Decision and Validation Frameworks Questions

Covers structured approaches for making launch or recommendation decisions by combining experimental data validation with holistic go no go assessment. Candidates should be able to specify what data and metrics are needed to validate a hypothesis, design controlled experiments or pilots including sample sizing, duration, monitoring, success thresholds, and rollback plans, and describe how to manage measurement risk and biases. Candidates should also apply a three pillar decision framework that examines desirability including user need and market demand, feasibility including technical capability timeline and resource requirements, and viability including business model and financial sustainability. Interviewers look for clear success criteria and decision thresholds, trade off analysis, risk mitigation and contingency planning, stakeholder alignment and communication, and the ability to integrate quantitative results with qualitative inputs to make a defensible go no go recommendation.