This paper examines the convergence of methods used to measure business economic performance (BEP). Researchers have traditionally used either perceptual assessments of senior executives or secondary data sources, but few have evaluated the degree of convergence across methods. The authors collected data on three dimensions of BEP—sales growth, net income growth, and profitability (ROI)—using both methods. They used the Campbell and Fiske's MultiTrait, MultiMethod (MTMM) framework and the Confirmatory Factor Analysis (CFA) approach to assess convergent and discriminant validity. While both methods yielded insights, CFA was found to be more advantageous for strategy research. Business performance is fundamental to management practice and research. Researchers have conceptualized and measured performance using various schemes, depending on their research questions, disciplinary focus, and data availability. Strategic management is particularly focused on organizational performance, but there has been limited attention to its measurement. Organizational researchers generally focus on organizational effectiveness, while strategy researchers focus on a narrower domain called BEP. The authors developed a two-dimensional four-cell classificatory scheme for the measurement of BEP based on data sources (primary or secondary) and mode of performance assessment (objective or perceptual). They collected perceptual data from senior managers and objective secondary data from external sources. The study used "between-methods" triangulation to ensure that the variance reflected was that of trait and not of method. The authors found that the requirements of convergent and discriminant validities were broadly satisfied, but the various criteria were open to researchers' interpretation. They also found that the CFA approach provided a more detailed analysis of measurement variance, decomposing it into trait, method, and error components. The results indicated that the primary method was more reliable for sales growth, while the secondary method was more reliable for profitability. Both methods were found to be poor measures for operationalizing net income growth. The study highlights the importance of considering both perceptual and objective data in measuring BEP. It also suggests that no single method is universally superior, and that researchers should consider the context and purpose of their study when choosing a measurement method. The use of CFA provides a more comprehensive analysis of measurement variance and is recommended for strategy research. The study also emphasizes the need for further research on the measurement of BEP, particularly in relation to the reliability and validity of different methods.This paper examines the convergence of methods used to measure business economic performance (BEP). Researchers have traditionally used either perceptual assessments of senior executives or secondary data sources, but few have evaluated the degree of convergence across methods. The authors collected data on three dimensions of BEP—sales growth, net income growth, and profitability (ROI)—using both methods. They used the Campbell and Fiske's MultiTrait, MultiMethod (MTMM) framework and the Confirmatory Factor Analysis (CFA) approach to assess convergent and discriminant validity. While both methods yielded insights, CFA was found to be more advantageous for strategy research. Business performance is fundamental to management practice and research. Researchers have conceptualized and measured performance using various schemes, depending on their research questions, disciplinary focus, and data availability. Strategic management is particularly focused on organizational performance, but there has been limited attention to its measurement. Organizational researchers generally focus on organizational effectiveness, while strategy researchers focus on a narrower domain called BEP. The authors developed a two-dimensional four-cell classificatory scheme for the measurement of BEP based on data sources (primary or secondary) and mode of performance assessment (objective or perceptual). They collected perceptual data from senior managers and objective secondary data from external sources. The study used "between-methods" triangulation to ensure that the variance reflected was that of trait and not of method. The authors found that the requirements of convergent and discriminant validities were broadly satisfied, but the various criteria were open to researchers' interpretation. They also found that the CFA approach provided a more detailed analysis of measurement variance, decomposing it into trait, method, and error components. The results indicated that the primary method was more reliable for sales growth, while the secondary method was more reliable for profitability. Both methods were found to be poor measures for operationalizing net income growth. The study highlights the importance of considering both perceptual and objective data in measuring BEP. It also suggests that no single method is universally superior, and that researchers should consider the context and purpose of their study when choosing a measurement method. The use of CFA provides a more comprehensive analysis of measurement variance and is recommended for strategy research. The study also emphasizes the need for further research on the measurement of BEP, particularly in relation to the reliability and validity of different methods.