Open platforms are critical to operators’ sustainability goals

Telecoms operators are under unprecedented pressure to reduce their energy consumption and greenhouse gas (GHG) emissions, in order to achieve demanding targets for operating cost reduction and sustainability.

Sustainability strategies are multi-faceted and involve every part of the organisation, but energy efficiency in network and IT infrastructure plays a vital role. Networks and data centres account for around 85% of a Tier-1 operator’s Scope 1 and 2 emissions and energy costs, and while modern technologies, such as 5G radios, are more energy-efficient than older systems, rising volumes of data traffic, together with increasing density of networks and edge data centres, will cancel out those gains if operators do not adopt radical new measures to understand and manage energy consumption and emissions.

Many operators have set ambitious sustainability targets and have begun to implement efficiency measures in networks and IT. However, so far, many have been physical measures such as decommissioning legacy networks, or have addressed just one network domain, such as the RAN. To maximise the impact of energy-efficiency strategies, it is critical that operators adopt digital strategies that harness open cloud-based platforms and advanced data analytics enabled by artificial intelligence (AI) and deep learning. Such platforms can support a wide range of applications to monitor, manage and predict energy use across an operator’s networks and IT infrastructure, providing a holistic and proactive approach to energy efficiency.

Operators are increasingly aware of the need for open, cloud-based and multi-domain platforms if they are to hit their efficiency targets. In a recent survey of 62 Tier-1 operators, conducted by Analysys Mason, 35% said that AI-enhanced power management tools were one of their two top priorities for energy efficiency, and 31% said the same about cloud-based traffic management. However, there are still barriers to adoption of these new digital strategies. The most important relate to the siloed approach of most current systems. Almost 40% of the survey respondents, for instance, said that a lack of consistent data and analytics across multiple network and IT domains was a barrier to adoption, and therefore to achieving optimal energy-efficiency.

As their energy pressures intensify, operators are working with ecosystem partners to establish the requirements for a next-generation, cloud-based energy management platform that will maximise the effects of using tools such as AI and machine-learning (ML). The six key requirements identified by the operators in the survey are:

• an open cloud-based platform that maximises responsiveness and allows operators to access a broad base of innovations
• a holistic approach to energy management spanning all networks and IT
• a flexible cloud-based approach to software, that allows updates and actions to be implemented quickly and consistently
• a system that delivers sizeable results so that energy impacts can be assessed rapidly and accurately
• a system that provides clear data on network performance and how that may be affected by energy-efficiency measures, so that trade-offs can be minimised.

A fully open cloud platform, as opposed to a closed telco or vendor cloud, increases the impact of a holistic energy management system on all these operator KPIs, according to over 75% of operators, and facilitates the introduction of AI as new tools emerge. 

It is important for operators to adopt a future-proofed strategy. An open cloud platform allows them to implement immediate measures that will deliver some benefits now, and expand the range of tools as new solutions emerge from the ecosystem. For instance, many operators have already cloudified their packet core, but will wait a few years before virtualising the RAN. If they implement the RAN on the existing open cloud platform, the impact of energy efficiency systems will be further amplified. 

In order to win board-level support, it is crucial for operators to be able to quantify the benefits they will achieve from their new digital energy strategies. Some early adopters are starting to share their results, and the impact will only be increased as tools mature and, in the case of AI/ML, as operators amass more data over a longer period of time to support learning models. 

Analysys Mason’s survey identified 12 operators that had invested sufficiently in cloud-based energy management platforms to be able to provide some early quantitative findings. On average, they had achieved energy savings of 29% in networks and IT from these platforms and digital tools, combined with new power sources such as renewables, typically over a 3-year period. The most dramatic improvements were derived from implementing holistic cloud-based energy monitoring, to replace previous siloed data systems; and from moving from static to dynamic power control systems, including near-real time decisions on base station sleep/wake. Some of the improvements reported included a 52% improvement in energy data visibility, and an 18% reduction in network power cost as a direct result of AI.

As more operators start to invest in similar projects and to measure the impact, there will be an acceleration of adoption as confidence grows and the ecosystem broadens. This will be vital if the industry is to reduce energy consumption and emissions, challenges that will only become more business-critical as the decade progresses.