Prioritization of applications for software-As-A-service migration using total life cycle costs and the analytic network process

Eugene Rex L. Jalao, Dan Shunk, Teresa Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The current state of the world economy has made Software-As-A-Service (SaaS) an appealing concept for organizations with a small budget for IT infrastructure investment. In a SaaS setup, companies subscribe software applications on a pay-per-use system from external service providers over the internet. However, these companies are looking for a decision framework that can be used to prioritize business software applications for SaaS migration. This paper attempts to fill in this gap by proposing a hybrid methodology which is composed of a total system life cycle (SLC) cost analysis for cost estimation and the analytic network process (ANP) for prioritization. Real test case data is used to validate the decision making capability of the framework. Sensitivity analysis was done to determine the robustness of the recommendations using Monte Carlo simulation. Results show that the proposed methodology could aid managers prioritizes software application projects for SaaS migration.

Original languageEnglish (US)
Title of host publicationProceedings of the World Congress on Engineering 2012, WCE 2012
EditorsA. M. Korsunsky, Len Gelman, Andrew Hunter, S. I. Ao, David WL Hukins
PublisherNewswood Limited
Pages1352-1357
Number of pages6
ISBN (Print)9789881925220
StatePublished - 2012
Event2012 World Congress on Engineering, WCE 2012 - London, United Kingdom
Duration: Jul 4 2012Jul 6 2012

Publication series

NameLecture Notes in Engineering and Computer Science
Volume3
ISSN (Print)2078-0958

Other

Other2012 World Congress on Engineering, WCE 2012
Country/TerritoryUnited Kingdom
CityLondon
Period7/4/127/6/12

Keywords

  • ANP
  • Business Applications
  • Monte Carlo Simulation
  • SaaS
  • System Life Cycle Cost

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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