This study examines when analysts or managers issue more accurate earnings forecasts by decomposing firm profitability into market-, industry-, and firm-specific components and analyzing how these information sources interact with firm operational structure. Using annual management guidance and analyst forecasts for U.S. firms from 2001 to 2024, we compare relative forecast accuracy based on both the magnitude of forecast errors and the likelihood that one party outperforms the other. Applying an earnings disaggregation framework that allows firm-specific sensitivity to market and industry conditions, we find that analysts are more likely to outperform management when a greater proportion of earnings is attributable to industry-level factors, providing evidence of an industry-level information advantage that contrasts with prior findings of no such effect. This advantage, however, is not uniform across firms. Industry-level information improves analyst accuracy primarily for single-segment firms and for multi-segment firms with relatively concentrated operations, while greater diversification shifts the advantage toward management, particularly when earnings are driven by firm-specific factors. Additional analyses based on vertical integration and firm life cycle show that analysts’ advantages are most pronounced in mature firms, where earnings processes are more stable and information signals can be mapped more cleanly into future performance. Overall, the findings highlight how firm structure shapes the analyst–management forecasting competition.