Development of a BIM-Enabled Automated Cost Segregation System

The cost segregation study is a tax planning strategy employed to optimize cash flow by redefining real estate assets as personal property and land improvement, enabling accelerated tax depreciation. However, conventional cost segregation practices suffer from limitations, such as time-consuming procedures and high associated costs, which hinder their effectiveness. To overcome these challenges, this paper presents an innovative strategy that integrates Building Information Modelling (BIM) to develop an automated cost segregation system. The research aims to optimize the workflow by developing a BIM model and using 5D BIM to perform a cost segregation study by categorizing building elements under a Modified Accelerated Cost Recovery System (MACRS). This workflow aims at minimizing the time and financial resources expended with traditional methodologies. The proposed workflow enables precise identification and separate depreciation of building components, resulting in significant tax deductions that would otherwise be unattainable. The results indicate that performing cost segregation with BIM leads to a significant increase in depreciation amounts, particularly during the initial six years, while also raising the net present value of depreciation by 45%. The integration of BIM technology facilitates effective management and sharing of cost segregation data among stakeholders, enhancing collaboration and decision-making throughout the project lifecycle. Owners can optimize cost management and financial planning, identifying tax-saving opportunities and improving cash flow. General Contractors (GCs) can leverage the system during the bidding process, enhancing their competitiveness and project acquisition potential. Future research can explore the integration of cost segregation modules from BIM with asset management tools, enabling improved facility and fiscal management of building components. Such integration holds promise for enhancing the construction and real estate industry’s overall efficiency and performance.

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