The article focuses on highlighting the role of life cycle costing (LCC) in the preparatory and implementation phase of residential projects. It involves the evaluation of several investment scenarios in the pre-investment phase, the choice between variants of the design of the entire building or its parts, and the choice of variants of structures and equipment with acceptable parameters. An innovative method of evaluating the life cycle of buildings is described in the article. This method was tested in selected residential projects realized by Skanska in the Czech Republic. Experience from construction practice shows that the choice of variants, constructions, or equipment of buildings only on the basis of the lowest acquisition costs (lowest bid prices) is wrong. The LCC calculation tool has been designed to model life cycle costs of individual variants of construction designs with different input parameters. It is possible to analyze the components or equipment that have the greatest impact on total life cycle costs. The article presents a tool that evaluates the long-term economic efficiency of the proposed residential buildings in terms of analysis of life cycle costs. The article will also expand the knowledge of the professional and general public about the importance of examining investment and operating costs already in the phase of construction preparation.

The article deals with problematic parts of automated processing of quantity takeoff (QTO) from data generated in BIM model. It focuses on models of road constructions, and uses volumes and dimensions of excavation work to create an estimate of construction costs. The article uses a case study and explorative methods to discuss possibilities and problems of data transfer from a model to a price system of construction production when such transfer is used for price estimates of construction works. Current QTOs and price tenders are made with 2D documents. This process is becoming obsolete because more modern tools can be used. The BIM phenomenon enables partial automation in processing volumes and dimensions of construction units and matching the data to units in a given price scheme. Therefore price of construction can be estimated and structured without lengthy and often imprecise manual calculations. The use of BIM for QTO is highly dependent on local market budgeting systems, therefore proper push/pull strategy is required. It also requires proper requirements specification, compatible pricing database and software.

When using Building Information Modeling (BIM) for complex building design, optimizing the building quality in a design phase becomes an important part of integrated and advanced building design. The use of data from an information model in the design phase allows efficient assessment of different design strategies and structural variants and a higher quality of the final design. This paper aims to analyze and verify possible BIM data-driven workflows for Complex Building Quality Assessment (CBQA) and a suitable BIM data structure set up for automatic assessment and evaluation. For an efficient automation process in complex quality building assessment in the design phase, it is necessary first to understand the data structure of the Industry Foundation Classes (IFC), which is widely accepted and used for buildings, and second to understand the data structure of the assessment methodology used for the assessment. This article describes possible data workflows for an automatic assessment based on the experience gained on a case study of the real pilot project of a residential building, where the complex building quality was tested using SBToolCZ, the Czech national assessment method. This article presents the experience and recommendations for setting up the data model of a building for automatic assessment.

This study explores the diverse array of risks inherent in building renovation investments and proposes effective strategies for risk mitigation tailored to investors. Through a combination of qualitative analysis, expert interviews, and quantitative risk quantification techniques, the research identifies and evaluates key risk factors across regulatory, financial, technical, market, and other domains. Thorough due diligence, proactive stakeholder engagement, and contingency planning emerge as critical components of effective risk management in renovation projects. The study underscores the importance of proactive risk mitigation in enhancing project success and investor returns. By providing investors with a comprehensive understanding of the challenges they may face and practical strategies for addressing them, this research aims to empower stakeholders to make informed decisions and achieve positive outcomes in building renovation investments, ultimately contributing to a more resilient and sustainably built environment.