Multiperspective Assessment of Enterprise Data Storage Systems: The Use of Expert Judgment Quantification and Constant Sum Pairwise Comparison in Finding Criteria Weights

Abstract

Digital transformation has taken center stage in every IT organization. Data is being created at various sources: edge, core, and cloud at an unprecedented rate. For enterprise IT infrastructure, this means more places to store data and more ways to store them. Storage solutions can be broadly categorized as Direct Attached Storage (DAS), Storage Area Network (SAN), Network Attached Storage (NAS), Hyperconverged Infrastructure (HCI), and Public Cloud Storage, each with its advantages and potential drawbacks. Besides computing and networking, storage is one of the core physical components of an IT infrastructure. Application performance and availability depend strongly on their underlying storage. As such, the selection of storage systems is one of the critical decisions for IT executives. Assessment of Enterprise Data Storage Systems (EDSS) for selecting the one that provides a comprehensive solution requires not only the consideration of technical performance and economic feasibility but also other perspectives such as strategic, operational, and regulatory. An assessment model with multiple perspectives and related criteria will serve as a valuable reference in the decision-making process. This study uses expert judgment to validate an assessment model covering Strategic, Technological, Operational, Regulatory, and Economic (STORE) perspectives and their related criteria. Expert judgment is also used to calculate the criteria weights using the constant sum pairwise comparison method. The results can be used for the evaluation of various storage alternatives under consideration. It is anticipated that the STORE assessment model and criteria weights will be valid for IT organizations in their long-term strategic decision-making.

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