An investigation into the use of construction delay and disruption analysis methodologies

Abstract

Delay and disruption (DD) to contractors’ progress, often resulting in time and cost overruns, are a major source of claims and disputes in the construction industry. At the heart of the matter in dispute is often the question of the extent of each contracting party’s responsibility for the delayed project completion and extra cost incurred. Various methodologies have been developed over the years as aids to answering this question. Whilst much has been written about DD, there is limited information on the extent of use of these methodologies in practice. The research reported in this thesis was initiated to investigate these issues in the UK, towards developing a framework for improving DD analysis. The methodology adopted in undertaking this research was the mixed method approach involving first, a detailed review of the relevant literature, followed by an industry-wide survey on the use of these methodologies and associated problems. Following this, interviews were conducted to investigate the identified problems in more depth. The data collected were analysed, with the aid of SPSS and Excel, using a variety of statistical methods including descriptive statistics analysis, relative index analysis, Kendall’s concordance and factor analysis. The key finding was that DD analysis methodologies reported in the literature as having major weaknesses are the most widely used in practice mainly due to deficiencies in programming and record keeping practice. To facilitate the use of more reliable methodologies, which ensure more successful claims resolution with fewer chances of disputes, a framework has been developed comprising of: (i) best practice recommendations for promoting better record-keeping and programming practice and; (ii) a model for assisting analysts in their selection of appropriate delay analysis methodology for any claims situation. This model was validated by means of experts’ review via a survey and the findings obtained suggest that the model is valuable and suitable for use in practice. Finally, areas for further research were identified.