Network Capacity Management and how AI/ML can improve Network Investment Planning

The telecom world as we know it is constantly evolving, with technology innovation and enhancements coming on a regular basis. And today, with mobile technology evolving from 4G/LTE to 5G, there is an evolution in terms of customer experience demand and competition landscape as well. This puts CSPs in a precarious position to deliver the best experience to their consumers while keeping costs low, and competitive advantage intact.

This is where Intelligent Network Capacity Management comes in:

What CSPs need today are network capacity management solutions that can significantly help them enable smart network investment planning to maximize return on network investments.

However, in reality, this is far from as straightforward.

Strategically, CSPs leverage capacity management investments to gain competitive advantage and enhance end-user experience. However, such investments are highly cost intensive, both in terms of Capex and Opex. Any inaccuracies in the overall network investment planning can lead to unintended impacts on company financials and can create significant network inefficiencies.

How do CSPs come up with network investment plans which are accurate, has optimal cost, meets current & future requirements of users and gives competitive advantage over a long term?

In our view, the overall Network Investment Plan has 3 prime enablers which can help CSPs to formulate an efficient and robust Network Capacity Management framework comprising of: Network Capacity Assessment, Network Capacity Planning, Network Capacity Optimization, Network Capex Optimization, and a lot more.

Key Enablers:

  • End to end domain expertise: CSPs with capability to proactively manage end-to-end network would ensure high flexibility, reliability and availability of network service continuity. Deep network domain and service expertise to address broad set of use cases deployment fitting across CSPs key business objectives will ensure superior network and business performance.
  • Strong data management capability: As per GSMA mobile economy report, by 2025 around 130 exabytes of data would be generated every month, four times increase in volume as compared to current data volume, which is around 30 exabytes per month. Seamless handling of such a massive amount of data would ensure CSPs to efficiently extract relevant and meaningful insights at the right time for analysis.
  • Leveraging advanced analytics: Complexity of running a 4G and 5G network with plenty of data points in IoT will make it impossible for human hands for network planning, capacity management, quality optimization and predictive capacity analytics to enhance the customer experience. CSPs leveraging machine learning and deep learning models today will reap significant benefits in their overall network management, an ecosystem comprising of 2G, 3G, 4G and 5G technologies.

The three major enablers are quite significant in today’s digital era and will be extremely crucial in the 5G ecosystem. Delivering extraordinary customer experiences, staying ahead of competition and most importantly being profitable should be part of every CSPs strategy for evolution towards 5G technology.

Predictive network management modules considering the key aspects of digital transformation can help CSPs consolidate current 4G LTE network and plan for 5G network in a most cost-effective way with focus on enhancing the customer experience and maximizing returns on network investments.

Read a case study on how we helped a Tier-I telcos increase their revenues by over 12% through intelligent network investment planning.

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This blog was originally published on Whatech

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