What process examines the differences between predicted and actual revenue values to assess forecast accuracy?

Residual analysis is the correct process for examining the differences between predicted and actual revenue values to assess forecast accuracy. This method involves calculating the residuals, which are the differences between the observed values and the values predicted by a statistical model or forecasting method. By analyzing these residuals, decision-makers can determine how well the predictions align with the actual data and identify any patterns or biases that may need to be addressed.

This process is crucial in refining forecasting techniques, as it provides insights into the accuracy of predictions and can suggest adjustments for future forecasts. It helps in validating models and ensuring that they remain reliable over time, ultimately aiding in more informed financial planning and budgeting decisions.