Revenue Forecasting System Design Questions

Designing end to end forecasting infrastructure that produces reliable revenue estimates and integrates into planning workflows. Candidates should be able to discuss multiple forecasting approaches including statistical time series methods, causal models, and machine learning based models; design data ingestion and feature pipelines from sales, billing, and operations systems; and choose between batch and real time update strategies. Coverage should include scenario and what if analysis, evaluation metrics for forecast accuracy and calibration, model versioning and retraining cadence, monitoring for drift and anomaly detection, and human in the loop adjustments and overrides. Also expect discussion of integration points with planning and finance systems, reconciliation and governance processes, trade offs for latency and cost, and stakeholder facing outputs that include confidence intervals and explainability.