The Operational Impact of Analytics in Global Major Telcos

Abstract

This paper focuses primarily on big data and analytics in the context of global telecommunications. Telecommunications is one of the most data-sustaining industries, where data is used across all dimensions of operations, such as IT and network management. The article points out that how operators wish to be data driven, they are unable to put this into practice as the data processing, data normalization, and data reporting present a challenge. The purpose of this study is to evaluate the state of the art of human decision support systems with respect to telecom operations in practice, highlight the relevant existing problematic aspects, and indicate the directions, where enhancement, especially in the context of AI and Gen-AI is likely to appear. The research points that stakeholders need to think out of the box and provides two operational approaches how analytics driven operations can be realized, in the first place with the help of cognitive managed services. The results obtained in the study demonstrate that while impact of analytics is usually associated with cutting down the costs, the real advantage of such analytics is in levers for operational initiatives to improve the level of service and efficiency. The said research stresses the importance of people, processes and technology in a mature operational model. It also notes the need for maintaining certain standards not only of data traceability but of data quality in a bid to enhance the feasibility of analytics accent strategy. The main novelty of the present research lies in the transformational nature of analytics in telecom operations that the research addresses in proposing a systematic way of dealing with decision processing which entails the use of artificial intelligence algorithms and data quality system. The paper also presents an analytics framework for telecom operators in order to realize the unrealized bulging potential of analytics.

Keywords: Telecom Operations, Big Data, Analytics, AI (Artificial Intelligence), Gen-AI

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