Productivity curve and social network analysis in science megaproject management

Abstract

Abstract Megaprojects aimed at delivering next-generation, multi-billion euro scientific research facilities are complex and high-risk endeavours, requiring expert knowledge spanning a wide spectrum of technical and administrative fields. Such organisations tend to evolve organically, responding to technical and political challenges. They are almost certain to fail to meet expectations on schedule, budget, and deliverables. Whilst there have been illuminating ‘top-down’ phenomenological megaproject studies recently, this article reports a ‘bottom-up’ perspective on the emergence of these issues. Firstly, the staff productivity distribution curves are analysed at a European science megaproject, and a stratified culture is identified: there is a small, high productivity ‘clique’, and a vast, low-productivity group of ‘outsiders’ operating at only 50% of their potential. The social network is then analysed, revealing a dense decision-making group that is only tenuously connected to technical expert teams via hierarchy. Staff inefficiency is linked to superfluous roles in middle management, carrying increased bureaucratic burdens and a financial loss ∼10% of the annual salary budget. Corrective suggestions are given, for the current megaproject and future activities to mitigate these causes. This should help to reduce some of the overspend, schedule overrun, and reductions in ambition and scope that have become megaproject norms.