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).