A Return on Investment as a Metric for Evaluating Information Systems: Taxonomy and Application

Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics used in business analysis. ROI analysis (when applied correctly) is a powerful tool for evaluating existing information systems and making informed decisions on software acquisitions and other projects. Decades ago, ROI was conceived as a financial term and defined as a concept based on a rigorous and quantifiable analysis of financial returns and costs. At present, ROI has been widely recognized and accepted in business and financial management in the private and public sectors. Wide proliferation of the ROI method, though, has lead to the situation today where ROI is often experienced as a non-rigorous, amorphous bundle of mixed approaches, prone to the risks of inaccuracy and biased judgement. The main contribution of this study is in presenting a systematic view of ROI by identifying its key attributes and classifying ROI types by these attributes. ROI taxonomy has been developed and discussed, including traditional ROI extensions, virtualizations, and imitations. All ROI types are described through simple real life examples and business cases. Inherent limitations of ROI have been identified and advice is provided to keep ROI-based recommendations useful and meaningful. The paper is intended for researchers in information systems, technology solutions, and business management, and also for information specialists, project managers, program managers, technology directors, and information systems evaluators.