System Analytics is the process of investigating systems and calculating the way in which a system’s components interact with each other, how they function over time, and the way in which they operate within the context of larger technological and natural systems. A system can be described as any entity or object that consists of parts, each of which has a relationship with all other parts and to the entity as a whole. These parts work together in a predictable or planned way to achieve a specific goal. System Analytics requires knowledge related to (a) system inputs (i.e. people, materials, tools/machines, energy, information, finances, and time), (b) system processes (i.e. design, production, management), (c) system outputs (including desirable, undesirable, intended, unintended, immediate, and delayed outputs), (d) system feedback and control (including both internal and external controls), and (e) system optimization. This core concept is important to the practice of Quantitative Analysis as every physical and digital system is intertwined with a variety of natural, social, and technological systems, and is a system itself as well as developed through a system. The ability to analyze the design, function, and interaction of systems enables the development of dynamic controls that use data-comparing devices and sensors to optimize and automate system operations.