Altering management practices and production designs to create a more sustainable global system has been highlighted in government policies and corporation objectives. In the dairy market, the inefficient utilization of feed and high production of emissions associated with raising and maintaining cattle are scrutinized for contributing to environmental degradation, and therefore, have become targeted areas for improvement. Feed is a major expense for the Canadian dairy industry, representing over 50% of all production costs. A new prospect for decreasing the environmental footprint of the dairy industry is to increase feed efficiency and decrease methane emissions through the selection of genetically superior animals, as these traits are favorably correlated. Current selection programs have been successful in achieving breeding objectives related to production, health and longevity. It is also important to develop a selection program that includes an aim to increase total system efficiency, thereby, maintaining a viable industry both economically and environmentally. Thus, the economic value of efficiency traits to be used in selection programs must be determined. The methodology introduced below was used to determine the total savings associated with selecting for a decrease in the total dry matter intake of a lactating first parity dairy cow; including the economic value of the reduction in feed-related methane production. The lifespan of a typical Canadian dairy animal was divided into stages based on significant changes in cost of ration or energy requirements by the animal. Regression coefficients defined as a ratio of the mean total feed intake across production animal life stages relative to a first parity lactating cow, were used to determine the economic effect of decreasing feed intake. The resulting coefficients were applied to determine the cost savings associated with the lower output of emissions. Using this approach, the approximate lifetime savings generated by a more feed efficient production animal can be estimated.