Worldwide, the need for designing and constructing more sustainable buildings is constantly growing. Although the most critical time to make decisions on a building’s sustainable features is during the early stages of design, building performance analysis is usually performed after the design and construction documents are produced. This practice results in lost opportunities to maximise the use of energy efficient building design and technology options. Along with that, it is widely documented that productivity in the AEC/FM industry has been hampered by fragmentation, low innovation, adversarial relationships and slow adoption of Information Communication Technologies. Building Information Modelling (BIM) can promote integration among building professionals and improve design goals by allowing multi-disciplinary information to be integrated within one model. This creates an opportunity to conduct the analysis throughout the design process, concurrently with the production of the design documents. Despite the expected benefits of BIM and sustainable performance analysis, their practices have not been widely embedded within the UK AEC/FM industry. In order to achieve the change in current processes for optimal results, there is a need to define a number of aspects. These include the drivers, actions, good practices, impacts and benefits of sustainability analysis integration in the BIM-collaborative processes on one hand, and the barriers, limitations and deficiencies of current practice on the other. This paper is an early contribution to this ongoing research to improve the way of conducting BIM-based sustainability analysis and communicating the results among the various AEC participants. This can be achieved by automating and standarising the decision making process at the pre-construction stage. The findings indicate that there is no single tool that can be utilised to assess the full range of criteria required for achieving sustainability. It is also demonstrated how the capabilities of BIM-related sustainability software can be used to predict a number of the BREEAM rating system categories criteria.

• https://dspace.lboro.ac.uk/2134/14508