An enterprise faces many problems in the course of doing business. To develop insight into these problems and to evaluate different courses of action, decision makers often rely on computer-based models of these problems as they apply to the enterprise.
Today, such models are often built "from scratch," because the problems span a set of organizational or functional boundaries that differ from those related to previous problems that have been modeled. However, the model of the problem at hand still requires access to most of the same databases that have been used previously; what is different most often relates to data form, aggregation, granularity, period, frequency, precision, and so on. Enterprise Manufacturing Intelligence (EMI), or simply Manufacturing Intelligence (MI), is a term which applies to software used to bring a corporation's manufacturing-related data together from many sources for the purposes of reporting, analysis, visual summaries, and passing data between enterprise-level and plant-floor systems. As data is combined from multiple sources, it can be given a new structure or context that will help users find what they need regardless of where it came from. The primary goal is to turn large amounts of manufacturing data into real knowledge and drive business results based on that knowledge.