The development of residential automation and energy management systems have aimed to achieve energy reduction within the home. These systems have been developed to compliment human behaviour and potentially impart change in the way people consume energy. The development of energy efficient buildings has been considered a sustainable approach to better manage or optimise energy consumption and generation within a building however, multiple studies have demonstrated some limitations to these buildings and systems. The advancement of the home system of practice using the basis of Social Practice Theory has demonstrated a new focus for the design methodology of these systems. The home system of practice outlines the routines and repetitive nature of individual lifestyles, and these routines result in the temporal characteristic of energy consumption. This study monitored an Australian home that consisted of renewable energy systems, smart technology and automated systems designed to reduce the use of grid electricity. The aim was to understand the performance of the automation systems and interaction with the occupants and their routines. The paper discusses the effectiveness of incorporating social theories and the home system of practice into the design of energy efficient buildings and energy management systems. The methodology utilised machine learning techniques to identify patterns in energy consumption data and related these patterns to the routines and lifestyles of the home occupants. These patterns aimed to describe why the automation system incorporated into the study home did not operate as intended and how design changes can increase effectiveness and performance.