This thesis presents Organisational Sustainability Modelling (OSM), a new method to model and analyse risk and return systematically for the adoption of large systems such as Cloud Computing. Return includes improvements in technical efficiency, profitability and service. Risk includes controlled risk (risk-control rate) and uncontrolled risk (beta), although uncontrolled risk cannot be evaluated directly. Three OSM metrics, actual return value, expected return value and risk-control rate are used to calculate uncontrolled risk. The OSM data collection process in which hundreds of datasets (rows of data containing three OSM metrics in each row) are used as inputs is explained. Outputs including standard error, mean squared error, Durbin-Watson, p-value and R-squared value are calculated. Visualisation is used to illustrate quality and accuracy of data analysis. The metrics, process and interpretation of data analysis is presented and the rationale is explained in the review of the OSM method. Three case studies are used to illustrate the validity of OSM: • National Health Service (NHS) is a technical application concerned with backing up data files and focuses on improvement in efficiency. • Vodafone/Apple is a cost application and focuses on profitability. • The iSolutions Group, University of Southampton focuses on service improvement using user feedback. The NHS case study is explained in detail. The expected execution time calculated by OSM to complete all backup activity in Cloud-based systems matches actual execution time to within 0.01%. The Cloud system shows improved efficiency in both sets of comparisons. All three case studies confirm there are benefits for the adoption of a large computer system such as the Cloud. Together these demonstrations answer the two research questions for this thesis: 1. How do you model and analyse risk and return on adoption of large computing systems systematically and coherently? 2. Can the same method be used in risk mitigation of system adoption? Limitations of this study, a reproducibility case, comparisons with similar approaches, research contributions and future work are also presented.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:588909 |
| Date | January 2013 |
| Creators | Chang, Victor |
| Contributors | Wills, Gary ; Walters, Robert |
| Publisher | University of Southampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://eprints.soton.ac.uk/361523/ |
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