design for operational efficiency in a logistics-heavy business, requiring the candidate to target a specific, high-friction step in the delivery journey.
How to approach it
- Clarify scope: last-mile delivery execution, or the broader order-to-delivery pipeline including warehouse picking, since the design differs.
- Segment the journey into distinct steps: order intake, warehouse fulfillment, dispatch and routing, and last-mile handoff to the customer.
- Identify the highest-friction step using delivery data: failed or delayed handoffs at the customer's door (wrong address, no one home) are a common, costly failure point.
- Design a specific feature: real-time delivery tracking with a narrow, dynamically updated arrival window and proactive two-way messaging so customers can adjust in real time (reroute, leave instructions) before a failed delivery attempt.
- Add a secondary feature: route optimization software for drivers that accounts for real-time traffic and delivery density, reducing per-stop time.
- Define success as reduced failed-delivery rate and reduced average delivery cost per order, not just faster average delivery time alone.
What a strong answer includes
- Targets the last-mile handoff specifically, correctly identifying it as the highest-cost, highest-friction point in most delivery businesses.
- Proposes a concrete, specific feature, proactive two-way messaging with a dynamic arrival window, rather than a vague better tracking answer.
- Uses illustrative numbers as assumptions: assume failed delivery attempts cost significantly more to redeliver than a first successful attempt, justifying investment in reducing them.
- Chooses a cost-oriented success metric, not just speed, recognizing that faster delivery without reducing failure cost doesn't necessarily improve the business.
Common mistakes
- Proposing generic tracking features without identifying the actual highest-friction step in the journey.
- Ignoring failed delivery attempts as a major, quantifiable cost driver.
- Measuring success purely by speed instead of cost and reliability.
Likely follow-up questions
- How would you handle a customer who repeatedly isn't available for delivery?
- What's the trade-off between narrower delivery windows and driver route efficiency?
- How would you measure the ROI of this feature?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop