Statistical model for schedule prediction: Validation in a housing-cooperative construction database

There are often considerable differences between the planned schedule for a construction project and what later develops during actual construction. This paper introduces an innovative approach that uses Markov Chain models to support predictions during earned value analyses. A statistical model was developed to predict possible deviations in a project schedule and the future progress of a project. This model, based on Markov chains, uses data from the past to adjust future predictions. A case study was built from a database of 90 housing cooperative construction projects and was validated in 12 more projects. A cross validation of three interactions was also carried out, obtaining an error of 2.38% in the prediction of future progress and an error of 4.29% in the prediction of construction timing. The innovative prediction model presented in this paper contributes to the management body of knowledge by introducing a new tool for the management and control of construction timing. The method presented improves construction management because it predicts future deviations in schedules with reduced errors and determines total deviation from a construction schedule with great precision. This allows better control over work timing and represents important input in determining strategies and future actions.