Escalation management

This thesis investigates the effects of inflation upon costs and prices of building contracts. The aim is to facilitate effective management of such escalation, particularly through the provision of accurate forecasts. The literature survey considers escalation in a variety of project-based industries to establish the 'state of the art'. Examination of theoretical bases indicates causes of escalation, provides mechanisms for its measurement, including levels of accuracy and potential sources of errors in the measurements, and suggests techniques appropriate for the management of escalation. Requirements of clients, consultants and contractors for dealing with escalation are obtained via postal questionnaires, the results of which are used to test sub-hypotheses developed from the literature and theory. Criteria for escalation systems are established and those which are in common use are evaluated against the criteria. Correlation and regression techniques show that leading indicators of building activity, costs and prices exist but further work is required to develop robust leading indicators. Both regression techniques and stochastic time series analyses are applied to indices of building costs and tender prices. The resultant models are used to provide forecasts of the indices, errors being found by comparison of the forecasts with the realised indices. Forecasting accuracies are assessed against the errors of published predictions. Supplementary indices (e.g. location, contract type) are examined and compatibilities of various building cost/price data sets are considered. Analyses of completed building projects are used to model cash flow for NEDO work category indices for a typical building project. The model is combined with forecasts of the NEDO indices obtained from stochastic time series models to predict project escalation. Sensitivity analyses are performed to examine the accuracy and robustness of the escalation model. The research determines that stochastic time series approaches allow forecasts of costs and prices to be made which are more accurate than those currently available and which are more suited to clients', consultants' and contractors' needs.