A methodology based on benchmarking to learn across megaprojects: The case of nuclear decommissioning. Issue 1 (5th March 2018)

• Record Type: Journal Article
• Authors: Invernizzi, Diletta Colette; Locatelli, Giorgio; Brookes, Naomi J.
• Is Part Of: International journal of managing projects in business. Volume 11:Issue 1(2018)
• Page Start: 104
• Page End: 121
• Publication Date: 2018-03-05
• Subjects: Benchmarking -- Methodology -- Megaprojects -- Cross-case study -- Nuclear decommissioning; Project management -- Periodicals; Electronic journals; 658.404
• DOI: 10.1108/IJMPB-05-2017-0054
• Languages: English
• ISSNs: 1753-8378

Abstract

Abstract : Purpose: The literature lacks a single and universally accepted definition of major and megaprojects: usually, these projects are described as projects with a budget above $1 billion and a high level of innovation, complexity, and uniqueness both in terms of physical infrastructure and stakeholder network. Moreover, they often provide fewer benefits than what were originally expected and are affected by delays and cost overruns. Despite this techno-economic magnitude, it is still extremely hard to gather lessons learned from these projects in a systematic way. The purpose of this paper is to present an innovative methodology based on benchmarking to investigate good and bad practices and learn from a portfolio of unique megaprojects. Design/methodology/approach: The methodology combines quantitative and qualitative cross-comparison of case studies and statistical analysis into an iterative process. Findings: Indeed, benchmarking offers significant potential to identify good and bad practices and improve the performance of project selection, planning, and delivery. Research limitations/implications: The methodology is exemplified in this paper using the case of Nuclear Decommissioning Projects and Programmes (NDPs). Originality/value: Indeed, due to their characteristics, NDPs can be addressed as megaprojects, and are a relevant example for the application of the methodology presented here that collects and investigates the characteristics that mostly impact the performance of (mega)projects, through a continuous learning process.