Information Technology (IT) Governance Framework with Artificial Neural Network and Balance Scorecard to Improve the Success Rate of Software Projects

Abstract

IT governance enables companies to plan and manage their IT investments in order to achieve their strategic objectives. Overall goal of this paper is to discuss about an approach to increase the success of the software projects through Artificial Intelligence. Standard governance standards are analyzed to understand the impact on software project success rates. Enterprise governance is a subset of IT governance that aids in the management of information technology resources. COBIT is a widely used methodology for developing effective enterprise IT governance. ISACA (Information Systems Audit and Control Association) stated implementation solution currently uses a sequentially ordered approach, which has raised issues. Several challenges have arisen as a result of top management's lack of commitment and misplaced solutions. Limitation on this investigation is the customized and confidential governance pattern used across various organization, hence there are very limited real time data for end-to-end analysis. Nonetheless, in combination with the agile project management paradigm, new project life-cycle solutions have evolved. Artificial Intelligence (AI) is an important element to address the increasing demand for machine learning systems. Artificial neural network (ANN) method is highly useful to arrive at best possible solution to improve the project success. This study found that ANN with Balance Score Card was exceptionally effective in providing the optimal solution to increase the project success rates.