Drivers for energy analysis towards a BIM-enabled information flow

Ahmad Mohammad Ahmad, Sergio Rodriguez-Trejo*, Mian Atif Hafeez, Nashwan Dawood, Mohamad Kassem, Khalid Naji

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
28 Downloads (Pure)


The paper presents a set of Key Performance Indicators (KPIs) extracted from the developed Energy Analysis (EA) process maps and interviews with expert stakeholders. These KPIs stem from the literature review and link to the benefits of EA through industry expert review. The study includes; i) Development and validation of EA process maps adjusted to requirements from different stakeholders. ii) KPIs aligned with the EA process map. iii) Identification of the drivers that can facilitate lifecycle information exchange. iv) Opportunities and obstacles for EA within Building Information Modelling (BIM) enabled projects.

EA within a BIM enables consistent data integration in central repositories and eases information exchange, reducing rework. However, data loss during information exchange from different BIM uses or disciplines is frequent. Therefore, a holistic approach for different BIM uses enables a coherent lifecycle information flow. The lifecycle information flow drives the reduction of data loss and model rework and enhances the seamless re-use of information. The latter requires a specification of the EA KPIs and integrating those in the process.

This paper depicts a viable alternative for EA process maps and KPIs in a BIM-enabled AEC design industry. The findings of this paper showcase the need for an EA within BIM with these KPIs integrated for a more effective process conforming to the current OpenBIM Alliance guidance and contributing towards sustainable lifecycle information flow.

Research limitations/implications:
The limitation of the research is the challenge of generalising the developed EA process maps; however, it can be adjusted to fit defined organisational use. The findings deduced from the developed EA process map only show KPIs to have the ability to facilitate adequate information flow during EA.

Practical implications:
The AEC industry will benefit from the findings of this primary research as they will be able to contrast their process maps and KPIs to those developed in the paper.

Social implications:
This paper benefits the societal values in energy analysis for the built environment in the design stages. The subsequent lifecycle information flow will help achieve a consistent information set and decarbonised built environment.

The paper offers a practical overview of process maps and KPIs to embed EA into BIM, reducing the information loss and rework needed in the practice of this integration. The applicability of the solution is contrasted by consultation with experts and literature.
Original languageEnglish
Pages (from-to)507-533
Number of pages27
JournalSmart and Sustainable Built Environment
Issue number3
Early online date20 Apr 2022
Publication statusPublished - 10 Apr 2023


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