Complete lack of data, poor quality data, or a major time lag until data becomes available are all reasons for poor business decision-making ultimately resulting in reduced profitability. At a dairy farm good decision making is highly dependent on the availability of high quality and current data about different parameters of the production unit, i.e., the cow. Unfortunately, despite the availability of many technologies and data on dairy farms today, dairy producers continue to lack tools that provide an accurate and detailed account of individual cow profitability with minimal effort and in real time. Thus, most of the individual cow decision-making continues to be done based on averages for the herd or groups, parameters that do not truly reflect cow profitability, and in some cases perception or "gut feeling". To overcome this barrier to good business decision- making, I propose using daily values for cow inputs and outputs to estimate dry matter intake and feed cost which is a leading expense for dairy farms and thus, an important value to estimate overall cow profitability. In this study, I used data from existing precision technologies for commercial dairy farms that monitor parameters of performance and cow features required by equations to calculate feed intake by cattle. Substantial differences for estimations of dry matter intake and feed cost for lactating dairy cows were observed when representing scenarios when data from precision technologies were or were not available.