Modelling client's value for money uncertainties in PFI projects

Private Finance Initiative (PFI) has successfully transformed the management of public sector construction projects by minimising construction risks and delivering projects with higher certainty in the time, cost, quality, and customer satisfaction than is with the counterpart traditional approach. The success rests in the principles of better Value for Money (VfM) demonstrated through the focus on whole-life costs and quality as the measure for economic, effective, and efficient procurement of the private sector and the delivery of the project and services thereafter. However, PFI has not addressed in full the expectation to provide better VfM due to uncertainties in the estimated project costs and persistent decrease in the specified client requirements as the project advances in the procurement process; hence, attracting distrust and resistance to the initiative. This highlights the need for a new approach to ensure that VfM is not only demonstrated at a point of procurement, but also monitored and sustained over the whole PFI contract period. This research explored the exposure of PFI projects to VfM uncertainty and developed a VfM Optimisation and Sustainability (VaS) model as it main scientific contribution. The developed model works abreast a Process Map, Taxonomy of uncertainty factors, and VfM Simulation and Monitoring Templates to define and develop VfM processes, create VfM, assess and test for its robustness, and sustain it through the entire project life. The model follows from a systematic analysis of the current practice and the uncertainties it creates. The analysis based on an empirical research that adopted a mixed-methods approach involving healthcare and transport PFI projects. The model was evaluated by experts from PFI projects and academics and by using simulation case studies. Adopting the model has the potential to improve the delivery of VfM through optimization of the benefits and costs during the project appraisal process, monitor and sustain VfM during the operating phase, and utilise lessons learnt for improvements in the future.