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A proposed model to analyse risk and return for a large computing system adoption

A proposed model to analyse risk and return for a large computing system adoption
A proposed model to analyse risk and return for a large computing system adoption
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.
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
Walters, Robert
7b8732fb-3083-4f4d-844e-85a29daaa2c1

Chang, Victor (2013) A proposed model to analyse risk and return for a large computing system adoption. University of Southampton, Physical Science and Engineering, Doctoral Thesis, 288pp.

Record type: Thesis (Doctoral)

Abstract

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.

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More information

Published date: November 2013
Organisations: University of Southampton, Electronic & Software Systems

Identifiers

Local EPrints ID: 361523
URI: https://eprints.soton.ac.uk/id/eprint/361523
PURE UUID: 0f82a4b5-4b6d-4915-83bc-0b9eecc1371f
ORCID for Gary Wills: ORCID iD orcid.org/0000-0001-5771-4088

Catalogue record

Date deposited: 27 Jan 2014 09:54
Last modified: 06 Jun 2018 13:03

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