Elevating Organizational Competitiveness: Deconstruction of Information System Management Models and Concepts Using Machine Learning
Kassem Danach *
Department of Information Technology and Management Systems, Faculty of Business Administration, Al Maaref University, Lebanon.
Jomana Al-Haj Hassan
Department of Computer Science, Faculty of Science, Islamic University, Lebanon.
*Author to whom correspondence should be addressed.
Abstract
This article discusses the role of machine learning in addressing the challenges of Information System (IS) management in today's business environment. It highlights the importance of data analytics, predictive maintenance, and security threat identification in overcoming the complexity of IS management. The article presents a custom framework that modifies paradigms for IS management, including data collection, continuous monitoring, machine learning model selection, and seamless integration. This approach is proven effective in solving problems and boosting competitiveness. The article provides risk mitigation techniques, realistic implementation methodologies, and case studies to help organizations embrace this innovative journey. The article concludes by highlighting the importance of implementing this novel paradigm as a necessary first step towards a data-driven, globally competitive future
Keywords: Information system management, organizational competitiveness, machine learning, framework, data analytics