Agile science as a service
: a decision framework for next generation digital business services within the energy sector

Student thesis: Doctoral Thesis

Abstract

The literature on digital transformation that leverages cloud computing within the energy industry has been dominated by examples and issues from small to mid-size companies. This research focuses on the wider approach of how organisations, specifically within the energy industry can leverage the value of this transformation through a robust framework for success. The research is conducted via a series of research related to project management, cloud computing to run advanced data modelling applications within the industry context, is perhaps one of the biggest and most complete set of research pushing the boundaries of what you can do with sensitive data.
The thesis aimed to explore the vast array of complexity from a global perspective of evaluating and implementing innovative technology projects. Action research is used to examine the phenomena that exists across some major projects. These included an international project that was based in Japan, looking at the human side of mobilising and demobilising. Another study was conducted throughout a million-dollar cloud pilot which lasted over one year from start to finish.
The research was able to identify some emergent issues affecting initiation, implementation, technical security challenges and evaluation of a significant change to the security provision of critical data within a large international company affecting many stakeholder groups.
The research then looked at the legal and security aspects of data protection within the EU legal system and how this would change when moving from one legislation to another. The research later delved into the specifics of the industry looking at aspirations, challenges and technical architectures from a global perspective. The findings resulted in a framework for agile science which was applied and tested out through a pilot project within an industrial operation. The research makes a contribution by modelling some of the complexities of applying agile science within the industry context, particularly for large international companies.
Date of AwardMar 2020
Original languageEnglish
SupervisorAlice Good (Supervisor) & Carl Jeffrey Adams (Supervisor)

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