Estimation and Assumptions Analysis Questions

Frameworks and techniques for producing rapid, defensible estimates and for surfacing and testing the assumptions that underlie them. Candidates should clarify the objective and units, decompose the problem into measurable components, choose top down or bottom up approaches, select reasonable proxies and external data sources, and perform back of the envelope calculations with clear arithmetic and units. Candidates should state assumptions and bounds explicitly, run sensitivity analysis to show how results change with different inputs, present confidence levels and caveats, and describe what data would be required to refine estimates. Interviewers evaluate structured thinking, numerical literacy, ability to justify assumptions, and communication of uncertainty when estimates inform prioritization, sizing, or business cases.