National estimated breeding values of bulls from 1998 through 2006 from 12 different German artificial insemination (AI) organizations were used to determine the differences in expected and realized selection intensities for cow sire selection, considering the total merit index as well as subindexes for production, conformation, somatic cell count, fertility, and functional herd life. The expected selection intensity was derived from a Gaussian distribution and from the replacement rate describing the percentage of bulls graduated as cow sires from the total amount of progeny-tested young bulls within the AI organization and by birth year. Realized selection intensities for all indexes were derived from the selection differential of cow sires, defined as the deviation of the average index of selected cow sires from the average index of the total number of progeny-tested young bulls. A low replacement rate of cow sires was associated with relatively high realized selection intensities for the total merit, production, and conformation indexes, but was not related to the somatic cell count, fertility, and functional herd life indexes. The controlling value, defined as the ratio of realized to expected selection intensities, indicates the effectiveness of cow sire selection for different traits. Low controlling values (i.e., low realized selection intensities in combination with moderate or high expected selection intensities) suggest improvements in the step of cow sire selection, especially when discussing the total merit index. Analysis of variance revealed significant differences in expected selection intensities, realized selection intensities, and controlling values for the total merit, production, and conformation indexes between AI organizations and birth years of bulls. Artificial insemination organizations applying well-defined breeding policies (e.g., high controlling values for the total merit index) were successful in the national competition when evaluated according to the national top lists for the respective indexes, regardless of the active population size. The suggested method also allows for comparison of the importance of different indexes in selection decisions. Furthermore, controlling values can monitor additional potential in the improvement of cow sire selection with respect to improvement of the genetic level in the whole population. The development of appropriate selection tools or controlling instruments is of increasing concern for monitoring selection policies in the short term as well as for establishing sustainable breeding policies.