Addressing Bureaucratic Inefficiencies: A Case Study on Adaptation of Waterfall Methodology for Improved Project Management

Abstract

This paper aims to explore the bottlenecks in the project management processes of a large profit driven Oil & Gas downstream sector organization which has adopted traditional predictive methodology. Annually, the company elaborates and refines a portfolio of programs and projects for execution, but the performance of its Project Management Office (PMO) has been on the decline, resulting in a failure to utilize the budget that gets allocated each year. The author conducts this research to discover if bureaucratic inefficiencies and lack of process adaptations are among the real causes of the problem. This research employs qualitative research methodology and an inductive research approach. The primary data collection method includes semi-structured, face-to-face interviews of the PMO employees to gain an in-depth understanding of their experiences and to determine the challenges and inefficiencies they encounter in project management. Moreover, a thorough case study analysis and review of literature on project management frameworks, methodologies, and best practices from other industries was also conducted. The focus was given to predictive project management methodologies (e.g. Waterfall, Critical Path Method (CPM), Program Evaluation and Review Technique (PERT)) to see how these approaches can be used to fight the bureaucratic inefficiencies that are typical for them. The examples of literature review show how the customization of these methodologies can reduce administrative burden while maintaining project control. The outcomes of this research can be useful for the top management of the organization under this study and other O&G downstream companies that encounter similar project management issues. As a result, the study tries to enhance the efficiency and effectiveness of project management practices in such organizations through revealing existing problems and discussing potential solutions to those deficiencies of the predictive project management methodology.