Taking decisions is hard no doubt. That said understanding how will be the sales the companies executives agree to take better a quickly decision everyday would not be nearly as hard if executives today would just consider some kind of forecast to understand how the sales will be. A practical diagnose of the situation in all department is certainly important, but that not mean just a forecast. It not mean that at all. To get visibility of the company today’s executive must data science to get the information. Just creating a meeting to talk about the situation for areas to take along the time that the executive doesn´t have. The same situational areas taking companies executives time in the ’80s born the S&OP. When S&OP born companies take executive data science process and integrate metrics and classification in a better way. That data science, that core heart data science. That data science not science. Data science tool of science, no more. Analyze data for companies executives data analysis. All scientists data scientists since all take data to analyze. They take data to make decisions. The also hypothesize and experiment. For example take understand how the sales will be. Data scientists not scientists because data scientists take information to get how sales will be. But they not hypothesize why sales be the way they be. They not design experiment to test why sales be the way they be or how sales will be when process integration complete. They not be scientists. Why then they be calling themselves scientists? It may is not the correct. May is not the correct indeed.