John Legere of T-Mobile is a canny operator and knows how to play the sycophant to Trump’s nationalist instincts in touting the ability of a combined T-Mobile & Sprint to invest in a super-charged 5G roll out, as per this presentation, playing the job creation and beat the Chinese technological advancement cards. Legere cites an Analysys Mason report commissioned by the US industry lobby group CTIA to back up such claims which in turn cites an Accenture report from 2017 on 5G in the US which claims that “telecom operators are expected to invest approximately $275 billion in infrastructure, which could create up to 3 million jobs and boost GDP by $500 billion”. In 2016, the European Commission in this report stated that 5G “investments of approximately €56.6 billion will be likely to create 2.3 million jobs in Europe”. An IHS Markit 2017 report commissioned by Qualcomm claims that in 2035, “5G will enable $12.3 trillion of global economic output” and “the global 5G value chain will generate $3.5 trillion in output and support 22 million jobs” on the basis that “the global 5G value chain will invest an average of $200 billion annually”.
These are fantastical figures. Many assumptions go into their computation including the availability, range and cost of spectrum plus infrastructure spend and policy in relation to streamlining procedures and fee structures for the deployment of the small shoe-box cell sites (between 10 to 100 more antenna are required for 5G than current networks). Larger issues such as privacy and security also need to be addressed before we enter a world of ubiquitous ultra-reliable low latency networks as envisaged by the reports referenced above. Those of us who lived through, and barely survived, the telecom boom of the late 1990s can be forgiven for having a jaundice view of a new technology saving the telecom industry. This blog illustrates some of the challenges facing the wired telecom sector and the graph below shows the pressures that the US mobile players are under in terms of recent trends in service revenues.
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The mobile service revenues trends are remarkably similar to those in the enterprise and wholesale space. The graph above also shows the rationale for the T-Mobile/Sprint merger in terms of size as well as the impact of T-Mobile’s aggressive pricing strategy. All these trends are in the context of the insatiable increase in bandwidth traffic, as illustrated by the IP figures from Cisco below.
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This report from 2017 by Oliver Wyman is one of the better ones and contains some illuminating context for the 5G era. It shows that in Europe despite a 40% annual increase in mobile subscribers and a 36% annual increase in European IP traffic from 2006 to 2016, mobile service revenue and total telecom service revenue decreased by 22% and 19% respectively, as per the graphic below.
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The Oliver Wyman report concludes as follows:
“In the next five to ten years, demand in fixed-line broadband bandwidth will grow exponentially, leading to speeds that can only be supplied by FTTH/B. Mobile broadband demand will follow in parallel. Virtual reality is the “killer app” that will drive massive demand. Mobile broadband supply will begin to reach its limits, with spectral efficiency gains and additional attractive spectrum in the current bands not growing as fast as they have in the past. High-frequency beam technology in 5G will be radically new and will be able to meet future demand. At the same time, however, it will create massive mobile backhaul demand. The outcome is likely to shake the industry, leading not only to a new balance of power between mobile-only and integrated/fixed-line operators, but also to new potential revenue growth for the first time in many years.”
Another interesting graphic from the report, as below, is the historical and projected broadband usage.
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This 2017 report from Deloitte argues that “5G, across both the core and radio access network, stands to have a potentially greater impact on the overall ecosystem than any previous wireless generation”. Deloitte sees a “convergence of supply between wireline and wireless broadband, as almost all devices become connected over short-range wireless”. Deloitte concludes that “with an increasingly converged ecosystem of network and content players, an increasingly software-managed and defined physical networking space, and the demands and needs of consumers becoming complex enough that they no longer can manage individually, 5G and its associated technologies may have the power to reset the wireless landscape”.
This paper from an Infinera executive called Jon Baldry highlights the need for “improvements to the overall network infrastructure in terms of performance, features and bandwidth” to support 5G “using software-defined networking (SDN) control and network functions virtualization (NFV) will play a major role in the optimization of the network”. I came across an interesting claim that SDN and network virtualisation can reduce opex and capex by 63% and 68% respectively compared to traditional telecom networking. Baldry concludes that “these improvements will drive new fiber builds, and fiber upgrades to an ever-growing number of cell sites, creating significant opportunity for cable MSOs and other wholesale operators to capture significant share of cell backhaul and fronthaul services for 4G and 5G mobile networks”.
Whether all these investments and resulting new networks will halt the declining revenue trend for the telecom sector or merely provide a survival avenue for certain telecoms is something I have yet to be convinced about. One thing seems certain however and that is that tradition telecom models will change beyond recognition in the forthcoming 5G era.
Posted in Telecom
Tagged %G economics, 5G, 5G antenna, 5G cell sites, 5G cost benefit, 5G era, 5G mobile networks, 5G roll out, 5G value chain, Accenture, aggressive pricing strategy, Analysys Mason, bandwidth demand, broadband usage, cell backhaul, cell fronthaul services, China 5G, Cisco, converged network, CTIA, Deloitte, exponential growth, fee structures, fiber builds, fiber upgrades, fixed-line broadband bandwidth, high-frequency beam technology, IHS Markit, Infinera, infrastructure capex, infrastructure policy, IP traffic, John Legere, killer app, low latency networks, mobile backhaul demand, Mobile broadband demand, mobile subscribers, network functions virtualization, network infrastructure, network optimization, NFV, Oliver Wyman, PB per month, Qualcomm, radio access network, SDN, service revenues trends, short-range wireless, software defined network, spectral efficiency gains, spectrum, Sprint, T-Mobile, telecom hype, telecom revenue trend, telecom saviour, US mobile market, virtual reality, wireless generation, wireless landscape
The digital transformation of existing business models is a theme of our age. Robotic process automation (RPA) is one of the many acronyms to have found its way into the terminology of businesses today. I highlighted the potential for telecoms to digitalise their business models in this post. Klaus Schwab of the World Economic Forum in his book “Fourth Industrial Revolution” refers to the current era as one whereby “new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human”.
The financial services business is one that is regularly touted as been rife for transformation with fintech being the much-hyped buzz word. I last posted here and here on fintech and insurtech, the use of technology innovations designed to squeeze out savings and efficiency from existing insurance business models.
Artificial intelligence (AI) is used as an umbrella term for everything from process automation, to robotics and to machine learning. As referred to in this post on equity markets, the Financial Stability Board (FSB) released a report called “Artificial Intelligence and Machine Learning in Financial Services” in November 2017. In relation to insurance, the FSB report highlights that “some insurance companies are actively using machine learning to improve the pricing or marketing of insurance products by incorporating real-time, highly granular data, such as online shopping behaviour or telemetrics (sensors in connected devices, such as car odometers)”. Other areas highlighted include machine learning techniques in claims processing and the preventative benefits of remote sensors connected through the internet of things. Consultants are falling over themselves to get on the bandwagon as reports from the likes of Deloitte, EY, PwC, Capgemini, and Accenture illustrate.
One of the better recent reports on the topic is this one from the reinsurer SCOR. CEO Denis Kessler states that “information is becoming a commodity, and AI will enable us to process all of it” and that “AI and data will take us into a world of ex-ante predictability and ex-post monitoring, which will change the way risks are observed, carried, realized and settled”. Kessler believes that AI will impact the insurance sector in 3 ways:
- Reducing information asymmetry and bringing comprehensive and dynamic observability in the insurance transaction,
- Improving efficiencies and insurance product innovation, and
- Creating new “intrinsic“ AI risks.
I found one article in the SCOR report by Nicolas Miailhe of the Future Society at the Harvard Kennedy School particularly interesting. Whilst talking about the overall AI market, Miailhe states that “the general consensus remains that the market is on the brink of a revolution, which will be characterized by an asymmetric global oligopoly” and the “market is qualified as oligopolistic because of the association between the scale effects and network effects which drive concentration”. When referring to an oligopoly, Miailhe highlights two global blocks – GAFA (Google/Apple/Facebook/Amazon) and BATX (Baidu/Alibaba/Tencent/Xiaomi). In the insurance context, Miailhe states that “more often than not, this will mean that the insured must relinquish control, and at times, the ownership of data” and that “the delivery of these new services will intrude heavily on privacy”.
At a more mundane level, Miailhe highlights the difficulty for stakeholders such as auditors and regulators to understand the business models of the future which “delegate the risk-profiling process to computer systems that run software based on “black box” algorithms”. Miailhe also cautions that bias can infiltrate algorithms as “algorithms are written by people, and machine-learning algorithms adjust what they do according to people’s behaviour”.
In a statement that seems particularly relevant today in terms of the current issue around Facebook and data privacy, Miailhe warns that “the issues of auditability, certification and tension between transparency and competitive dynamics are becoming apparent and will play a key role in facilitating or hindering the dissemination of AI systems”.
Now, that’s not something you’ll hear from the usual cheer leaders.
Posted in Insurance Market
Tagged Accenture, AI, AI systems, algorithm bias, Alibaba, Amazon, Apple, Artificial Insurance, artificial intelligence, asymmetric global oligopoly, auditability, Baidu, Capgemini, claims processing, competitive dynamics, Deloitte, Denis Kessler, digital transformation, ex-ante predictability, ex-post monitoring, EY, Facebook, Financial Stability Board, fintech, Fourth Industrial Revolution, Future Society, Google, granular data, Harvard Kennedy School, improving efficiencies, information asymmetry, information commodity, insurance Innovation, insurance sector, InsurTech, internet of things, Klaus Schwab, machine learning, machine learning algorithms, machine learning techniques, new AI risks, Nicolas Miailhe, product innovation, PwC, robotic process automation, robotics, SCOR, telemetrics, Tencent, transparency, Xiaomi