MULTIPERSPECTIVE ASSESSMENT OF ENTERPRISE DATA STORAGE SYSTEMS USING HIERARCHICAL DECISION MODELING

Abstract

This paper offers a multiperspective framework for assessing Enterprise Data Storage Systems (EDSS) with Hierarchical Decision Modeling (HDM). The research was based on a practical issue many organizations face; selecting a storage architecture is no longer simply about performance alone but about strategic alignment, operable management, legal compliance and sustainable economics. Therefore, the authors have developed a HDM model to identify the decision problem through five STORE perspectives – Strategic, Technological, Operational, Regulatory, and Economic – and use Constant-Sum Pairwise Comparisons to elicit expert opinion. Structured surveys were used to collect expert opinion in the empirical part of the research to assess five different storage architectures: Direct Attached Storage (DAS), Network-Attached Storage (NAS), Storage-Area-Network (SAN), Cloud storage, and Hybrid Storage. Results indicate that both technical and legal factors are the most significant when it comes to the overall importance of the perspectives in the evaluation process and finally that the last ranking indicates that Hybrid Storage is preferred over all other alternatives followed by SAN, Cloud, NAS and DAS. Finally, the authors demonstrate how HDM can provide a methodical approach to aggregate multiple expert opinions and therefore support more defensible EDSS selections in enterprise environments.