Contributed by Andrew Baldock, Product Marketing Director, Infovista

5G network rollout is creating complexity for operators planning networks and services like never before. Not only are the RF technologies involved in in 5G network roll-outs new; the revenue streams that will pay for them are new too – supported in many cases by as yet untried business models.

Against this backdrop, there’s no room for waste when rolling out, densifying and expanding 5G networks. Planning must not only maximize today’s addressed revenue; it must also be ready to accommodate potential revenue growth.

Whether it’s a greenfield network or an expansion and densification of a live network, operators have long been faced with the need to control CAPEX. But, the fact is that these days the business side of an operator is just as invested in the success of network planning as the technical side. Network performance is increasingly directly connected to revenue, with the increasing prevalence of service level agreements (SLAs). However, the ability to quickly deploy and scale 5G network infrastructure with the highest revenue potential is hindered by legacy siloed processes.

A new agile way of working is needed, combining traditionally separate disciplines.

There needs to be a shift in focus in network planning, from network KPI optimization to business outcomes optimization, and on combining diverse network and business predictions within a single vendor-neutral software application.

Senior stakeholders – including the CTO and CMO organizations – need accurate, predictive views of how their network plans will deliver against the business KPIs, including TCO, additional revenue, churn and ROI. They need to answer questions like how to prioritize the allocation of budget in different geographies so as to capture the larges revenue upside at the lowest cost; or how to target high churn probability hotspots in the network which exist today or will pop-up in the future.

This means data. Data that supports this decision-making must of course include things like the targeted number of sites; download and upload performance; coverage targets; throughput; capacity targets; traffic growth areas, RAN products performance; antenna propagation; latency; interference. The list goes on.

But it’s not enough to just understand the physical network, it’s vital that the teams can understand how the network is being used – the end-users’ experience. The population density in different areas, the dwell time around different cell sites, what kinds of content users consume, even the price plans the customers are on, can be useful for planners. That means live performance management (PM) traffic data, crowdsourced data, social media usage, high resolution geodata and geolocated call traces as examples.

Then to round things off, there’s financial data: TCO, cell-level revenue, regional ARPU.

All this is required to enable decision makers to answer questions like: will demand increase over time? To what extent does this vary? Are we missing areas of demand? How sensitive is predicted revenue to capacity availability? What is the optimum trade-off between throughput capacity and customer experience if, say, a certain area experiences heavy social media usage for only a very short time?

In short, operators need to marry together network planning and business outcomes in a systematic way, using advanced analytics to optimize predicted ROI and then quickly act on the information.

Network planning is a learning process. In an environment where more and more data points can be incorporated into planning, it isn’t a task human teams can manage unassisted. Artificial intelligence (AI) and machine learning (ML) have an increasingly important role to play in the automation of complex decision-making.

Our approach – Smart CAPEX – supports engineering and network planning teams to optimize their efforts in radio network evolution planning for densification and expansion including multiple what-if scenarios simulation in a systematic, repeatable, and continuous way. It leverages fully automated business-driven planning algorithms along with rich geospatial views that provide ‘at-a-glance’ information about the current and predicted network performance, areas, and hotspots with poor QoE or capacity bottlenecks. On top of that, the solution automates the design of the network optimized for TCO, revenue and the resulting ROI.

Smart CAPEX enables CSPs to intelligently optimize traffic and revenue potential against deployment costs and then invest where it matters most to increase the return on investment from their networks. It ends the problem of siloes, enabling the senior team right across the organization to work from a single dashboard, modeling prioritized cell site deployments based on their traffic and revenue potential and making smart investments that address the business KPIs.

In short, Smart CAPEX allows 5G operators to effectively and efficiently plan, optimize and model to deliver next generation networks with the maximum return on investment. It then continues to do so through the network’s lifecycle as adjustments and improvements are highlighted, costed, and implemented.

As 5G rolls out, operators will need to apportion costs with more precision, based on their network’s needs and revenue. The result will improve not just the networks of tomorrow, but the ROI they generate.

Register for the 22nd February, Webinar: Smart CapEx investment: Optimizing for RoI featuring C-Level execs from Infovista, BT, Telus, T-Mobile Netherlands, Rakuten Mobile & STL Partners