The increasing complexity of networking environments
Network managers face the challenge of managing call quality in increasingly complex networking environments. The telecoms industry has undergone a fundamental transformation with the decline of traditional landlines and the rapid evolution of technologies. Smart devices, Voice over Internet Protocol (VoIP), the Internet of Things (IoT), 5G, and cloud communications offer new ways for people to talk. In parallel, modern enterprise networks have evolved from being mainly hardware-driven. Networks are now a software-driven fusion of virtual and physical networks. Network managers now have sophisticated control of their networks. They need to carefully manage telephone voice quality and other real-time traffic to ensure a positive customer experience.
Connectivity is now a basic need and call quality remains important
We live in a data-driven era. Our inexhaustible demand for data is driving changes in the way enterprises manage their infrastructure. Connectivity is now a basic need. Not only do we not tolerate down-time, but we have an expectation of consistent fast bandwidth and low latency. With keen competition in the market, customer experience management is now a vital focus for telecoms and unified communications providers. Call quality remains a priority. Voice is still a dominant customer communication channel.
Growing from reactive, to proactive, to cognitive
IBM describes the increasing maturity level of operational support as growing from reactive, to proactive, to cognitive 1. A reactive approach to managing network operations was common in the past. In response to reports of an issue, support teams mobilized. The analysis and troubleshooting only began after the service delivery impact. The focus was purely on restoring service. Insufficient time was available to investigate and determine the cause of the problem. Monitoring tools have enabled operations centers to become more proactive. Using key performance indicators (KPI), performance measurement helps to predict problems, limiting or avoiding service impact. The evolution of cognitive networking takes things a step further.
Leveraging Artificial Intelligence
Cognitive networking involves the application of artificial intelligence and automation to network operations and network service virtualization. Two key focuses are network optimization and preventative maintenance. Cognitive networks apply sophisticated algorithms to a vast array of historical data. They use machine-learning techniques to anticipate future issues and automate the optimization of the network. Over time, cognitive networks can learn to anticipate issues, propose solutions to support technicians, and even automatically apply fixes before any degradation in service.
Voice traffic is particularly sensitive to degradations in service. This is because conversations happen in real-time. Corrective adjustments that were originally made in a reactive mode, such as gain adjustment, buffer size adjustment, Quality of Service (QoS) priority setting, and route selection, can now be done in a preventive mode with advanced monitoring. In cognitive mode, a self-regulating network will respond to changing demand patterns by making these types of adjustments automatically in real-time. This enables better telephone call quality and better conversations based on machine learning and AI responses.
Will cognitive networks eliminate the need for monitoring tools?
No. Monitoring tools are still vital for measuring performance and detecting changes over time. Cognitive network solutions need to understand the network conditions. They rely on the historical data and alerts generated by monitoring tools. The key benefit is that cognitive computing can turn data into knowledge by leveraging data from different sources. This data helps to identify patterns and correlations. Over time, expertise is developed. It all begins with the data. Access to good quality, insightful data is crucial.
Conclusion
Faced with managing complex networks under intense demand from consumers, network managers are on a journey moving from reactive, to proactive, to cognitive management of their infrastructure. In the future, the application of cognitive computing could help providers achieve zero downtime and consistent quality of service for consumers. But, effective monitoring tools will still be required to create the vital knowledge-base for machine learning and decision-making processes.
Use Spearline as part of your armory in the transition to cognitive management of your network. Spearline gathers vital call quality data about connection success, audio quality, post dial delay (PDD), touch tone (DTMF) success, and latency. Our comprehensive call records enable you to form a complete picture of the performance history of your contact numbers. Our analytics facilitate the identification and root cause analysis of issues, and our reports allow you to benchmark the performance of your telecoms network. Spearline can give you the crucial insights you need not only to proactively manage your network but also to accelerate improvements in your customer experience.
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About us
Spearline is the leading network intelligence company in the telecommunications industry. Our platform enables enterprises and telecommunications service providers to test connectivity and quality on global telecoms networks, testing automatically at volume. If you are interested in our platform or would like more information, please get in touch with us.
1 Cognitive Network and Service Operations, IBM Telecommunications, Media and Entertainment
