Factors of Uncertainty in Forecasting the Cost of Construction and Installation Works in Investment Construction Projects

The article addresses the issue of uncertainty in forecasting the cost of construction and installation works (CIW) in investment construction projects under conditions of high price volatility, regional market differentiation, organizational fragmentation of business processes, and insufficient formalization of pricing procedures. An analysis of external and internal factors affecting the accuracy of cost forecasts is carried out. Particular attention is given to macroeconomic, logistics-related, seasonal, design and technological, organizational and process-related, and information-based sources of uncertainty. A significant share of forecasting errors is caused not only by market volatility, but also by imperfections in baseline data, the subjectivity of expert assessments, weak coordination between departments, and the absence of a unified digital environment for cost formation. The purpose of the study is to identify and systematize uncertainty factors affecting the accuracy of forecasting the cost of construction and installation works, as well as to substantiate approaches to their reduction based on digitalization and the use of intelligent data analysis methods. The objectives of the study include analyzing the key uncertainty factors, comparing cost forecasting methods, and developing practical recommendations for improving forecast accuracy. The paper systematizes uncertainty factors by project life cycle stages and by levels of managerial influence. A comparison of traditional and intelligent cost forecasting methods is performed. The necessity of transitioning from classical cost estimation analysis to a digital cost management framework is substantiated. The practical significance of the study lies in the development of a set of recommendations aimed at reducing uncertainty in forecasting the cost of CIW, including the standardization of baseline data, improvement of the transparency of procedures for reviewing commercial proposals, digitalization of cost change approval processes, implementation of price monitoring systems, and the use of predictive analytics in the management of investment construction projects.