A novel multiple linear regression model for forecasting S-curves

Purpose - Cash flow forecasting is an indispensable tool for construction companies, and is essential for the survival of any contractor at all stages of the work. A simple and fast technique of forecasting cash flow accurately is required, considering the short time available and the associated cost. Seeks to examine this issue. Design/methodology/approach - The paper argues that instead of producing an S-curve that is based on historical projects combined (state-of-the-art is based on classifying projects into groups and producing a standard curve for each group simply by fitting one curve into the historical data), here the attempt is to produce an individual S-curve for an individual project. A sample of data from 50 projects was collected and 20 criteria were identified to classify these projects. Using the most influential criteria, a multiple linear regression model was created to forecast the programme of works and hence the S-curves. A further six projects were used to validate and test the model. Findings - The results of the model developed in this paper were compared with previous models and evaluated. It is concluded that the model produced more accurate results than existing value and cost models. Originality/value - The paper proposes an alternative and novel approach to the development of standard value and cost commitment S-curves. This approach is based on a multiple linear regression model of the programmes of works.