A Methodology for Decision Support for Implementation of Cloud Computing IT Services

Adela Tušanová,Ján Paralič

doi:10.12776/qip.v18i1.275

Abstract

The paper deals with the decision of small and medium-sized software companies in transition to SaaS model. The goal of the research is to design a comprehensive methodic to support decision making based on actual data of the company itself. Based on a careful analysis, taxonomy of costs, revenue streams and decision-making criteria are proposed in the paper. On the basis of multi-criteria decision-making methods, each alternative is evaluated and the alternative with the highest score is identified as the most appropriate. The proposed methodic is implemented as a web application and verified through case studies.

Highlights

Cloud computing is nowadays very popular business and scientific domain
3 PROPOSED METHODOLOGY FOR DECISION SUPPORT The result of our research is the methodology for decision support in the transition to the cloud computing SaaS model, consisting of nine steps, see Figure 1
This case study was atypical in two aspects - analysis of the software was focused only on cost analysis, as this is the most demanding part of the methodology and there was one more alternative examined – so-called in-house solution

Summary

Introduction

Cloud computing is nowadays very popular business and scientific domain. Cloud solutions are presented by their providers as the best IT solutions despite initial non confidence in safety. More and more software developers deal with the question to develop or do not develop their software solutions for cloud (and in the form of Software as a Service - SaaS). They still lack some kind of coherent methodology that would adequately support their decision in this matter. The aim of the analysis is to determine the current situation in the company and identify areas where cloud computing could improve the situation and how. To perform such an analysis deep knowledge of the analysed topic is necessary. Development of PaaS and SaaS solutions requires particular knowledge of the new architecture and new ISSN 1335-1745 (print) / ISSN 1338-984X (online)

Methods

Results

Conclusion