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Leveraging Business Intelligence as a Catalyst for Strategic Decision-Making in Emerging Telecommunications Markets
Subject area: Management and Commerce · Area of research: Business Intelligence in Telecommunications
Abstract
Emerging telecommunications markets are characterized by rapid subscriber growth, increasing data volumes, and evolving consumer demands, presenting both opportunities and challenges for operators. Traditional decision-making approaches in these markets are often reactive, fragmented, and constrained by limited analytical capabilities, leading to inefficiencies, delayed responses to market trends, and suboptimal resource allocation. Business Intelligence (BI) has emerged as a critical tool to bridge these gaps by integrating data management, analytics, and visualization into strategic decision-making processes. This explores how BI can serve as a catalyst for informed, proactive, and data-driven decision-making in emerging telecommunications markets. By consolidating diverse data sources?including network usage, billing, customer behavior, digital engagement, and IoT-enabled services?BI enables operators to generate actionable insights that support operational efficiency, customer-centric strategies, and revenue optimization. The framework emphasizes BI applications across multiple strategic domains, including network optimization, customer experience and retention, revenue management, and market expansion. In particular, predictive analytics and real-time dashboards allow operators to anticipate congestion, identify churn risks, personalize offerings, and target underserved regions with tailored products and services. Implementation pathways involve establishing robust data infrastructure, building analytics capabilities, fostering organizational alignment, and deploying BI solutions through phased rollouts that prioritize pilot initiatives, scaling, and continuous refinement. Challenges such as data quality issues, high implementation costs, skill gaps, and organizational resistance are addressed through standardized data protocols, training programs, cloud-based solutions, and leadership-driven change management. Ultimately, leveraging BI enables telecom operators in emerging markets to improve decision-making speed and accuracy, enhance operational efficiency, strengthen customer engagement, and achieve competitive differentiation. By embedding data-driven intelligence into strategic planning and execution, operators can navigate dynamic market environments, anticipate consumer needs, and drive sustainable growth, positioning themselves for long-term success in the rapidly evolving telecommunications landscape.
Keywords
Business Intelligence, Strategic Decision-Making, Emerging Telecommunications Markets, Data-Driven Strategy, Analytics Integration, Predictive Insights, Operational Efficiency, Customer Segmentation, Market Competitiveness, Real-Time Reporting, Performance Metrics
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How to cite this paper
@article{1710818,
author = {Stanley Tochukwu Oziri, Adesola Abdul-Gafar Arowogbadamu, Omorinsola Bibire Seyi-Lande},
title = {Leveraging Business Intelligence as a Catalyst for Strategic Decision-Making in Emerging Telecommunications Markets},
journal = {Iconic Research And Engineering Journals},
year = {2018},
volume = {2},
number = {3},
pages = {92-105},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710818.pdf},
abstract = {Emerging telecommunications markets are characterized by rapid subscriber growth, increasing data volumes, and evolving consumer demands, presenting both opportunities and challenges for operators. Traditional decision-making approaches in these markets are often reactive, fragmented, and constrained by limited analytical capabilities, leading to inefficiencies, delayed responses to market trends, and suboptimal resource allocation. Business Intelligence (BI) has emerged as a critical tool to bridge these gaps by integrating data management, analytics, and visualization into strategic decision-making processes. This explores how BI can serve as a catalyst for informed, proactive, and data-driven decision-making in emerging telecommunications markets. By consolidating diverse data sources?including network usage, billing, customer behavior, digital engagement, and IoT-enabled services?BI enables operators to generate actionable insights that support operational efficiency, customer-centric strategies, and revenue optimization. The framework emphasizes BI applications across multiple strategic domains, including network optimization, customer experience and retention, revenue management, and market expansion. In particular, predictive analytics and real-time dashboards allow operators to anticipate congestion, identify churn risks, personalize offerings, and target underserved regions with tailored products and services. Implementation pathways involve establishing robust data infrastructure, building analytics capabilities, fostering organizational alignment, and deploying BI solutions through phased rollouts that prioritize pilot initiatives, scaling, and continuous refinement. Challenges such as data quality issues, high implementation costs, skill gaps, and organizational resistance are addressed through standardized data protocols, training programs, cloud-based solutions, and leadership-driven change management. Ultimately, leveraging BI enables telecom operators in emerging markets to improve decision-making speed and accuracy, enhance operational efficiency, strengthen customer engagement, and achieve competitive differentiation. By embedding data-driven intelligence into strategic planning and execution, operators can navigate dynamic market environments, anticipate consumer needs, and drive sustainable growth, positioning themselves for long-term success in the rapidly evolving telecommunications landscape.},
keywords = {Business Intelligence, Strategic Decision-Making, Emerging Telecommunications Markets, Data-Driven Strategy, Analytics Integration, Predictive Insights, Operational Efficiency, Customer Segmentation, Market Competitiveness, Real-Time Reporting, Performance Metrics},
month = {September},
}