Building Autopilots for Business: Leveraging Flight Science to create new Data Science Frameworks

We will discuss how leveraging Control System Theory, which informed and lead to the advent of flight control systems, is ushering in a new data-science framework for bringing automated insights to Enterprise. As organizations grow, managers start relying on data from several sources to make decisions concerning the organization and its customers. Organizations with a growing gap between desired results and actual results need a control system to better manage and predict results using their existing data. Control Theory is typically used in two forms: (1) Goal Seeking Model: For example autopilot guiding an aircraft from A to B. We will show how an organization looking to increase profits can be modeled as a Goal Seeking organization. (2) Disturbance Rejection Model; Sometimes seen in temperature control systems in buildings, in Enterprise an organization seeking to minimize costs, can be modeled using the Disturbance Rejection model. Both of these concepts are based on sound scientific principles that can be used to model and control businesses. The talk will include two real-world cases of how Emad Hasan translated these ideas into data science applications at Facebook and PayPal which powered executive decision making, as well as how they can now be used by data scientists and managers around the world to improve insights and cues for business executives.