Systematic ROI Assessment Framework for Legacy System Modernization

Authors

  • Rajkumar Chindanuru Anna University, India Author

DOI:

https://doi.org/10.32628/CSEIT251112317

Keywords:

Legacy Application Modernization, ROI Assessment Framework, Digital Transformation, Intangible Benefits Evaluation, Technology Investment Metrics

Abstract

This article presents a comprehensive framework for evaluating Return on Investment (ROI) in legacy application modernization initiatives, addressing the growing need for organizations to make data-driven decisions in their digital transformation journeys. The framework integrates both quantitative and qualitative dimensions of assessment, providing a structured approach to measuring the effectiveness of modernization efforts. By examining the interplay between tangible benefits, such as operational efficiency gains and cost reductions, alongside intangible benefits like improved business agility and enhanced user experience, the framework enables organizations to develop a holistic understanding of their modernization investments. Through a systematic evaluation methodology incorporating clearly defined business goals, cost-benefit analysis, intangible benefit assessment, and robust ROI metrics, organizations can better align their modernization initiatives with strategic objectives. The proposed framework not only facilitates initial decision-making but also supports continuous monitoring and optimization of modernization outcomes, contributing to the growing body of knowledge in digital transformation management. This article bridges the gap between theoretical modernization approaches and practical implementation considerations, offering valuable insights for technology leaders and decision-makers navigating the complexities of legacy system transformation.

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References

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Published

23-02-2025

Issue

Section

Research Articles

How to Cite

Systematic ROI Assessment Framework for Legacy System Modernization. (2025). International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 11(1), 3170-3179. https://doi.org/10.32628/CSEIT251112317