5G for business: An update on telco pioneers

SK Telecom, Verizon and Telstra have looked to expand their 5G networks and to provide businesses with more opportunities to take advantage of 5G. But new developments have not been ground-breaking and adoption of 5G, while growing, is off a low base.

Changes in 5G business propositions

Last year we published a three-part series taking an in-depth look at how early adopters SK Telecom, Verizon, and Telstra had evolved their approaches to 5G commercialisation since launch. This article will focus specifically on how they have grown their 5G business and enterprise propositions since the publication of those reports.

Each of the three operators has pursued a slightly different 5G strategy, reflected in the way they have enhanced their offering of 5G for business over the course of 12 months. SK Telecom has continued to promote its 5G cloud offerings and to develop its 5G-enabled smart factory solutions. Verizon has looked to expand its network coverage by adding mid-band (C-band) 5G to its spectrum ranges and is also emphasising MEC solutions. While Telstra continues to promote 5G as a part of its ‘advanced network’ foundation (though there is evidence that 5G, specifically, is enabling Telstra to broaden its solution portfolio, e.g. it has launched a new on-premise dedicated 5G network for business).

SK Telecom

Enterprise is one of five “business groups” that SKT has recently prioritised to “maximise corporate value” (drive revenues). Specific SKT Enterprise Group plans include:

  • To build data centre capacity, with integrated MECs at new sites.
  • To leverage 5G MEC, AI technology and hyperscaler collaboration to grow the cloud business (it will make equity investments to expand this internationally).
  • To extend services in select verticals – Smart Factory, Finance and Security – combining its own AI technology and its digital infrastructure (5G, Cloud and IoT).
  • Its commercial 5G offerings available on the market broadly reflect these priorities.

5G cloud products

SKT continues to promote “5GX Cloud” as the lead 5G solution area on its website. Its suite of solutions includes 5GX Public Edge (leveraging hyperscaler partnerships) and 5GX On-Site Edge (a private MEC environment for companies that require extra secure real-time data processing or cost-efficient high-capacity data transfers). 5G and MEC are explicit as the foundations for these propositions.

Recently, SKT has teamed up with Dell Technologies to launch an enterprise 5G MEC solution called “Petasus”. It combines SKT’s 5G MEC solution and Dell PowerEdge servers. The solution provides network virtualisation features designed specifically for MEC, as well as associated operational tools. SKT promotes MEC as an essential technology for application areas such as smart factories and autonomous driving (due to its ability to enable ultra-low latency communication).

5G vertical services

SKT has been building a portfolio of offerings under the 5GX Smart Factory banner. Since the previous report it has added the following solutions:

  • TV live caster: A 5G-enabled HD video control solution capturing feeds from smartphones, drones and cameras. It can be used for safety management, remote tech support and live broadcasting from public and industrial sites.
  • Die-Casting Manager: A service for die-casting facilities where thermal monitoring equipment is used to monitor operations for early problem detection and optimisation of production conditions.
  • Welding Quality Inspection Manager: A solution leveraging Acoustic Emission (AE) sensors, Machine Vision cameras and AI to determine not only external welding defects but also internal problems with industry-leading accuracy. This enables enterprise customers to reduce costs, increase work efficiency and maintain high production quality.
  • Machine Vision Solutions: Quality inspection solutions using 5G, AI and MEC tech to detect defects in the appearance of a product using AI-trained models and take appropriate action on the production line based on the results.

Figure 1: SKT Machine Vision Solution

5G business

Source: SK Telecom

Corporate actions regarding the finance and security verticals appear less 5G-inclusive at this stage. While it is leveraging AI with Kookmin Bank in the finance vertical, there does not appear to be a role for 5G in this space yet. SKT announced its intentions to become the market-leading “ICT-based convergence security specialist in Korea” in 2021 when its SK Infosec entity merged with ADT Caps. It plans to “create a safer society and lead the future security industry by combining 5G, AI and Big Data analysis technologies with convergence security and quantum cryptography technology”. STL will be watching this space.


Over the last year, Verizon’s approach to commercialising 5G for business appears to have progressed. It has been building out its network and seems to be focusing on two main areas for monetisation: fixed wireless access and 5G Edge. It also promotes 5G’s suitability for public/ emergency services provision, though specific solutions are not evident.

5G mid-band

The most significant development that has taken place for Verizon has been the addition of mid-band (C-band) 5G to the spectrum ranges that make up its 5G Ultra Wideband (UWB) proposition. Verizon launched 5G on mmWave spectrum due to its promise of high speeds and low latency, but quickly came in for criticism as it was difficult to secure coverage given that mmWave network signals struggled to negotiate buildings and other infrastructure. This significantly limited 5G adoption.

Mid-band spectrum has become the entry point for most 5G implementations since Verizon’s launch as it offers speed and latency performance improvements over 4G, whilst being easier to propagate. Verizon’s mid-band purchase is intended to address the problems with Verizon’s UWB and expand 5G coverage.

The mid-band spectrum has been deployed more quickly than anticipated. By January 2022, Verizon announced that 100 million people were covered by its 5G UWB. It is expecting that 175 million people will be covered by the end of 2022 – a year ahead of schedule.

Figure 2:  Verizon 5G coverage map May 2022

5G business

Source: Verizon


Verizon is currently promoting a 5G UWB fixed wireless solution as an alternative to fixed line business broadband. Its extended UWB footprint has increased its addressable market. It is trying to win market share from fixed line players with a commitment to keep its pricing unchanged for 10 years.

5G Edge

5G Edge is a focus for Verizon (the cloud opportunity appears more closely scoped than at SK Telecom). There are two variants of 5G Edge services: Public and Private MEC.

Public MEC

Verizon has expanded its 5G Edge Public MEC (Multi-Access Edge Computing) capabilities over the last year. Public MEC leverages AWS Wavelength and brings AWS compute and storage services to the edge of Verizon’s wireless network. In August 2021 it was available in 10 locations across the US and, as of January 2022, it was available in 17 locations.

Verizon provides examples of how businesses are utilising 5G Edge Public MEC to demonstrate how it can be used and to promote uptake. For example, Aetho (the company behind Beame AR telepresence solutions) is using Verizon 5G Edge with AWS Wavelength to offer students and prospects of Morehouse College virtual tours of its campus and remote learning tools. It is unclear how many companies are taking advantage of 5G Edge Public MEC, and how accessible it is to the average company.

Private MEC

Verizon has added to its Private MEC offerings since STL’s report was published in April 2021. On 31st August 2021, Verizon announced it was offering businesses an on-premise private edge compute solution that enabled ultra-low latency and allowed real-time enterprise applications.

5G vertical services

One vertical that Verizon is focusing on is the Public Sector. Specifically, it appears to be concentrating on 5G-enabled solutions for first responders. Developments are underway in the 5G First Responder Lab, a collaboration between Verizon and ResponderXLabs. Verizon says that its 5G UWB will support a range of next generation capabilities for public safety, including; real time intelligence, critical training preparedness, next-generation communications, remote asset operations and augmented reality (AR) on-the-job support.

Verizon has recently formalised its strategy to target stadium and venue customers with 5G enabled solutions to enhance the fan experience and public safety. It has started to promote a Crowd Analytics solution (which uses Public MEC capabilities) to enable better customer experience at venues and stadiums, for example analysing guest traffic to help reduce waiting times in key areas. This is likely to be a B2B play, where the services are provided by the telco to the event organiser/ broadcaster. The strategy leverages Verizon’s private 5G technology and supports its private networks, mobile edge compute and business solutions vectors of growth.

A further vertical service is Verizon’s 5G Edge Automated Guided Vehicles Management solution. This is designed to facilitate robotic fleet management for customers such as manufacturers and warehouse and logistics operators. It leverages on site 5G connectivity (private 5G network) and private mobile edge computing (the MEC is at the company location).


Telstra’s approach to 5G for business remains to position it as part of Telstra’s “integrated solution stack based on network foundations”. In general, 5G is not singled out as a prominent component of any offering, but it is listed as an option for those businesses with specific requirements. For example, Telstra’s Adaptive Mobility connectivity plans are marketed as 5G-compatible, with “add-ons” like the Adaptive Mobility Accelerator leveraging 5G if the device and coverage allow, though it is not 5G-dependent. There is no change in this regard since last year’s report.


Telstra promotes its Enterprise Wireless offering as bringing together “our investment in our 5G network rolling out in selected areas, simplified mobility plans, enterprise grade endpoints and managed services.” It has introduced an Enhanced Enterprise Wireless version of the service, which includes service level agreements and managed services, allowing the customer to connect to “dedicated enhanced infrastructure”. This Enhanced version is one of the few examples where a service is 5G-dependent.

Figure 3: Enhanced Enterprise Wireless

5G business

Source: Telstra

Private 5G for business

Telstra has begun offering a “dedicated private network” solution. In January 2022, Telstra and Ericsson announced the first deployment of an on-premise dedicated 5G network for business that leverages its “single-server dual mode core”. The core facilitates both LTE and 5G Standalone (SA) simultaneously, which means that 5G SA capabilities can be accessed to offer a “wireless connectivity platform for enterprise than can deliver low latency, enhanced resilience and the capacity to meet even the most demanding business operation requirements” when relevant devices are available. This should bring the full benefits of 5G for business to fruition.

5G edge

Telstra does not emphasize 5G in its cloud propositions, though it is mentioned as a connectivity option. It is also mentioned in connection with multi-access edge computing solutions.

  • Telstra has started trials of Australia’s first 5G-enabled edge compute solution for businesses, in collaboration with Ericsson. The solution is being explored in the Telstra Retail store environment, where a smart video solution is issued to simplify operations and enhance customer experience.

Telstra promotes its ability to tailor cloud offerings through its “technology services”/consulting entity, Telstra Purple. This may result in an increased consideration/inclusion of 5G as part of a cloud solution.

Conclusions: Incremental changes are evident, with MEC initiatives dominating

The portfolios of early adopters of 5G have not been radically revised over the course of the year or so, but they have each looked to improve their 5G business offerings. The improvements they have made have largely been in line with their initial 5G strategies. SK telecom has expanded its range of technologically advanced 5G solutions to address specific use cases. Verizon has looked to redress T-Mobile’s dominance in terms of 5G network coverage. Telstra has positioned itself as capable of addressing customer’s unique needs through its deployment of flexible technology solutions that can be tailored to enterprise needs.

Figure 4: How telcos are commercialising 5G for business

5G business

Source: STL Partners

One area that has seen significant developments is MEC. All three operators have expanded their MEC offerings and have clearly identified this as an important source of revenue in years to come. 5G-includive vertical solutions have become more prominent over the last 12 months, further contributing to 5G monetisation. Operators are also focusing on developing and monetising their private network solutions, which is something we will continue to follow closely.

Telcos see private cellular and edge as two peas in a pod

Telecoms operators see private cellular and edge computing as part of a larger revenue opportunity beyond fixed and public cellular. It is an opportunity for telcos to move from being seen as horizontal players providing increasingly commoditised connectivity services, to more vertical players that address value-adding industry-specific use cases. Private cellular and edge compute can be seen as components of a wider innovative and holistic end-to-end solution for enterprises, and part of the telcos’ ambition to become strategic partners or trusted advisors to customers.

We define a private cellular network as a dedicated local on-premises network, designed to cover a geographically-constrained area or site such as a production plant, a warehouse or a mine. It uses dedicated spectrum, which can be owned by the enterprise or leased from a telco operator or third party, and has dedicated operating functions that can run on the enterprise’s own dedicated or shared edge compute infrastructure. Private cellular networking is expected to play a key role in future wireless technology for enterprise on-premises connectivity. Private cellular networks can be configured specifically to an individual enterprise’s requirements to meet certain needs around reliability, throughput, latency etc. to enable vertical-specific use cases in a combined way that other alternatives have struggled to before. Although there are early instances of private networks going back to 2G GSM-R in the railway sector, for the purpose of this report, we focus on private cellular networks that leverage 4G LTE (Long Term Evolution) or 5G mobile technology.

Private cellular combines the benefits of fixed and wireless in a tailored way

private cellular and edge

Edge compute is about bringing the compute, storage and processing capabilities and power of cloud closer to the end-user or end-device (i.e. the source of data) by locating workloads on distributed physical infrastructure. It combines the key benefits of local compute, such as low latency, data localisation and reduced backhaul costs, with the benefits of cloud compute, namely scalability, flexibility, and cloud native operating models.

For more information about the video analytics opportunity at the edge, check our report Scaling private cellular and edge: How to avoid POC and pilot purgatory

Video analytics is a large and growing market

Video analytics is the processing and analysis of visual data (images or videos). When artificial intelligence is used to extract information from the data, it is referred to as intelligent video analytics or computer vision, although video analytics is often still used as a shorthand.

Video analytics stands out as a huge opportunity. It has the potential to be a killer application for edge computing, due to:

  • The large and growing market – In 2021 there were an estimated one billion surveillance cameras operational around the world. With the number of cameras predicted to grow by 20% in the period 2017-2024, AI and analytics will become increasingly important to capture value from the wealth of video footage being collected each day.
  • The ability for edge computing to grow the market – Without edge computing, video analytics is hindered by challenges with data sovereignty, and the cost of sending high-bandwidth data to the cloud (a problem that is heightened as video streams increase in quality). Edge computing therefore plays a key role in enabling video analytics, including more advanced AI/ML-enabled analytics, in a cost-effective way.
  • Its relevance to almost all industries – Video analytics can address a wide variety of use cases, from understanding consumer habits in retail, to analysing how football players kick a ball. In the case of video analytics for security, it is relevant across virtually all industries – education, transport, manufacturing, the list goes on.

The market for edge-enabled video analytics will be worth $75bn by 2030

Video analytics is a huge application for private 5G and edge computing, accounting for a quarter of edge revenues in 2021 (topped only by cloud gaming). In 2021 the edge-enabled video analytics market was worth over $5 billion globally. This is predicted to grow to $75 billion by 2030 at a CAGR of 34%.

video analytics

There are many application areas for video analytics, of which three are shown in the figure above. Of the three, video ingest and analysis for security and surveillance is the biggest short-term opportunity, representing an estimated 21% of the total edge computing market in 2021. This is due to the large base of installed security cameras that already exists, to which video analytics solutions can easily be retrofitted.

However, by 2030, video analytics for production and maintenance will be a larger opportunity. This will grow throughout the decade along with the move to Industry 4.0 and increase in automation resulting in an increase in sensors and analytics. Verticals like manufacturing, oil and gas and logistics will therefore be key adopters of this use case.

For more information about the video analytics opportunity at the edge, check our report How video analytics can kickstart the edge opportunity for telcos and STL Partners – Edge computing market sizing forecast

Telco edge computing data centres: 3 approach factors

Telecoms operators want to build their network edges where there is demand. In other words, where there is a sufficient number of end-users or customers that will benefit from the capabilities that come with edge.

In general, the approach has been to create a plan for a network of edge data centres that guarantees a maximum level of latency for a certain level of population coverage. In interviews with operators, this has often ranged from 90-99% of the population experiencing sub-10 to 20 millisecond roundtrip latency for applications hosted at their network edge.

The resultant number of edge data centres will therefore be impacted by the spread of the population, the size of the country and the telecoms operator’s network topology. For example, in well connected, small countries, such as the Netherlands, low latencies are already achievable.

The actual number of sites and speed at which a telecoms operator deploys these sites is driven by three main factors:

  1. Edge computing strategy;
  2. The speed at which it has or will deploy 5G (if it is a mobile operator);
  3. The country’s geographic profile.

3 key factors determining a telco’s approach and timing for its edge computing data centres 

Source: STL Partners

STL Partners’s forecasting capacity of network edge computing 2021 to 2025 details a forecast of the capacity available for non-network applications at the network edge over the next five years. Network edge capacity is forecast to build slowly reach an inflection point in 202X and although edge does not need 5G, it is certainly helping drive the market. Telecoms operators also see hyperscalers as key partners in helping to bringing compute and storage to the edge.

There is much debate in the industry on the topic of telco edge computing, but little clarity for players within the telecoms industry and potential customers on how much capacity will be available.

STL Partners Edge Insight Service

The edge computing market is an ever-evolving space. This coupled with the parallel changes in the telecoms ecosystem make it an exciting space to watch. STL Partners will continue to update this forecast with the latest information on telcos’ network edge deployments. Future versions of the forecast will include:

  • New application domains: RAN network functions
  • Network edge data centres provided by non-telcos

Outside of this forecast, STL Partners is adding to its Edge Insights Service, ensuring we publish reports on key topics and incorporate insights through our tools (see an overview of the service below). If you have any questions you would like to discuss with us, or any suggestions for what we should be covering, please contact the lead analyst on edge computing, Ahmed Ali (ahmed.ali@stlpartners.com).

STL Partners’ Edge Insights Service

Source: STL Partners

STL Partners telco edge computing coverage

Edge computing forecast 2020-2030: 20 use cases

STL Partners has developed extensive expertise in edge computing, working with telcos and tech companies to identify their strategies and select suitable use cases.

Based on our industry knowledge, we have developed an Edge computing market forecast model to estimate the size of the edge computing market over the next 10 years (2020-2030) in terms of revenue, broken down for the entire value chain: what we call total edge computing addressable revenue. Our analysis provides country-level revenue forecasts for 186 countries, 7 regions and the world. STL Partners analysed the demand for edge computing from 20 main use cases and the projected spend over the next 10 years.

These 20 use cases are listed below with In-hospital patient monitoring displayed for illustrative purposes. Our assumptions for high-income countries show how application processing will migrate from its current locations (mainly on-device and cloud) to edge infrastructure (on-prem and network edge) during the forecast period.

The use cases that represent the biggest opportunities in 2030 are edge CDN, cloud gaming, connected car driver assistance, video ingest & analysis for production and maintenance, and edge application delivery network (ADN).

You can access STL Partner’s country-level revenue forecast and 20 uses cases in our December 2021 report Edge computing market sizing forecast

  1. Advanced predictive maintenance
  2. AR/VR for training
  3. Automated guided vehicles
  4. Cloud gaming
  5. Connected car driver assistance
  6. Contextual DOOH advertising
  7. Drone inspection and navigation
  8. Edge ADN (Application Delivery Network) & web content optimisation
  9. Edge CDN
  10. Flow analysis – video ingest and analytics
  11. In-hospital patient monitoring……..(see use case graphic below)
  12. Live video/broadcast
  13. MR for working safety & productivity
  14. Production & maintenance – video ingest and analytics
  15. Real-time collaboration in design and engineering
  16. Real-time precision monitoring and control
  17. Remote monitoring and care
  18. Security – video ingest and analytics
  19. Smart city traffic management
  20. Temporary compute for events

Edge computing forecast model and use case

Source: STL Partners

Additional resources

STL Partner’s Edge Insights Service offers extensive reports and articles as well as our Edge Computing Use Case Directory and our Edge Computing Ecosystem Tool


CSPs in Asia Pacific are generally more favourable to having converged edge infrastructure

The original concept for edge computing in the telecoms sector stemmed from network virtualisation efforts. CSPs were building distributed data centre-like facilities to support their network function infrastructure and consolidating network functions onto server infrastructure in place of functional hardware appliances. This meant there was spare capacity in those facilities to support customer applications and maximise economies of scale by sharing as much of the infrastructure as possible.

However, reality has diverged from the theory. The requirements for network functions are different to that of IoT/IT/business applications that will be hosted at the edge. Network teams have arguably stricter security rules for controlling data and access and the type of hardware for network functions is different than that needed for enterprise applications. For example, radio access network functions need specialised hardware, such as field programmable gateways (FPGAs) and hardware accelerators. By contrast, video analytics, gaming or AI-intensive applications may need GPUs and other technologies for enhancing graphics processing.

Despite these limitations, there are different elements of the stack that can be shared between network functions and consumer/enterprise applications, beyond the site itself. Our survey demonstrated that there is a wide range of opinions in the telecoms industry on the level of convergence. Only 12% of respondents globally believe that edge infrastructure should be entirely converged (facility, hardware, application platforms and orchestration). On the other side of the spectrum, 13% of respondents feel that the infrastructure should be entirely separate and only the site itself should be shared. However, there are slight differences across regions.

CSP respondents in North America were least supportive of having completely converged infrastructure, whereas Asia Pacific operators prefer convergence. One of the reasons for this is organisational dynamics, which will be explored in the next section. Another reason could be the level of maturity of the operator’s edge strategy; CSPs in North America and Europe have gone through a process of initially attempting to share the infrastructure and operating models, but have since found it to be too challenging to manage each domain’s different needs. As a result, most CSPs in those regions prefer a degree of separation in the hardware and software stacks.

Find more about the findings of our survey and why edge infrastructure will be multi-cloud in our report Building telco edge: Why multi-cloud will dominate

STL Basics: Edge computing types

As edge computing technologies and definitions are still evolving, different terms are sometimes used interchangeably or have been associated with a certain type of stakeholder. For example, mobile edge computing is often used within the mobile network context and has evolved into multi-access edge computing (MEC) – adopted by the European Telecommunications Standards Institute (ETSI) – to include fixed and converged network edge computing scenarios. Fog computing is also often compared to edge computing; the former includes running intelligence on the end-device and is more IoT focused.

These are some of the key terms that need to be identified when discussing edge computing:

  • Network edge refers to edge compute locations that are at sites or points of presence (PoPs) owned by a telecoms operator, for example at a central office in the mobile network or at an ISP’s node.
  • Telco edge computing is mainly defined as distributed compute managed by a telco operator. This includes running workloads on customer premises equipment (CPE) at customers’ sites as well as locations within the operator network such as base stations, central offices and other aggregation points on access and/or core network. One of the reasons for caching and processing data closer to the customer data centres is that it allows both the operators and their customers to enjoy the benefit of reduced backhaul traffic and costs.
  • On-premise edge computing refers to the computing resources that are residing at the customer side, e.g. in a gateway on-site, an on-premises data centre, etc. As a result, customers retain their sensitive data on-premise and enjoy other flexibility and elasticity benefits brought by edge computing.
  • Edge cloud is used to describe the virtualised infrastructure available at the edge. It creates a distributed version of the cloud with some flexibility and scalability at the edge. This flexibility allows it to have the capacity to handle sudden surges in workloads from unplanned activities, unlike static on-premise servers.

See our other in-depth research on telco edge computing and hyperscalers:

Hyperscalers telco edge partnerships: Operators strategies

Although many operators acknowledge the opportunities that edge computing brings to their existing and future network, operators move to the edge remains relatively cautious. The uncertain ROI, as well as the varying requirements for different edge nodes, has not allowed most operators to develop a clear strategy towards their edge computing as they keep waiting for stronger demands to take off and proven use cases to be identified.

However, many tier 1 early adopter operators such as AT&T, Vodafone and SK Telecom have taken several steps to establish their edge computing business and enable the market growth. Their strategies can be summarised in the following points.

  • Deployment: driving synergy between edge computing and other technologies and network structure in the operator roadmap. Edge computing relates to many essential network upgrades such as 5G, open RAN and the migration to the cloud in addition to enterprise services such as IoT and private networks. Understanding the role edge computing plays in enabling and improving these services supports its business case and helps operators to plan in advance the deployment of and investment in edge within its network in accordance with the overall strategy.
  • Platform: exploring platform options from different available partners to select the ones that best meet network and customer requirements. Hyperscaler platforms have become the first choice for many operators recently, but operators’ platform strategies are still evolving as they test and partner with multiple platform providers. Also, the edge standardisation process that many operators are engaged in will impact the platform selection.
  • Partnership: collaboration on a wide scale and with a diverse range of stakeholders. Openness to work with other stakeholders helps raise knowledge, improve prospects and reduce risks for different parties. On one hand, partnerships on stack elements such as the platform, hardware and location can reduce the cost and risk for individual stakeholders. On the other hand, co-creating, testing and deploying use cases with partners and sharing the knowledge among the community can promote overall adoption. Furthermore, collaborating on standards can simplify and accelerate wide-scale deployments.

See our other in-depth research on telco edge computing and hyperscalers:

Edge computing use case: AR/VR gaming and simulation

Use case description

  • Location based AR/VR game play is becoming increasingly popular (e.g. PokemonGO)
  • This requires a lot of data processing for both location awareness and running the virtual reality game, especially for multiplayer gaming where the game needs to know where players are in real time
  • Consumers expect consistent connectivity/ quality of content
  • Likely at the network edge, to enable remote multiplayer gaming, the edge platform would match players who are physically near one another to reduce latency, as well as render the game from the closest server as possible to reduce lag on the VR/AR game

Customer benefits – why edge?

  • Hosting game servers on the edge reduces latency (20 100ms roundtrip) and allows gamers to get the fully intended experience of their multiplayer game. If gamers experience high latency when wearing a VR headset, they may feel sick
  • Edge can also remove some of the compute intensive programs off device and host on the edge, allowing end users to purchase lighter devices decreasing costs

Potential ecosystem partners

  • With edge computing, game developers can develop games without building in constraints for lag/connectivity issues
  • eSports is a growing industry, and being able to offer a high performance solution with edge computing will enable eSports to be played remotely
  • CDN network providers like Qwilt , who have existing relationships and capabilities in this space can help provide service to optimise games
  • AR/VR platforms, such as Unreal , will need to integrate edge computing for this to work

Industry mapping

*AEC: Architecture, engineering and construction

Case study: MobiledgeX

For more information, check our STL Partners’ Edge Insight Service

Five telco B2B edge computing services

Five telco B2B edge computing services: edge-to-cloud networking, private edge infrastructure, network edge platforms, multi-edge & cloud orchestration, vertical solutions

Operators have different strategic ambitions for how edge can play a role in growing their business. Some operators view edge as an opportunity to move up the value chain, and even become a ‘onestop shop’ to meet all customers’ technology needs. Other operators see edge as extending and enhancing their core business of offering network services and are focussed on meeting the increased demands of networks that are growing physically and have more premium requirements (e.g. lower latency). Finally, some operators view edge as providing the opportunity to enter new markets e.g. the developer segment.

We have identified five types of B2B edge services telcos can offer:

  1. Edge-to-cloud networking: Optimising connectivity between devices or premises to edges and clouds seamlessly and securely
  2. Private edge infrastructure: Providing on-premises edge clouds for customers – may be in conjunction with private cellular network
  3. Network edge platforms: IaaS / PaaS-type platforms to allow customers to use (shared) edge cloud resources, plus services to enhance applications
  4. Multi-edge & cloud orchestration: Services to better monitor and manage network and application workloads across edges and clouds (private and public)
  5. Vertical solutions: End-to-end solutions, combining networking, edge computing, applications and services

See our in-depth research on telco edge computing strategies:

Edge computing use case: Advanced predictive maintenance

Use case description

  • Predictive maintenance monitors data from sensors on equipment to ensure it is in good condition and flag pre-emptively if there is a need to repair it, eliminating the need for scheduled maintenance, adding AI to “condition-based monitoring”
  • For this to work effectively, dozens of sensors need to be employed combined with machine learning/AI at the edge to accurately predict the equipment’s condition
  • The benefit of predictive maintenance is that it reduces downtime and increase the return on assets (up to 24%)
  • Gartner predicts that spending on IoT-enabled predictive maintenance will increase to $12.9 billion in 2022 from $3.4 billion in 2018

Customer benefits – why edge?

  • Advanced predictive maintenance requires data from 1000s of sensors to be collected and analysed – a huge amount of data, too expensive to send to a central server
  • Edge computing can also simplify integration with other management systems, e.g. CRM
  • Enterprises in some industries, e.g. manufacturing, are hesitant to use the cloud (data security)

Potential ecosystem partners

  • Device manufacturers – companies are moving towards servitisation and providing maintenance services with the product/device
  • Systems integrators to integrate outcomes of analytics into wider enterprise systems
  • Cloud providers – solutions will move to IoT, therefore connecting to the cloud will becoming increasingly important, as insights need to be shared across multiple parties
  • Maintenance companies who would leverage the analytics output

Industry mapping

*AEC: Architecture, engineering and construction

Case study: Atos

For more information, check our STL Partners’ Edge Use Case Service