smart capex solution

Monetizing 5G Networks with Smart CAPEX

Rayan Salha
May. 4 2023

In a research report by TM Forum – Network Lifecycle Automation: Can CSPs optimize 5G investment? – ​t​he author surveys over 170 respondents from 93 leading global CSPs, essentially to gauge their experiences with delivering on the business case for 5G (which as we all know, has been transformative, on paper at least). But like all new innovations, some of the building blocks for the practical delivery of the 5G networks that were to catalyze the revenue growth assumed in said business case, were presupposed. The magnitude of the change needed to enable the characteristics necessary to support high-revenue services delivery was not fully appreciated.  

That’s why the majority of those surveyed in 2022, in some cases a full 2 years since the 5G deployments were initiated, believe they spent too much, the result wasn’t optimal, and it took too long. Benefits were achieved but not to the extent that was prophesized by, admittedly much of the time, the vendors selling the 5G equipment itself.  

It’s clear a large majority of the upside of 5G remains on the table, and for the most part, we are left with a faster network. More cost-efficient per MB delivered maybe, but just faster.  

That leaves the other two elements of the 5G value proposition unfulfilled: Latency and connection density (URLLC and MMTC respectively). There are two absolutely fundamental aspects about the way that CSPs roll out and operate 5G networks that need to change to resolve this issue: Planning has to be razor-sharp in accuracy and timeliness, and operations has to be up to the challenge of delivering not just speed and reliability, but other business KPIs including latency and connection density.  

These challenges are addressed with Infovista’s  Smart CAPEX, and 360° Assurance use cases, powered by Network Lifecycle Automation (NLA)

​​​How can CSPs address the cost-inefficiencies experienced with their 5G deployments?​​ 

Respondents to the TM Forum survey were in agreement. Smart CAPEX, with 63% of the vote, is the most popular capability for enabling CSPs to address the cost-inefficiencies experienced with their 5G deployments so far. 45% of respondents expect an improvement in customer experience and NPS as the top business outcome of ​Network Lifecycle Automation (NLA), and 360° Assurance is critical to earning that ‘carrier-grade’ label (as distinct from services provided by OTT players). This is unsurprising because it's critical to success for the higher value services that combine high speed, low latency and high connection density (like e-gaming or sports broadcasting).  

​​​How can Smart CAPEX help?​​ 

Smart CAPEX represent a departure from the planning and operations approaches used to date to a unified, customer-centric and business-driven one, delivering a scalable entry point into the more profitable revenue streams unlocked by the more advanced features native to 5G networks.  

Telco is a capital-intensive industry. According to NYU Stern, in the US as of January 2022, CAPEX to total sales for telecom equipment and services was 9% and 5% respectively. That compares to an average across industries of around 3.5%. So it’s no surprise that improving CAPEX efficiency is a top priority for the telco.  

What’s the challenge of CAPEX today for the mobile operator deploying 5G, versus previous technologies?  

It isn’t as simple as saying that higher spectrum frequencies equal shorter range, equals more equipment, equals higher CAPEX. The challenge is more about the complexity that comes from greater choice.  

The equipment providers have been innovating with cost in mind, reducing the cost of the equipment that makes up the BTS itself and the supporting backhaul and fronthaul (X-haul); offering smaller form-factors and devices that are small and light enough to be installed by a single engineer, for example. Step forward technologies like MIMO, and beamforming, power efficiency, component centralization and virtualization (the CU versus the DU), silicon that requires less cooling. These are just some examples of downward pressure on prices for RAN roll-outs.  

The challenge is now one of complexity.  

5G has made it possible to very precisely deliver mobile connectivity that delivers very specific performance criteria. This can be done for instance by using small cell-based networks in densely populated areas like transport hubs or business districts, with large form factor networks providing broader coverage at lower cost in residential areas, where more of the consumer’s connectivity is provided by fixed or Wi-Fi networks.  

Beyond this complexity of choice and highly localized roll-out challenge, 5G is also a lot more dynamic than previous RAN technologies, for the same underlying technical reasons. Densifying a 5G RAN where more capacity is needed is simpler and faster because of smaller form factors and component centralization. This opens up more options for locating new radio antennas (like lampposts or smaller commercial buildings).  

So, to support the challenge of dynamicity, it’s necessary to have insight and intelligence into how the conditions of the mobile connectivity provided in a given location influence the way the connectivity is used.  

A simple example is churn sensitivity to QoE. Where we see a high correlation between perceived QoE and churn, we could have a strong business case for expanding capacity to improve QoE and thus reduce churn. But we need to respond quickly, and the planning needs to be highly precise and based on an accurate understanding of how RAN expansion or densification will impact QoE.  

This is precisely why when we implement ​Network Lifecycle Automation (NLA)​, it is done with business outcomes in mind. Otherwise, we cannot easily use all of the underlying capabilities that drive successful use cases. ​These include​ multi-domain machine learning algorithms that can identify the correlation between RAN performance, perceived QoE, and business outcomes like churn, NPS and revenue, or detailed geospatial visualization tools that show the expected outcomes of CAPEX investments under different scenarios.  

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