Estimate the annual market size for food delivery group ordering among office lunch coordinators under scale, incentive, and regulatory constraints

Problem Statement Description

Swiggy is evaluating the market opportunity for food delivery group ordering in office lunch settings, where an office admin, team assistant, HR representative, or informal lunch coordinator places recurring orders on behalf of multiple employees. Your task is to estimate the annual market size for this use case in India, focusing on repeat group lunch orders rather than all individual food delivery.

This is a guesstimate problem, so you should define the scope clearly, choose reasonable assumptions, and build a structured calculation from first principles. The estimate should account for urban office density, hybrid work patterns, coordinator-led ordering behavior, average group size, order frequency, average order value, platform adoption, and repeat usage.

You should also factor in real-world constraints that affect whether this market can scale: restaurant preparation capacity during lunch peaks, delivery batching reliability, incentives or discounts needed to drive repeat behavior, company reimbursement norms, privacy around employee food preferences and payments, and any regulatory or compliance considerations around corporate ordering, taxation, and food safety.

The estimate should consider:

- The geographic scope, such as India overall versus Swiggy-served Tier 1 and Tier 2 office markets.

- The relevant user base: offices, employees, and lunch coordinators who influence or place group orders.

- The unit of estimation, such as annual gross order value, annual revenue opportunity, number of orders, or addressable market.

- Adoption assumptions, including what share of offices use food delivery for group lunches and what share could use Swiggy.

- Frequency assumptions, including working days, hybrid attendance, special events, regular team lunches, and repeat ordering behavior.

- Average order size and value, including number of participants per group order and per-person lunch spend.

- Sensitivity drivers, such as incentive levels, delivery reliability, restaurant availability, corporate budgets, and regulatory or operational friction.

- Sanity checks against broader food delivery usage, office population size, and realistic lunch-hour delivery capacity.

Your goal is to produce a clear, defensible market-size estimate and explain which assumptions matter most. The interviewer is looking for structured reasoning, practical scoping, transparent assumptions, and the ability to identify where the estimate would change meaningfully under different operating or market conditions.