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

Alexei Botchkarev

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 ROI sensitivity to error is a natural thought, and common sense suggests that ROI evaluations cannot be absolutely accurate. However, literature review revealed that in most publications and analyst firms reports, this issue is just overlooked. On the one hand, the results of the ROI calculations are implied to be produced with a mathematical rigor, possibility of errors is not mentioned and amount of errors is not estimated. On the contrary, another approach claims ROI evaluations to be absolutely inaccurate because, in view of their authors, future benefits (especially, intangible) cannot be estimated within any reasonable boundaries. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of the information systems implementations. 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. The results of this research are 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. Most results are applicable to ROI evaluations in a wider subject area.

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