Case: 10% Delivery Drop in Los Angeles

Scenario

A food-delivery marketplace reports a 10% decline in completed deliveries in Los Angeles over a recent comparable period.

Assume “deliveries” means completed orders (after cancellations/refunds) and the decline is measured relative to a stable baseline (e.g., week-over-week or year-over-year for the same week). Clarify exact time window before analysis.

Tasks

1. Identify and quantify the key drivers of the 10% decline.
2. List the data you would examine (demand, supply, product, external, and operational).
3. Propose concrete hypotheses for potential causes.
4. For each hypothesis, outline how you would validate it, including metrics and methods.
5. If controlled experiments are not possible, describe alternative causal inference approaches (e.g., synthetic control, DiD, time-series causal methods).

Hints

• Use funnel analysis, supply vs. demand decomposition, seasonality and event checks, competitor impact.
• Consider synthetic-control, difference-in-differences, and time-series causal methods for causal inference without experiments.