Cost Control Problems in Construction Projects in Congo-Brazzaville

This study was undertaken with the aim of achieving better cost control in construction projects in Congo-Brazzaville, through the analysis and monitoring of variances and deviations in project estimates and actual costs. Indeed, in the field of building and civil infrastructure construction in Congo-Brazzaville, cost management problems occur recurrently from the preliminary estimation stage and throughout project execution. Poorly conducted estimates often lead to either underestimation or overestimation of the project’s total cost. Furthermore, a lack of coordination during construction often causes disruptions in site organization, resulting in significant financial deviations. Consequently, there is generally a noticeable gap between the estimated and the actual construction costs. In developing countries (D.C.s) such as Congo, it is uncommon for a construction project to meet both its scheduled completion time and its initial estimated budget. Chronic time and cost overruns therefore represent a major issue within the sector. The main objective of this work is to develop reliable estimation models capable of anticipating actual costs as early as the feasibility stage. For this purpose, construction cost data were collected from several design offices, covering twenty-five (25) single-storey building projects and twenty (20) two-storey (R + 1) building projects. Statistical analysis, conducted using the SPSS software through a step-by-step multiple linear regression approach, led to the development of two cost estimation models according to building type. Both models proved to be highly significant according to the ANOVA test (sig. = 0.00), with a strong predictive power confirmed by the high coefficient of determination (R²). The models include eight and six explanatory variables respectively, each related to total cost. Validation results showed that the predicted values are very close to the observed actual values, with low residuals: from 0.04% to 1.81% for single-storey buildings and from 0.10% to 7.07% for two-storey buildings. These results indicate that the developed models provide highly reliable cost estimations, with small deviations from observed values. However, the tolerance margin—estimated at over 30% of the predicted value—remains relatively high. Thus, these models represent a relevant decision-support tool for the feasibility phase of construction projects, but still require further adjustments to improve their accuracy and to better control error margins related to real execution conditions in