The objective of this study was to examine the relationship between intensity of short-range and medium-range capacity management and effectiveness of manufacturing operations. Data were collected to test the null hypothesis which stated that intensity of short-range and medium-range capacity management does not influence manufacturing effectiveness. Intensity of short-range and medium-range capacity management was indicated by the following variables: (1) production standards; (2) priority determination; (3) delivery dates determination; (4) material requirements planning; (5) routing information; (6) capacity utilization; and (7) backlog measurement. Manufacturing effectiveness was indicated by the following variables: (1) delivery dates performance; (2) lead times; (3) subcontract work; (4) direct labor overtime; (5) direct labor efficiency; (6) plant and equipment utilization; and (7) work in process inventory. The population selected to provide data for this study is the manufacturing firms in the State of Texas with five hundred or more employees. Over 42 percent of the eligible firms responded to a six-page questionnaire. Several multivariate techniques were utilized for data analysis: (1) factor analysis; (2) canonical correlation analysis; (3) bivariate correlation; (4) multiple linear regression; (5) cross-tabulation; and (6) analysis of variance. The results of this research did not adequately support the rejection of the null hypothesis. However, they did definitely identify a distinct group of capacity management intensity variables that influence manufacturing effectiveness in specific cases. Intensity variables were placed in three groups that identified how influential they were over the effectiveness measures. The most influential group included the variables: production standards and material requirements planning. The indication for the manufacturing manager is to concentrate on improvements in these areas. Effectiveness variables were also placed in three groups that identified the level at which the variables were influenced by the intensity variables. The highly influenced group included plant and equipment utilization and delivery dates performance.