Recent developments in energy management systems and the IoT (Internet of Things), have enabled easy, and low cost visibility of real time energy consumption data of not only main power lines but also individual devices. For anyone skilled in the art of energy management, it is obvious that such data contains incredible value that can help facility managers significantly increase the operational and energy efficiency of their sites. However, due to the shortage and cost of analytical resources, it is always a great challenge to practically and easily deliver such valuable insights out of so much data. As more and more devices are being monitored, the task becomes nearly impossible to manage manually. An article which I recently published as part of the latest research work we're doing in Panoramic Power, introduces an innovative data-science approach that helps automatically generate actionable energy and operational efficiency insights out of real time device level energy consumption data, using machine learning techniques.