Estimating the Accuracy of the Return on Investment (ROI) Performance Evaluations

Alexei Botchkarev
Interdisciplinary Journal of Information, Knowledge, and Management  •  Volume 10  •  2015  •  pp. 217-233
Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly) is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications) was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties.
Return on Investment, ROI, evaluation, costs, benefits, accuracy, estimation error, error propagation, uncertainty, information system, performance measure, business value
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