Enhancing Telecom Service Performance with Real-Time Dashboards: An Analysis of Impact and User Adoption
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Telecommunications, Dashboard, Real-time Data, Key Performance Indicators, Data Visualization, Big Data, Telecom Service Performance, Strategic Decision Making
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Abstract
"Unlock the full potential of your telecom services with our cutting-edge Performance Dashboards, designed to transform vast amounts of data into actionable insights. With 92% of users reporting real-time data updates and 84% satisfaction with personalization, our Dashboards drive strategic decision-making and improve Key Performance Indicators (KPIs). Discover how our innovative solution can help you monitor network performance, reduce customer cancellations, and stay ahead in the competitive telecom landscape. Explore the benefits of integrating Big Data technologies and AI-powered search to take your telecom services to the
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[...] Integrating various real-time data sources can be complex and costly. Kimball and Ross (2013) note that consolidating data from different platforms requires robust ETL systems and high-performance data infrastructure. Technical limitations also include performance and latency challenges. Processing and visualizing real-time data requires significant resources and advanced distributed processing technologies, such as Apache Kafka and Spark (Kreps et al., 2011; Zaharia et al., 2016). On an organizational level, adopting real-time Dashboards can be hindered by resistance to change and a lack of technical skills. [...]
[...] 4.3.2.2 Adaptation to Specific Departmental Needs To better adapt the Dashboards to the specific needs of different departments, several suggestions have been made. Users want more autonomy to personalize their Dashboards, which would allow them to adjust the tool to their particular needs. Paradoxically, some suggest standardizing the Dashboards for the entire company, probably to facilitate interdepartmental communication. The automation of updates is a recurring demand, aiming to ensure the constant availability of up-to-date data. Finally, the organization of regular exchanges with experts to refine the Dashboards is proposed, highlighting the importance of a collaborative approach in the continuous improvement of the tool. [...]
[...] ANNs can learn from historical data to predict potential performance degradations and outages. - Linear and Logistic Regression Algorithms : Used to establish relationships between different KPIs and network events, enabling the prediction of future failures based on the current values of the indicators. - Decision Trees and Random Forests : Used to classify network states and predict incidents based on collected performance data. These algorithms help telecommunications operators transition from a reactive to a proactive approach to network management, thereby reducing downtime and improving overall service quality. [...]
[...] Preliminary studies have shown that the use of real-time performance monitoring dashboards is crucial for the effective management of telecom services. For example, a study conducted by Gartner (2015) demonstrated that companies using real-time monitoring solutions were able to reduce service interruptions by thanks to faster incident detection and resolution. Another study conducted by IDC (2017) showed that real-time dashboards can also help operators optimize their network resource utilization by identifying periods of high and low demand and adjusting capacities accordingly. [...]
[...] - Optimization of performance : Setting up a solution to improve the reactivity of the Dashboard. 5.2.2.2 Progressive Deployment Strategy A progressive deployment strategy has been adopted, with validations at each stage by the churn team. This approach has allowed to adjust the Dashboard based on user feedback and ensure that each phase met the specific needs of the team before moving on to the next one. 5.3.2 Post-Deployment Follow-up 5.3.2.1 Collection of Feedback The collection of feedback was mainly done through regular interactions with the churn team. [...]
