As many manufacturing firms engage in time-based competition today, the efficient measurement and management of cycle time has become a critical factor determining a firm's core competitiveness. However, due to the absence of efficient methods for measuring and analyzing cycle time, it has not been widely utilized as a performance evaluation metric. Furthermore, systematic research on the factors causing cycle time variation has been insufficient, making it meaningless to compare cycle times and evaluate improvement without accounting for these factors. Therefore, this study aimed to develop a cycle time measurement model that can support corporate performance analysis, competitive benchmarking, and managerial decision-making, and to identify non-operational factors that cause variation in cycle time measured using financial statements, thereby establishing methods for efficiently managing and improving cycle time. Panel data analysis was conducted using financial data from domestic manufacturing firms over the 1981–2002 period, yielding the following results. First, a measurement method using financial data was proposed so that cycle time can be effectively utilized as a performance evaluation metric for manufacturing firms. Second, gross profit margin, capital intensity, and input-output variability were identified as non-operational causes of ambiguous variation in measured cycle time, demonstrating that the cycle time concept based on financial data has inherent limitations in measuring and analyzing time performance by itself. Third, an adjusted cycle time measurement model was proposed that controls for differences caused by factors that induce cycle time variation, enabling cycle time to be used for firm-level or year-over-year performance analysis.