The beef cattle industry is based on valuation of phenotypes, and its supply chain components vary across global region. In many areas, producers maintain ownership of animals until sale to an abattoir, yet in many other regions distinct industry segments (cow-calf, grower/stocker, finisher/feedlot, packer) exist where animal ownership changes across segment. Commodity cattle (of unknown genetic and/or management background) have different value potential as compared with cattle with known background. The utility of genomic data and analyses are, and will remain, different regarding these 2 types of cattle. Many genomic approaches have calculated molecular breeding values of animals; however, most beef industry managers other than seedstock producers would much rather have predicted phenotypes (predictions that could be collectively based on breeding value, non-additive genetic value, and environmental value) for improved management and marketing decisions. Current US beef industry trends show increasing carcass (and mature cow) weight and carcass quality grade, but static incidence of respiratory disease in feedlots, and no improvement in percent calf crop weaned in beef herds. Trends for more prevalent and less costly genomic data will also continue. There appears to be large potential to genomically characterize beef cattle for production-related physiological systems (health, growth, body composition, fertility, nutrient utilization) as well as potential interactions for optimal economic management and production system assessment. Better understanding of these systems and their components will require knowledge beyond the DNA sequence including RNA regulatory elements and products and protein function and structure; the roles of fetal programming and epigenetics on economically important traits in beef production remain largely unknown and need investigation. Resource cattle populations with detailed phenotypes and banked biological samples, and that evaluate multiple components of beef cattle production systems remain critically important; partnerships of industry groups and research institutions can assemble large, informative data sets. The incorporation of genomic data into economic assessments is also encouraged.