Diagnose why average waiting time increased

## Scenario You are a Data Scientist supporting DoorDash logistics. The business metric **average waiting time** has increased noticeably over the last 1–2 weeks. Assume: - Waiting time is defined as **dasher_wait_time_minutes = pickup_time - arrival_at_store_time** (time a dasher waits at the merchant). - You have event-level data for orders (timestamps for order placed, merchant confirmed, dasher assigned, dasher arrived, pickup, dropoff), plus merchant attributes, dasher attributes, and market-level supply/demand data. ## Task 1. **Debug/diagnose** why average waiting time increased. Provide a structured investigation plan. 2. Identify what additional data you would request (if any) and how you would validate data quality. 3. Propose **product/ops/model levers** to reduce waiting time. 4. Describe how you would **evaluate** proposed changes (metrics, experiment design, guardrails).