Measuring The Business Value Of Cloud Computing
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Measuring the Business Value of Cloud Computing
The importance of demonstrating the value achieved from IT investments is long established in the Computer Science (CS) and Information Systems (IS) literature. However, emerging technologies such as the ever-changing complex area of cloud computing present new challenges and opportunities for demonstrating how IT investments lead to business value. Recent reviews of extant literature highlights the need for multi-disciplinary research. This research should explore and further develops the conceptualization of value in cloud computing research. In addition, there is a need for research which investigates how IT value manifests itself across the chain of service provision and in inter-organizational scenarios. This open access book will review the state of the art from an IS, Computer Science and Accounting perspective, will introduce and discuss the main techniques for measuring business value for cloud computing in a variety of scenarios, and illustrate these with mini-case studies.
The Economics of Cloud Computing
The Economics of Cloud Computing An Overview for Decision Makers Bill Williams Foreword by George Reese, author of Cloud Application Architectures The decision-maker’s guide to cloud computing: from making the case to managing the transition This concise book delivers the insight and tools you need to make intelligent decisions about cloud computing and effectively manage the transition to this new paradigm. Bill Williams explains how cloud computing platforms are transforming business IT and helps you fully understand the economies of scale and other benefits associated with “the cloud.” Williams defines and explains cloud computing platforms and technologies, analyzes the costs associated with the IT supply chain, and (using industry standard metrics) creates a process for measuring the value of implementing cloud service models. He presents realistic and up-to-date ROI and NPV calculations comparing cloud strategies with conventional investments in owned/leased hardware. Through additional examples, he addresses costs and savings related to software licensing and disaster recovery/high availability, offering even deeper practical insight into the financial impact of cloud computing. Writing for business leaders and “in-the-trenches” managers, Williams outlines the impact of cloud computing on the IT supply chain by contrasting legacy processes and systems with cloud computing implementations. To simplify deployment, Williams presents easy-to-use tables, a decision-maker checklist, and a comprehensive collection of additional resources for further study. · Understand today’s leading cloud service and deployment models · Identify the major characteristics of cloud computing platforms · Use key performance/success indicators to measure IT performance and influence business strategies · Quantify the baseline costs of your current IT value chain · Use TCO, the payback method, ROI, NPV, and other metrics to justify cloud deployments · Calculate the total financial impact of migrating to “the cloud” · Place cloud computing in the historical context of technological revolutions · Recognize the long-term social and global benefits of cheap and ubiquitous computing This volume is in the Network Business Series offered by Cisco Press®. Books in this series provide IT executives, decision makers, and networking professionals with pertinent information about today’s most important technologies and business strategies.
Proceedings of 23rd International Conference on Informatics in Economy (IE 2024)
This book includes high-quality research papers presented at 23rd International Conference on Informatics in Economy (IE 2024), which is held in Bucharest, Romania, during May 2024. This book covers research results in business informatics and related computer science topics, such as IoT, mobile-embedded and multimedia solutions, e-society, enterprise and business solutions, databases and big data, artificial intelligence, data mining and machine learning, quantitative economics.