Análise dos riscos presentes nos custos da construção civil pelo método Monte Carlo

Abstract

With an increasingly competitive market and a very demanding consumer, every venture requires an economic feasibility study, a detailed budget and a rigorous physical-financial monitoring of the work. In this sense, cost control, obtained from the budget, consists of monitoring the execution of adjustments in the schedule in order to adapt it to the plan and to do the redesignations if necessary. Meanwhile, the evaluation of the economic risk involved in the production system allows the planning and execution of the activities considering the possible variations involved. To evaluate this risk, the Monte Carlo simulation technique has been employed, being the most simple and practical among the methods that use probability in the risk analysis. The overall objective of this research is to evaluate the risks that involve the costs of a large residential project. For this purpose, the main research strategy was the simulation of quantitative data, which will allow the development of a method that aims at identifying the risks related to the costs of an enterprise. This simulation of data was due to the construction sector not having the necessary data for the development of the model through the use of computational techniques to simulate the operation of productive systems from mathematical models. As a result the research showed the analysis of the budget, which in turn was divided into three parts: total budget; indirect costs; And direct costs. For that, the simulation was performed with 100,000 iterations with the program @risk. Considering the total budget, there was a 48.1% probability of the budget occurring within the confidence interval. In this case, it was considered a sensitivity analysis composed of three scenarios, in which only scenarios I and III became good alternatives for improving the budget. For indirect costs, a probability of only 11% of the costs occurred within the confidence interval. For this purpose, a single scenario was used, which reflected a probability of 42.2%. For indirect costs without adjustments, a probability of 61.8% was found. In this analysis two scenarios were considered, but they did not present themselves in a positive way. Given the results presented, it is possible to conclude that the main factor that leads the total budget to a relatively low probability is related to the large variations presented in indirect costs activities. However, it is possible to conclude from the risk analysis that the greater the severity (impact), the lower the likelihood of occurrence, and consequently the greater the risk of that budget. Given the results presented, the model presented as a good alternative to help future entrepreneurs in decision making.