What can telcos learn from Silicon Valley?

Silicon Valley: The promise of “Open” Innovation and agile experimentation

Until the early 2000s, Closed Innovation, based on a model of internal, centralised research and development, was the de facto way for companies to protect intellectual property and gain competitive advantage. Latterly, assisted by the tailwinds of increasing connectivity, there has been a shift in mindset towards Open Innovation – sourcing and acquiring external expertise, scanning the environment, and tapping into ideas and input from beyond the four walls of the business. Today, the array of innovation models is varied and ever-expanding: scouting, crowdsourcing, idea competitions, collaborative design and development, spin-outs, corporate ventures, incubators, joint ventures, in- and out-licensing of intellectual property, consortia, innovation platforms and ecosystems to name but a few. Increasingly, this activity is taking place in clusters – auspicious geographic concentrations of interconnected companies and institutions – the most famous of which is Silicon Valley.

Thanks to a unique confluence of assets – the presence of tech giants and leading research universities, an abundance of venture capital and skilled labour, a disruptive culture, and a relatively benign regulatory environment – Silicon Valley is one of the world’s leading hotbeds of innovation.

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Hundreds of organisations of various sizes and industries – even those with plentiful local R&D talent in their home markets – have been drawn to the Valley in the hope of importing outside-in innovation, identifying new products and partners, and harnessing its ecosystem to solve strategic problems. Telcos are no exception: since the early 2000s, telcos’ core businesses have come under increasing pressure from OTT players as well as wider market forces to innovate and grow. Open Innovation is the antithesis of telcos’ traditional, vertically-integrated approach of translating their own R&D efforts into internally-developed products and services, typically tightly linked to their existing customer bases and offerings. Operators are hoping some of the Valley’s magic dust of disruptive thinking and speed of execution will rub off on them.

However, insiders sometimes quip that the Boeing 747s flying out of San Francisco International Airport have “amnesic” properties. The executive groups that typically descend upon the Valley, hoping to learn from its incumbents both large and small, take copious notes and leave fired up about re-energising innovation in their home base. But once back within the corporate environment, the seeds of innovation struggle to germinate and the majority of initiatives fail to generate any substantial return on objectives. There appears to be a degree of cognitive dissonance between the expectation of such engagements, and their impact.

Other approaches to the Valley, from CVCs (Corporate Venture Capital investments in start-ups) to environmental scanning and venture-building, are better established, with hundreds of corporate outposts currently in place. Four major routes to outside-in innovation, with illustrative examples are shown below.

Four major routes to outside-in innovation

Open Innovation

Unfortunately, truly transformational success stories are few and far between (gains tend to be small or incremental in nature) and there is a long tail of failures and missed opportunities.

For STL Partners, this raises a series of questions:

  • What are telcos hoping to learn from Silicon Valley and how are they going about it?
  • What are the challenges they face in implementing and operationalising what they learn?
  • What can they do differently to overcome some of the common pitfalls of Open Innovation to drive more significant successes?

In addition to its own primary and secondary research, STL Partners explored the challenges and opportunities in depth with Jean-Marc Frangos – Executive Fellow at INSEAD, Executive in Residence at the Plug and Play Tech Center, and Advisor to the Telecom Council of Silicon Valley and former Senior VP of BT’s Innovation function. Located in the Bay Area, Jean-Marc benefits from a 360° view of the disruptive technologies, revenue opportunities and shifts in the in the Valley landscape, and advises European and Asian players on how to integrate such innovations into the incumbent telecoms environment.

What are telcos hoping to do in Silicon Valley?

There are currently somewhere between 300 and 500 corporate outposts in Silicon Valley, as varied in their industries, size and depth of operations as they are in their motives, which are not exclusively tech-focused. The majority have a relatively small footprint, such as those acting as an innovation “antenna” or corporate venture capital (CVC) office, although some have established a more structured presence, for example an innovation lab or R&D centre.

Despite the diversity of these outposts, their common goal is to sense and respond to technology shifts, whether they be disruptive opportunities or disruptive threats. Many of these corporations may be struggling to keep pace with innovation in their own industry and are looking to infuse their organisation with a more entrepreneurial mindset and attract creative talent to gain competitive advantage. In the case of telcos, most are already facing disruption while the remainder can see it looming on the horizon.

The key drivers for innovation outposts include:

  • Keeping a finger on the pulse of trends originating in the Valley;
  • Scouting emerging technologies with a view to investment, incubation, acquisition or some form of collaborative partnership and identifying new channels to market, new business models or new people/processes;
  • Acquiring expertise or best practices from outside the organisation that can be internalised (e.g. to evolve the corporate culture) with a view to accelerating the innovation cycle from start-up through Minimum Viable Product (MVP) to initial production.

Table of contents

  • Executive summary
  • Introduction
  • What are telcos hoping to do in Silicon Valley?
    • The dominant innovation outpost models in Silicon Valley
    • What to learn in Silicon Valley: Four levels of learning
    • Increasing acceptance of evolving business models
  • What should telcos do differently?
    • Purpose: Match effort to expectation
    • Whom to learn innovation lessons from in Silicon Valley
    • People: Who goes to the Valley, and who stays home
    • Practices: Dos and don’ts
  • Telco dynamics and challenges
    • Ambidextrous transformation is a hard art to master
    • Two-speed IT puts the brakes on digital culture
    • Capital-intensive infrastructure companies have a bigger turning circle
    • Design thinking must infuse the transmission belt
    • Telcos may struggle to win the battle for tech talent
  • Conclusion
  • Index

Related research

 

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Growing B2B2X: Taking telcos beyond connectivity and 5G

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The telecoms industry is looking to revive growth

Telecoms operators have enjoyed 30 years of strong growth in all major markets. However, the core telecoms industry is showing signs of slowing. Connectivity revenue growth is declining and according to our research, annual growth in mobile operator revenues pre-COVID were converging to 1% across Asia Pacific, North America, and Western Europe. To help reverse this trend, telecoms operators’ have been investing in upgrading networks (fibre, 4G, 5G), enabling them to offer ever-increasing data speeds/plans to gain more customers and at least sustain ARPUs. However, this has resulted in the increasing commoditisation of connectivity as competitors also upgrade their networks. The costs to upgrade networks coupled with reducing margins from commoditisation have made it difficult for operators to invest in new revenue streams beyond core connectivity.

While connectivity remains an essential component in consumer and enterprises’ technology mix, on its own, it no longer solves our most pressing challenges. When the telecoms industry was first founded, over 150 years ago, operators were set up to solve the main challenge of the day, which was overcoming time and distance between people. Starting in the 1990s, alongside the creation of the internet and development of more powerful data networks, today’s global internet players set out to solve the next big challenge – affordable access to information and entertainment. Today, our biggest challenge is the need to make more efficient use of our resources, whether that’s time, assets, knowledge, raw material, etc. Achieving this requires not only connectivity and information, but also a high level of coordination across multiple organisations and systems to get it to the right place, at the right time. We therefore call this the Coordination Age.

Figure 1: New challenges for telecoms in the Coordination AgeThe coordination age overview

Source: STL Partners

In the Coordination Age, ‘things’ – machines, products, buildings, grids, processes – are increasingly connecting with each other as IoT and cloud-based applications become ubiquitous. This is creating an exponential increase in the volume of data available to drive development of advanced analytics and artificial intelligence, which combined with automation can improve productivity and resource efficiency. There are major socioeconomic challenges that society is facing that require better matching of supply and demand, which not only needs real-time communications and information exchange, but also insights and action.

In the Coordination Age, there is unlikely to be a single dominant coordinator for most ecosystems. While telecoms operators may not have all the capabilities and assets to play an important coordination role, especially compared to the Internet giants, they do have the advantage of being regulated and trusted in their local markets. This presents new opportunities for telecom operators in industries with stronger national boundaries. As such, there is a role for telcos to play in other parts of the value chain which will ultimately enable them to unlock new revenue growth (e.g. TELUS Health and Elisa Smart Factory).

New purpose, new role

The Coordination Age has added increased complexity and new B2B2X business model challenges for operators. They are no longer the monopolies of the past, but one of many important players in an increasingly ecosystem-based economy. This requires telcos to take a different approach: one with new purpose, culture, and ways of working. To move beyond purely connecting people and devices to enabling coordination, telcos will need a fundamental shift in vision. Management teams will need to embrace a new corporate purpose aligned with the outcomes their customers are looking for (i.e. greater resource efficiency), and drive this throughout their organisations.

Historically, operators have served all customers – consumers, small and medium-sized enterprises (SMEs), larger enterprises from all verticals and other operators – with a set of horizontal services (voice, messaging, connectivity).  If operators want to move beyond these services, then they will need to develop deep sector expertise. Indeed, telcos are increasingly seeking to play higher up the value chain and leveraging their core assets and capabilities provides an opportunity to do so.

However, in order to drive new revenues beyond connectivity and add value in other parts of the solution stack, telcos need to be able to select their battles carefully because they do not have the scale, expertise or resources to do it all.

Figure 2: Potential telco roles beyond traditional connectivity

Source: STL Partners

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Clearer on the vision, unclear on the execution

Many telcos have a relatively clear idea of where they want to drive new streams of revenue beyond traditional connectivity services. However, they face various technical, strategic and organisational challenges that have inhibited this vision from reaching fruition and have unanswered questions about how they can overcome these. This lack of clarity is further evident by the fact that some telcos have yet to set explicit revenue targets or KPIs for non-connectivity revenue, and those that have set clear quantifiable objectives struggle to define their execution plan or go-to-market strategy. Even operators that have been most successful in building new revenue streams, such as TELUS and Elisa, do not share targets or revenues for their new businesses publicly. This is likely to protect them from short-term demands of most telecoms shareholders, and because, even when profitable, they may not yet be seen as valuable enough to move the needle.

This report focuses not just on telco ambitions in driving B2B2X revenues beyond core connectivity and the different roles they want to play in the value chain, but more importantly on what strategies telcos are adopting to fulfil their ambitions. Within this research, we explore what is required to succeed from both a technological and organisational standpoint. Our findings are based on an interview programme with over 23 operators globally, conducted from June to August 2020. Our participant group spans across different operator types, geographies, and types of roles within the organisation, ensuring we gain insight into a range of unique perspectives.

In this report, we define B2B2X as a business model which supports the dynamic creation and delivery of new services by multiple parties (the Bs) for any type of end-customer (the X), whether they be enterprises or consumers. The complexity of the value chains within B2B2X models requires more openness and flexibility from party providers, given that any provider could be the first or second ‘B’ in the B2B2X acronym. This research is primarily focused on B2B2X strategies for serving enterprise customers.

In essence, our research is focused on answering the following key question: how can operators grow their B2B2X revenues when traditional core connectivity is in decline?

Table of Contents

  • Executive Summary
  • Introduction
    • The telecoms industry is looking to revive growth
    • New purpose, new role
    • Clearer on the vision, unclear on the execution
  • Beyond connectivity, but where to?
    • “Selling the service sandwich”
    • Horizontal play: Being the best application enabler
    • The vertical-specific digital services provider
    • There is no “best” approach: Some will work better for different operators in different situations
    • 5G is a trigger but not the only one
  • Accelerating the shift towards partnerships and ecosystems
    • Some operator ‘ecosystems’ look more like partnerships
    • Not all telcos define ‘ecosystems’ the same way
    • Most telcos focusing on ecosystems want to orchestrate and influence the proposition
    • Many see ecosystems as a key potential route but ecosystems come with new requirements
  • The market is ripe for telco ecosystems
    • The interest in network intelligence is not new but this time is different
    • Telcos can provide unique value by making their networks more accessible
    • But so far, telcos have not fully embraced this vision yet
  • Conclusions and recommendations

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Telco AI: How to organise and partner for maximum success

Not a passing fad: AI is becoming a core capability for telcos

Artificial intelligence (AI) has become a key enabler of the digital transformation journey for service providers in the telecoms industry, providing them with the insights and capabilities they need to be more agile and take a more software-centric approach to their role.

The document was researched and written independently by STL Partners, supported by Nokia. STL’s conclusions are entirely independent and build on ongoing research into the future of telecoms. STL Partners has been writing about telcos’ AI opportunities since 2016, looking first at how AI might improve the customer experience and then at the critical role AI might play in the future of network operations.

In this report, we provide a comprehensive overview of the state of AI in the telecoms industry. Supported by nearly a dozen in-depth interviews plus an online survey of more than 50 leading telcos around the world, we explore where the industry is looking to progress and how it is planning to do so — and identify the strategic and business opportunities that are being enabled by AI.

This report will be followed by a sequel that quantifies some of the business outcomes telcos can expect from specific AI application areas. In the coming months, we will also publish a report discussing how AI technology is evolving and presenting our vision of the telco AI roadmap.

What is artificial intelligence?

Before going any further, it is important to clarify what we mean by “artificial intelligence”. To us, AI is about using computing capabilities to perform tasks traditionally associated with humans (such as inference, planning, anticipation, prediction and learning) in human-like ways (e.g., autonomous, adaptive). Our definition incorporates machine learning (ML), which we define as a subset of AI that focuses on the ability of machines to receive datasets and adapt responses in pursuit of a goal.

These definitions attempt to encapsulate the distinction between AI and other forms of rules-based automation — although we acknowledge that in practice these lines are easily blurred.

Practically speaking, AI sits on a continuum of other related technologies and concepts, which we have covered at length in our previous reports. Figure 1 illustrates this continuum and depicts the stages we expect telcos will have to go through as they to move from manual to automated and then to AI-augmented processes.

Figure 1: Moving toward AI

The progression of AI maturity in four steps

Source: STL Partners

A long-term ambition for many telcos is to reach the orange zone in Figure 1: a state in which their systems and processes run and learn from themselves with human input limited to the setting of desired business goals. Beyond the targeted use of ML in certain applications, however, the industry and society as a whole are far from realising that ambition. It is still unclear what fully autonomous systems in a telco might look like in practice, let alone whether they will ever be achievable.

Today, most telcos are still figuring out how to play in the blue zone. They’re using targeted data analysis to inform largely human-led decision-making processes, or they’ve implemented some fixed-policy automation where machines follow a script written and inputted by a human. This is valuable work, but it is not the focus of this report. Instead, we focus on the middle section of Figure 1: on those fledging opportunities that move beyond rules-based automation and into the realm of ML-supported automation

Cutting through the hype

AI has generated considerable industry noise and media attention — so much so, in fact, that a recent survey of leading telcos awarded AI the title of “most overhyped emerging technology”. We believe this hype originates in a general lack of understanding of what AI is (and is not), as well as unrealistic expectations about what it can do for a business, how quickly it can be deployed, and how much ongoing work will be needed to manage it. While there is consensus that the technology has great potential, many telcos doubt it will deliver everything that has been promised up to now.

For those disillusioned by the hype, it is worth noting the impact of AI is much likelier to be evolutionary than revolutionary. The line between automation and AI is blurred; so, too, is the progression between the two. While AI has the potential to unlock new business opportunities, realising that potential will require patience and long-term investment.

And yet, the truth is that telcos are uniquely positioned to take full advantage of AI technology — largely because they’re already used to dealing with the huge volumes of data AI relies on. When telcos automate systems, networks and processes — particularly with the injection of AI — they benefit from feedback loops that further improve those automated processes. This drives simplicity in an industry rife with complexity.

The digital transformation we all talk about depends on driving out complexity and becoming more agile, and the only way to do that is by automating intelligently. Looking ahead to the launch of 5G, it will become impossible for telcos to manage billions of connected devices without AI assistance.

Telcos’ current AI focus: Improving speed and efficiency

Key learnings on telco AI initiatives

Through our research, we have identified five primary domains of activity for telcos looking to make use of AI. The first three broadly relate to business process improvement, with the end goal of reducing costs and improving efficiency.

  1. Optimising existing networks and operations. Telcos are using AI not only for network planning and optimisation, but also to improve their human resources, accounting and fraud-management functions. For example, Telefónica has built an ML model capable of monitoring the status of the network, predicting possible failures and an optimising maintenance routes.[1] This has been particularly important in its rollout and maintenance of networks across rural Latin America, where it can take an engineer up to a day to travel to the site of a network fault.
  2. Improving sales and marketing activity. This includes upselling, cross-selling and agent augmentation. Globe Telecom, for example, has created a data-management platform that collates network signal information alongside information from billing and payment systems to provide personalised offers to its mobile customers.[2]
  3. Improving the customer experience. This includes use cases such as fault resolution, churn management, chatbots and virtual assistants. Vodafone has developed the chatbot TOBi, for example, which can handle 70 percent of customer requests and employs ML technology to further improve the support it offers to customers.[3]

The remaining two domains focus on using AI to enable new ways of working that go beyond a telco’s core connectivity offering, with a focus on growing revenues.

  1. Driving (and monetising) customer data. AI can help telcos aggregate massive volumes of anonymised customer data that can then be sold to third parties. Singtel’s DataSpark has taken a step down this data-as-a-service route, providing access to GPS and mobile network data that other organisations can incorporate into their applications and services.[4]
  2. Enabling or supporting new services. This includes cybersecurity and predictive analytics. As an example, AT&T is using ML to quickly identify normal and abnormal activity in it networks.[5] This sort of solution could be sold as a managed service to other enterprises in the future, unlocking a new revenue stream.

Contents of the full report include:

  • Executive Summary
  • Not a passing fad: AI is becoming a core capability for telcos
  • What is artificial intelligence?
  • Cutting through the hype 8
  • Telcos’ current AI focus: Speed and efficiency
  • How are telcos using AI today?
  • Sharing is caring: How telco AI initiatives are organised
  • Centralised AI initiatives
  • Cross-functional R&D units
  • Individual AI initiatives
  • The stumbling blocks for AI implementation — and how to get around them
  • AI initiatives need to be powered by high-quality data
  • Data governance is an essential requirement
  • Exploring the link between data maturity and AI success
  • The tricky transition from the lab to in-field deployment
  • Accept failure and embrace innovation
  • Revamp partnership strategies
  • New challenges, new expectations
  • Finding the impact: How telcos assess the benefits of AI
  • Different types of telcos, different levels of AI maturity
  • Conclusion

Figures:

  1. Moving toward AI
  2. Telco AI initiatives by domain
  3. Centrally coordinated AI initiatives are more likely to scale
  4. Poor data and a lack of internal skills are key challenges
  5. Telcos struggle with data management at every step of the AI journey
  6. Issues with data governance do not preclude AI implementation
  7. Only 1 in 5 AI projects has advanced to live deployment
  8. Collaborative partnering is key to AI success
  9. Nearly half of telcos have not gone live with AI
  10. Fixed-line and wholesale operators lag behind


[1] Source: Telefónica

[2] Source: Cloudera

[3] Source: Vodafone

[4] Source: DataSpark

[5] Source: AT&T

Three new telco business models: Soft-net, Cloud-net, Compute-net

Introduction

This report outlines three new telecoms business models that builds on previous research where we have outlined our vision of an emerging third age of telecoms called the Coordination Age. This is based on a global need to improve the efficiency of resource utilisation is manifesting in industries and individuals as a desire to “make the world work better”. We discuss this concept in detail in the following reports:

We believe that three new business models for telcos are emerging as part of the Coordination Age.

  • The Soft-Net: the core business remains connectivity, but the softwarisation of the network through SDN / NFV enables the network to adapt and scale to support new, advanced connectivity services. This includes third-party digital and networked-compute services that depend on the physical network connectivity the Soft-Net provides.
  • The Cloud-Net: also connectivity-focused, but with the production, delivery and consumption of services increasingly effected via the cloud (i.e. cloud-native). SDN and virtualisation enable capacity and services to be spun up, managed and delivered on demand over any physical network and device.
  • The Compute-Net: the core business is to provide distributed, networked, compute- and software-based services, often for specific enterprise verticals. These depend on SDN and NFV to deliver the ultra-fast, low-latency compute, throughput and routing capabilities required.

The three new models represent distinct strategic options for telcos looking to either: optimise and evolve their existing connectivity business; create new value from cloud-based, ‘horizontal’ platforms; or expand into new vertical markets – or a combination of all three approaches. This is illustrated here:

Interdependence between the three future telco business models

Source: STL Partners

In other words:

  • The Soft-Net operates the physical and virtualised infrastructure that delivers flexible, advanced connectivity in support of Cloud-Net and Compute-Net services (as well as well as legacy communications and connectivity services, delivered in a more scalable and cost-effective way)
  • The Cloud-Net delivers flexible, on-demand connectivity over hybrid infrastructure (including that owned by multiple Soft-Nets) in support of the increasingly complex and variable networking requirements of globally distributed, digital enterprises
  • The Compute-Net delivers vertically focused, compute-enabled processes and outcomes across all areas of industry and society. In doing so, it relies on networking and cloud platform services supplied by the Soft-Net and Cloud-Net, which may or may not be vertically integrated as part of its own organisation.

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The three telecoms business models link to NFV / SDN strategies

One of the distinguishing features of these models is the different modes of telco engagement in NFV and SDN they are potentially driven by. In previous analyses, we have identified three pathways towards NFV and SDN deployment. This is how they link to the three business models:

Figure 1: The three future telco business models and corresponding NFV pathways

Source: STL Partners, NFV / SDN deployment pathways: Three telco futures

In the rest of this report, we define these telecoms business models in more detail and illustrate how they present a pragmatic framework for telcos to focus their technology investments and develop valuable new Coordination Age services.

Contents:

  • Executive Summary
  • Introduction
  • Three telco futures and Telco 2.0
  • Chapter 1: Three telecoms business models for the Coordination Age
  • Three new business models: but why ‘telco’?
  • Business model analysis: Telcos’ vs competitors’ strengths
  • Relationship between the Soft-Net, Cloud-Net and Compute-Net business models
  • Chapter 2: Roles of the Soft-Net, Cloud-Net and Compute-Net in a ‘driverless car-as-a-service’ ecosystem
  • A driverless car-as-a-service business involves coordination of data, processes and events across a broad supply chain
  • Soft-Nets provide the mainly wireless connectivity
  • Cloud-Nets provide the hybrid, on-demand wide-area networking
  • Compute-Nets design and coordinate the ecosystem
  • Conclusions
  • The Coordination Age: A new purpose for telecoms, and three models for realising it
  • Key takeaways for telcos

Figures:

  1. The three future telco business models and corresponding NFV pathways
  2. The Telco 2.0 infrastructure and service stack
  3. Interdependence between the three future telco business models
  4. Two examples of the three new business models
  5. The three new business models overview
  6. Telcos face some fierce competition as they move up the stack
  7. Telco expansion across the three business models
  8. Advantages and disadvantages of vertical integration
  9. Mapping the Soft-Net, Cloud-Net and Compute-Net roles in a driverless car environment
  10. Types of data and corresponding compute-based services in a driverless car-as-a-service ecosystem

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Telcos in health – Part 2: How to crack the healthcare opportunity

This report is a follow-up from our first report Telcos in health – Part 1: Where is the opportunity? which looked at overarching trends in digital health and how telcos, global internet players, and health focused software and hardware vendors are positioning themselves to address the needs of resource-strained healthcare providers.

It also build on in depth case studies we did on TELUS Health and Telstra Health.

Telcos should invest in health if…

  • They want to build new revenue further up the IT value chain
  • They are prepared to make a long term commitment
  • They can clearly identify a barrier to healthcare access and/or delivery in their market

…Then healthcare is a good adjacent opportunity with strong long term potential that ties closely with core telco assets beyond connectivity:

  • Relationships with local regulators
  • Capabilities in data exchange, transactions processing, authentication, etc.

Telcos can help healthcare systems address escalating resourcing and service delivery challenges

Pressures on healthcare - ageing populations and lack of resources
Chart showing the dynamics driving challenges in healthcare systems

Telcos can help overcome the key barriers to more efficient, patient-friendly healthcare:

  • Permissions and security for sharing data between providers and patients
  • Surfacing actionable insights from patient data (e.g. using AI) while protecting their privacy

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Why telcos’ local presence makes them good candidates to coordinate the digital and physical elements of healthcare

  • As locally regulated organisations, telcos can position themselves as more trustworthy than global players for exchange and management of health data
  • Given their universal reach, telcos make good partners for governments seeking to improve access and monitor quality of healthcare, e.g.:
    • Telco-agnostic, national SMS shortcodes could be created to enable patients to access health information and services, or standard billing codes linked to health IT systems for physicians to send SMS reminders
    • Partner with health delivery organisations to ensure available mobile health apps meet best practice guidelines
    • Authentication and digital signatures for high-risk drugs like opioids
  • Healthcare applications need more careful development than most consumer sectors, playing to telcos’ strengths – service developers should not take a “fail fast” approach with people’s health

Telcos have further reach across the diverse  healthcare ecosystem than most companies

The complexity of healthcare systems - what needs to be linked
To coordinate healthcare, you need to make these things work together

However, based on the nine telco health case studies in this report, to successfully help healthcare customers adopt IoT, data-driven processes and AI, telcos must offer at least some systems integration, and probably develop much more health-specific IT solutions.

Case study overview: Depth of healthcare focus

Nine telcos shown on a spectrum of the kind of healthcare services they provide
Where Vodafone, AT&T, BT, Verizon, O2, Swisscom, Telstra, Telenor Tonic and TELUS Health fit on a spectrum of services to healthcare,

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Telcos in health – Part 1: Where is the opportunity?

Why is healthcare an attractive sector?

  • Healthcare systems – particularly in developed markets – must find ways to treat ageing populations with chronic illnesses in a more cost effective way.
  • Resource strained health providers have very limited internal IT expertise. This means healthcare is among the least digitised sectors, with high demand for end-to-end solutions.
  • The sensitive nature of health data means locally-regulated telcos may be able to build on positions of trust in their markets.
  • In emerging markets, there are huge populations with limited access to health insurance, information and treatment. Telcos may be able to leverage their brands and distribution networks to address these needs.
  • This report outlines how the digital health landscape is addressing these challenges, and how telcos can help

Four tech trends are supporting healthcare transformation – all underpinned by connectivity and integration for data sharing

These four trends are not separate – they all interrelate. The true value lies in enabling secure data transfer across the four areas, and presenting data and insights in a useful way for end-users, e.g. GPs don’t have the time to look at ten pages of a patient’s wearable data, in part because they may be liable to act on additional information.

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Digital health solutions break down into three layers

Digital health solutions in 3 layers

This report explores how telcos can address opportunities across these three layers, as well as how they can partner or compete with other players seeking to support healthcare providers in their digital transformation.

Our follow up report looks at nine case studies of telcos’ healthcare propositions: Telcos in health – Part 2: How to crack the healthcare opportunity

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MWC 2018: Desperately seeking a business case

What we found at MWC 2018

STL Partners were delighted to again be official partners of the GSMA for the Mobile World Congress (MWC 2018). Our team decamped to Barcelona for the week, and the following is an extract of our analysis of what we saw, heard and thought – and what telcos should do.

No big surprises, but plenty of nuance

As we expected (see MWC2018: 5 things to watch out for), IoT, 5G, NFV/SDN, edge computing and AI were the main topics of discussion, alongside telcos’ continuing struggles with the challenges of managing digital transformation and creating new revenues.

With consumers, and especially in more mature markets, telcos are fighting to retain and regain relevance with their customers, and struggling to justify why they should pay any more for data, lower latency or the insights IoT data can bring.

Hence the telco business cases for IoT, 5G, and edge computing are all eyeing the opportunity to digitalise and connect enterprise applications, sometimes hyped as ‘The Fourth Industrial Revolution’. But the enterprise market is notoriously difficult to serve due to its complex demands, so success requires a good understanding of industry-specific issues, and the business cases are hard to make.

So IoT, 5G, and edge computing are (somewhat inter-related) technologies that will initially deliver the same business benefits, i.e. helping enterprises adopt more efficient, agile and data-centric processes. AI is rather different and will have a more widespread impact in telecoms as we outline below. But each faces its own challenges.

5G: patchy to start

5G should deliver more than enterprise applications in the fullness of time. But most telcos are reluctant to step straight back into a major network capital investment cycle, and still have money to spend to meet the rising demand for 4G.

So, we think the market development of 5G will look different to the other ‘G’s, and the initial uptake of 5G will be patchy:

  • The US market is looking set to talk itself into a 5G war, with each operator having its own motivation to be seen as the leader in 5G. AT&T because it wants to do everything, Verizon because it has an instinct to retain its premium network tag, T-Mobile because it wants to punch all the other operators, and Sprint because it needs to find a way to differentiate. The US market is also big enough to tempt handset vendors into production – or at least into experimentation in 5G. From a PR perspective at least, the US operators’ fingers are twitching on their triggers, but it’s likely that the CFOs and shareholders will need a little more persuasion that it will work economically. This means there will probably be an initial period of ‘phoney war’ as they work out how to play it in various tests and trials, while making increasingly aggressive claims to win the opening propaganda contest.
  • South Korea and Japan also seem determined to head off on the 5G path, and are probably sufficiently advanced markets that are suited to taking the technology upgrade early.
  • Elsewhere though, the enthusiasm for 5G is a little more muted, but the enterprise applications could well make sense for reasons we discuss later in this brief report. Having said that, much of what we saw at MWC 2018 would best be described as “technology seeking a business case” – some interesting technical developments, but little coherent economic rationale that even vaguely approaches a credible business case. “If we build it they will come” may turn out to be the most pragmatic argument, so it is again initially likely to be something of a “test and pivot” approach, as operators dip a toe in the water to see what they can make work, and where, before betting more widely.
  • Wider new applications such as autonomous cars and AR/VR won’t move the needle until later in most markets. Autonomous cars because they won’t be able to rely on a network until it’s widespread and highly proven (see Autonomous cars: Where’s the money for telcos?), and AR/VR because it will take significant time to develop as a widespread and highly used technology (see AR/VR: Won’t move the 5G needle).

Many network vendors, notably Huawei, while hoping to bet big on 5G are sensibly taking an ‘incremental’ approach to 5G, and designing it as an add-on or upgrade to 4G or 4G+ solutions.

NB. We will soon be publishing a detailed report on our analysis of 5G’s progress.

Edge computing: the need to move beyond technology

MWC 2018 has shown that the industry is still mainly focussing on technology-focused PoCs in the area of edge computing. Key use cases that were demonstrated typically revolved around optimised video delivery, IoT edge gateways, and control of autonomous vehicles or drones.

However, it seems that the industry hasn’t got much closer to articulating viable business and monetisation models for these – technically impressive – use cases. Telcos still need to find out how to cope with three fundamental challenges and uncertainties which represent the key road blocks for success at the edge:

  • Commercialisation: It is – and will be for the foreseeable future – unclear which edge use cases will deliver significant commercial value to telcos (and to their customers for that matter). In addition, telcos lack clarity on which business models need to be employed to monetise individual use cases. We have addressed this issue in Edge computing: Five viable telco business models.
  • Operationalisation: Edge computing capabilities might be relevant for very different parts of the telco organisation – for both internal and external use cases, as well as wider efforts which are related to NFV and 5G. This calls for a certain degree of coordination within the organisation. Equally important is the need for an edge platform which ensures flexibility and speed in developing and onboarding applications.
  • Ecosystem orchestration: Telcos need to work out what their role in the wider distributed (multi-)cloud ecosystem should be, as edge computing is not solely a telco concept (see e.g. AWS Greengrass). This boils down to the question of who telcos should partner with and who they should compete with in the edge computing and edge cloud space. In addition, telcos are starting to acknowledge that there needs to be significant technical and commercial interoperability between operators providing edge computing capabilities to third parties. Otherwise, telcos will stumble over the usual problem of market fragmentation, which would make it unattractive for application providers and developers to offer their services through the telco edge cloud.

STL Partners is currently undertaking primary research on this topic to identify the key short-term and long-term strategic principles for telcos to overcome the above barriers and ensure commercial success at the edge. The findings will be discussed in an upcoming report.

IoT: the struggle to add value

What we saw at MWC 2018 lined up with what we said in Monetising IoT: Four steps for success. “IoT is not a quick win for telcos. The value of IoT connectivity is only a small portion of the total estimated value of the IoT ecosystem, and therefore telcos seeking to grow greater value in this area are actively moving into other layers, such as platforms and vertical end solutions.”

Telcos therefore face a conundrum in IoT. At one extreme, they can focus on the connectivity, and can do reasonably well by providing SIMs plus functionality in reporting and management. Above and beyond that, which is where the bulk of the economic value lies, industries need sophisticated and evolving solutions that integrate connectivity, applications, machines and data.

Such industry solutions need to be tailored to niche demands and limitations, such as specific regulations or legacy infrastructure. As an example, hospitals want to digitalise their operations, but they can’t afford to replace expensive medical equipment like 15-year-old MRI machines, which might not be compatible with the latest technologies and application programmes. On top of that, connecting sensitive medical data comes with sensitive data protection and security requirements. To make all this work well and securely is no small matter, and the province of some highly sophisticated specialist players, well beyond the appetite of most telcos. (NB. We discuss other possible healthcare approaches on page 8 of this report.)

To be successful at a wider level in Industrial IoT will take serious knowledge at both technical domain and sector level, and this is not easy to put together for even one industry, let alone several. It takes vision, commitment, time and investment.

NFV/SDN: grinding forward

NFV/SDN at MWC 2018 was again very much in line with our previous findings and expectations. Operators are making progress, but it is slow and piecemeal.

On the ‘progress’ side of the equation, two new open source initiatives to develop standards for RAN virtualisation were debuted at MWC: the Open RAN (ORAN) project (in which AT&T, China Mobile and Deutsche Telekom are pooling their efforts) and the Cisco-led Open vRAN initiative (vRAN and C-RAN will feature in our forward research). On the ‘piecemeal’ side of the equation, these developments only add to the sense of fragmentation in industry efforts to arrive at NFV standards and interoperability frameworks, which will be critical for realising the potential of NFV to support 5G use cases in areas such as IoT, edge computing and network slicing (as discussed above).

In our forthcoming reports on emerging NFV / SDN technology and use cases, we will build on the analysis in our recent report NFV/SDN deployment pathways: Three telco futures and attempt to show how strategic clarity about the type of telco they wish to be, and the social and economic functions they see their services as performing, is vital to inform operators’ engagement in NFV and SDN, and their selection of NFV / SDN use-cases and associated vertical markets (see discussion of expansion into new verticals below). The first of these reports will take in the MWC ‘hot topics’ of 5G, edge computing and network slicing, with subsequent analyses looking at SD-WAN / on-demand enterprise networking, and industrial and telco automation.

And of course, we are continuing to build our database of information on live, commercial deployments of NFV / SDN, the NFV Deployment Tracker, with further updates adding data on deployments in the Asia-Pacific region, the Middle East, Africa and Latin America, in addition to those recently completed for Europe and North America.

AI: Strategies taking form

AI is an exception to the other technologies because it has both

  • Internal applications for telcos, helping to streamline repetitive and data-intensive tasks across their businesses,
  • And the potential to complement external enterprise solutions.

While 5G, IoT and edge computing seem to be all about finding the use-cases, every sector and every part of telcos’ businesses, from network planning and operations, to back office functions, customer experience and product development, can be streamlined with more advanced data analytics and automation. So, it’s not surprising that all telcos are thinking about how to implement AI.

Tier 1 players such as AT&T, SK Telecom, Orange, Deutsche Telekom and Vodafone already have clear plans on what they are prioritising in the short-term, and what they want to do internally versus partner with vendors like IBM. Improving customer experience is by far the priority area right now, reflecting telcos’ desire to regain credibility with consumers, as well as the relative maturity and awareness of natural language processing within the wider field of AI/machine learning (ML).

Despite having clear ideas of what they want to do, most telcos are still in the early days of implementation. Any live telco chatbots still have limited capabilities and are only operational in one or two markets, so 2018 will be a year of scaling into new markets and channels.

The crucial initial promise of AI is to save costs across the business, and behind the highly hyped chatbot programmes there is evidence that telcos are taking steps towards using machine learning for predictive care (see our report AI in customer services: It’s not all about chatbots), back office resource planning, and network maintenance and operations.

The major question for telcos is how they should organise their AI initiatives and skills for the highest impact, and where and with whom they should partner. Right now, most telcos are taking a decentralised approach to deploying AI, so as not to stifle or hold back progress across various business units or opcos, with an aim to shift towards becoming more centralised.

Whether this is the right approach is still up for debate. We are addressing this question as part of an interview programme with telcos on their progress and strategies around AI and will publish our findings in a forthcoming report outlining the telco AI roadmap.

To read on about what telcos should do, please login and download the report, or contact us to subscribe.

Contents:

  • What we found at MWC 2018
  • No big surprises, but plenty of nuance
  • 5G: patchy to start
  • Edge computing: the need to move beyond technology
  • IoT: the struggle to add value
  • NFV/SDN: grinding forward
  • AI: strategies taking form
  • So, what should telcos do?
  • Next steps

Figures:

  • Figure 1: TELUS Health Exchange