Estimating a project's profitability: A longitudinal approach

Abstract

Forecasting a project's financial performance is central to aligning its operations with its strategic direction. Despite the panoply of approaches to predicting project performance, most studies focus on predicting the working capital and fixed capital requirements of projects. Few focus on forecasting profitability in the capital project industry. Thus, this longitudinal study of 121 capital projects identifies key variables in project initiation and planning phases that affect the profitability (return on sales) of completed projects. Subsequent multivariate robust regression analysis shows that the natural logarithm-transformed Scope and Team variables best explain the variation in profitability. The results show that the mean absolute percentage error (MAPE) value in the optimal forecasting model is 17.91%. Ultimately, our findings suggest that it is feasible to estimate a project's profitability before its execution.