The new telcos: A field guide

Introduction

The traditional industry view is that “telcos” are a well-defined and fairly cohesive group. Industry associations like GSMA, ETNO, CTIA and others have typically been fairly homogeneous collections of fixed or mobile operators, only really varying in size. The third-ranked mobile operator in Bolivia has not really been that different from AT&T or Vodafone in terms of technology, business model or vendor relationships.

Our own company, STL Partners used to have the brand “Telco 2.0”. However, our main baseline assumption then was that the industry was mostly made up the same network operators, but using a new 2.0 set of business models.

This situation is now changing. Telecom service providers – telcos – are starting to emerge in a huge variety of new shapes, sizes and backgrounds. There is fragmentation in technology strategy, target audiences, go-to-market and regional/national/international scope.

This report is not a full explanation of all the different strategies, services and technological architecture. Instead of analysing all of the “metabolic” functions and “evolutionary mechanisms”, this is more of a field-guide to all the new species of telco that the industry is starting to see. More detail on the enablers – such as fibre, 5G and cloud-based infrastructure – and the demand-side (such as vertical industries’ communications needs and applications) can be found in our other output.

The report provides descriptions with broad contours of motivation, service-offerings and implications for incumbents. We are not “taking sides” here. If new telcos push out the older species, that’s just evolution of those “red in tooth and claw”. We’re taking the role of field zoologists, not conservationists.

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Field guides are collections/lists of natural & human phenomena

animal-species-telcos-stl-partners

Source: Amazon, respective publishers’ copyright

The historical landscape

The term “telco” is a little slippery to define, but most observers would likely agree that the “traditional” telecoms industry has mostly been made up of the following groups of CSPs:

  • MNOs: Countries usually have a few major mobile network operators (MNOs) that are typically national, or sometimes regional.
  • Fixed operators: Markets also have infrastructure-based fixed telcos, usually with one (or a small number) that were originally national state-owned monopolies, plus a select number of other licensed providers, often with greenfield FTTX fibre. Some countries have a vibrant array of smaller “AltNets”, or competitive carriers (originally known as CLECs in the US).
  • Converged operators: These combine fixed and mobile operations in the same business or group. Sometimes they are arms-length (or even in different countries), but many try to offer combined or converged service propositions.
  • Wholesale telcos: There is a tier of a few major international operators that provide interconnect services and other capabilities. Often these have been subsidiaries (or joint ventures) of national telcos.

In addition to these, the communications industry in each market has also often had an array of secondary connectivity or telecom service providers as a kind “supporting cast”, which generally have not been viewed as “telecom operators”. This is either because they fall into different regulatory buckets, only target niche markets, or tend to use different technologies. These have included:

  • MVNOs
  • Towercos
  • Internet Exchanges
  • (W)ISPs
  • Satellite operators

Some of these have had a strong overlap with telcos, or have been spun-out or acquired at various times, but they have broadly remained as independent organisations. Importantly, many of these now look much more like “proper telcos” than they did in the past.

Why are “new telcos” emerging now?

To some extent, many of the classes of new telco have been “hiding in plain sight” for some time. MVNOs, towercos and numerous other SPs have been “telcos in all but name”, even if the industry has often ignored them. There has sometimes been a divisive “them and us” categorisation, especially applied when comparing older operators with cloud-based communications companies, or what STL has previously referred to as “under the floor” infrastructure owners. This attitude has been fairly common within governments and regulators, as well as among operator executives and staff.

However, there are now two groups of trends which are leading to the blurring of lines between “proper telcos” and other players:

  • Supply-side trends: The growing availability of the key building blocks of telcos – core networks, spectrum, fibre, equipment, locations and so on – is leading to democratisation. Virtualisation and openness, as well as a push for vendor diversification, is helping make it easier for new entrants, or adjacent players, to build telecom-style networks
  • Demand-side trends: A far richer range of telecom use-cases and customer types is pulling through specialist network builders and operators. These can start with specific geographies, or industry verticals, and then expand from there to other domains. Private 4G/5G networks and remote/underserved locations are good examples which need customisation and specialisation, but there are numerous other demand drivers for new types of service (and service provider), as well as alternative business models.

Taken together, the supply and demand factors are leading to the creation of new types of telcos (sometimes from established SPs, and sometimes greenfield) which are often competing with the incumbents.

While there is a stereotypical lobbying complaint about “level playing fields”, the reality is that there are now a whole range of different telecom “sports” emerging, with competitors arranged on courses, tracks, fields and hills, many of which are inherently not “level”. It’s down to the participants – whether old or new – to train appropriately and use suitable gear for each contest.

Virtualisation & cloudification of networks helps newcomers as well as existing operators

virtualisation-cloudification-networks-STL-Partners

Source: STL Partners

Where are new telcos likeliest to emerge?

Most new telcos tend to focus initially on specific niche markets. Only a handful of recent entrants have raised enough capital to build out entire national networks, either with fixed or mobile networks. Jio, Rakuten Mobile and Dish are all exceptions – and ones which came with a significant industrial heritage and regulatory impetus that enabled them to scale broadly.

Instead, most new service providers have focused on specific domains, with some expanding more broadly at a later point. Examples of the geographic / customer niches for new operators include:

  • Enterprise private 4G/5G networks
  • Rural network services (or other isolated areas like mountains, offshore areas or islands)
  • Municipality / city-level services
  • National backbone fibre networks
  • Critical communications users (e.g. utilities)
  • Wholesale-only / shared infrastructure provision (e.g. neutral host)

This report sets out…

..to through each of the new “species” of telcos in turn. There is a certain level of overlap between the categories, as some organisations are developing networking offers in various domains in parallel (for instance, Cellnex offering towers, private networks, neutral host and RAN outsourcing).

The new telcos have been grouped into categories, based on some broad similarities:

  • “Evolved” traditional telcos: operators, or units of operators, that are recognisable from today’s companies and brands, or are new-entrant “peers” of these.
  • Adjacent wireless providers: these are service provider categories that have been established for many years, but which are now overlapping ever more closely with “traditional” telcos.
  • Enterprise and government telcos: these are other large organisations that are shifting from being “users” of telecoms, or building internal network assets, towards offering public telecom-type services.
  • Others: this is a catch-all category that spans various niche innovation models. One particular group here, decentralised/blockchain-based telcos, is analysed in more detail.

In each case, the category is examined briefly on the basis of:

  • Background and motivation of operators
  • Typical services and infrastructure being deployed
  • Examples (approx. 3-4 of each type)
  • Implications for mainstream telcos

Table of contents

  • Executive Summary
    • Overview
    • New telco categories and service areas
    • Recommendations for traditional fixed/mobile operators
    • Recommendations for vendors and suppliers
    • Recommendations for regulators, governments & advisors
  • Introduction
    • The historical landscape
    • Why are “new telcos” emerging now?
    • Where are new telcos likeliest to emerge?
    • Structure of this document
  • “Evolved” traditional telcos
    • Greenfield national networks
    • Telco systems integration units
    • “Crossover” Mobile, Fixed & cable operators
    • Extra-territorial telcos
  • Adjacent wireless providers
    • Neutral host network providers
    • TowerCos
    • FWA Fixed Wireless Access (WISPs)
    • Satellite players
  • Enterprise & government telcos
    • Industrial / vertical MNOs
    • Utility companies offering commercial telecom services
    • Enterprises’ corporate IT network service groups
    • Governments & public sector
  • New categories
    • Decentralised telcos (blockchain / cryptocurrency-based)
    • Other “new telco” categories
  • Conclusions

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IoT security: The foundation for growth beyond connectivity

Introduction

The European Union Agency for Cybersecurity (ENISA) defines the IoT as “a cyber-physical ecosystem of interconnected sensors and actuators, which enable intelligent decision making.” In this ecosystem, the information or data flows among the various components of the IoT enable informed decision making for machines, objects, and the spaces in which they operate. Through this web of tightly interconnected cyber-physical systems, the IoT underpins a variety of applications such as smart cities, smart factories, smart agriculture and so forth.

While these applications touch all the areas of our living and working activities, bringing enormous benefits and possibilities, they also exacerbate system complexities and, in turn, significantly enlarge the domain of threats and risks. As a result, securing the IoT is a very complex task, involving the implementation of highly specialised security measures. In market terms, this complexity translates into rich ecosystems of skills and expertise, where there is not one player in charge of securing the IoT, but it is both a responsibility and an opportunity for all players in the value chain.

Thinking about IoT security, the fundamental objective is ensuring the trust between the provider of an IoT solution and the IoT solution adopter. Microsoft IoT Signals, a well-known survey of 3,000 organisations adopting the IoT, emphasizes this in its 2021 edition, where 91% of the organisations surveyed have security concerns about adopting the IoT. 29% of those organisations do not scale their IoT solution due to security concerns. These concerns hamper the benefits enterprises can gain from IoT solutions. For instance, in the same survey, more than 55% of organisations said they were becoming more efficient adopting the IoT, and 23% claimed that their IoT solution has a direct impact on revenue growth. These benefits come from the variety and volume of data gathered through the IoT to drive better informed operational decisions. The result is that IoT data becomes a fundamental and necessary asset that must be protected.

While managing security risks in IoT is often perceived as a necessary burden, this report will instead highlight securing the IoT as an opportunity. For telecoms operators, this opportunity may not always be directly evident in new revenues, but it is fundamental to the creation of trust between provider and the adopter of IoT services. That trust, built through IoT security services, provides a stronger foundation from which to develop new revenue-generating services beyond connectivity.

This report also argues that by building more comprehensive data insights services into their existing IoT platforms mobile network operators are in a strong position to bring that trust to enterprises. As operators expand their security offers from well-known security functions provided at connectivity level – almost embedded in an operator – to more sophisticated security services across the IoT architecture, they can position themselves as a partner and guide to enterprises as they likewise become more sophisticated in their security needs.

The report is structured in three main parts:

  1. Discussion of the key vulnerabilities in the IoT and responses to those defined by regulators and security bodies such as ENISA, NIST, IoT Security Foundation and others.
  2. Analysis of the roles mobile network operators are playing in the IoTsecurity services market.
  3. Analysis of the opportunities for mobile network operators in security services for the IoT.

The research is based on the author’s extensive experience in IoT security, and enriched by interviews with IoT security experts close to the world of mobile network operators. Finally, an understanding of the most authoritative guidelines and analysis (ENISA, NIST, IoTSF, GSMA, OWASP) on IoT security supports the research.

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Why IoT security is rising up the agenda

In the fervent debates on the development of the IoT, the security aspect is often hidden or avoided. This stems from a common view among IoT solution companies and end-users that security is a heavy point of discussion that hampers business enthusiasm. This perspective is both unhelpful and dangerous, actively hindering greater scale and trust in the IoT. We strongly believe the argument should be flipped around. Although IoT security is a fundamental risk for the development of the IoT, it is also the means through which to develop robust, reliable, and lucrative IoT solutions. Therefore, IoT security should become a priority in IoT strategy and project development.

There are three considerations that are driving a fundamental shift in perceptions of security from a barrier to an enabler of IoT solutions, both among providers and adopters:

  1. Rising frequency and prevalence of avoidable large scale IoT security breaches.  There are plenty of examples of hacking of connected devices and large IoT systems that have dramatically compromised IoT solutions’ functioning, the business case linked to them, and relationships with customers. Recent examples include:
    • In May 2021, Colonial Pipe suffered a ransomware attack that impacted the computerised equipment monitoring the entire pipeline system from Texas to New Jersey, carrying 2.5 million barrel of oil a day. The entire system, based on a vast IoT solution of several sensors along the pipeline, was blocked. To re-boot the system, Colonial Pipeline paid 75 Bitcoin (the equivalent of $4.4 million at the time). (The solution to this type of breach is implementation of a remediation strategy.)
    • Consumer IoT devices are no less attractive than big corporations to hackers. In June 2021, the McAfee Advanced Threat Research identified a potential security vulnerability in the Peleton Bike+: “The ATR team recently disclosed a vulnerability (CVE-2021-3387) in the Peloton Bike+, which would allow a hacker with either physical access to the Bike+ or access during any point in the supply chain (from construction to delivery), to gain remote root access to the Peloton’s tablet. The hacker could install malicious software, intercept traffic and user’s personal data, and even gain control of the Bike’s camera and microphone over the internet.” The Peleton Bike+ vulnerability almost become a matter of national security in the US, considering that President Jo Biden is, apparently, a Peleton Bike+ user. (The security solution to this type of breach is software and system updates.)

2. Regulatory bodies are responding to the increasing incidence of IoT attacks with guidelines and regulations. Realising the danger of connected devices and systems developed with inappropriate security features, regulators worldwide are issuing specific procedures and policies in IoT security. In some cases these are mandatory and in other cases function as guidance and support.

    • Australia has created a voluntary code of practice, Securing the Internet of Things for Consumers, focussing on issues of authorisation, authentication, and access of IoTdata in consumer devices.
    • Singapore has issued the IoT Cyber Security Guide to support enterprises to develop secure IoT systems. Enterprises should also comply to IoT-related standards in sensors, sensor networks, and devices.
    • The United Kingdom has focussed on security around IoT devices with the first Code of Practice for Consumer IoT Security published in 2018.
    • The European Union is focussing on the development of an “IoT Trust” label for IoT consumer devices.
    • The United States launched legislation in 2020 – IoT Cybersecurity Improvements Act – which, through a combination of subsidies and project grants, incentivises companies that build and sell IoT solutions to develop them with a security-by-design

These initiatives are all specifically designed around IoT devices and systems. However, it is important to highlight that the relevant legal framework is wider. For example, in the European Union, the three key regulations applying to the sale and use of IoT devices and ecosystems are CE Marking (health and safety of products sold in the EU), GDPR, and the Network and Information Security Directive (NIS Directive). It is well known, but important to stress it, that violation of GDPR – data breaches and misuses of data – can cost up to EUR20 million. A similar legal framework exists in the United States, in which there are three Acts relevant for IoT devices: Federal Trade Commission Act (FTC Act), the Cyber Security Information Sharing Act (CISA), and the Children’s Online Privacy Protection Act (COPPA). Those who violate America’s Federal Trade Commission Act could face fines of $41,484 per violation, per day.

It is also worth noting that many of these regulations focus on the consumer IoT because it has been the weakest in terms of attention to security features, there is a direct link to data privacy (i.e. by hacking into IoT devices malicious actors can gain access to other digital profile data), and most consumers do not have the skill or resources to protect themselves.

3. The increasing business and economic impact of IoT data. Organisations of all kinds are increasingly relying on data for their strategy development, optimisation of processes, increasing engagement with customers and innovating their business models. The data needed for all these activities is increasingly machine generated by an IoT solution. To illustrate this value, there have been several studies on understanding the economic impact of IoT data. For example, in April 2019, GSMA Intelligence estimated that the economic impact of IoT on business productivity was in the order of $175bn, 0.2% of the global GDP. GSMA Intelligence also forecasted that by 2025 the economic impact would increase to $371bn, 0.34% of the global GDP, with IoT companies generating almost a trillion dollar in revenues. Ultimately, if a competitor or malicious actors gets hold of an organisation’s data, then they have accessed one of its most important assets. Therefore, as organisations become ever more data-driven in their strategic decision making, the importance of securing the systems gathering and storing that data will rise.

Defining IoT Security

The US NIST (National Institute for Standards and Technology) defines cyber-risk as “a function of the probability of a given threat source’s exercising any potential vulnerability and the resulting impact of that adverse event on the organisation.” The IoT security risk is one of many cyber-risks to any organisation and refers to the unforeseen exploitation of IoT system vulnerabilities to gain access to assets with the intent to cause harm.

A major challenge in assessing the IoT system vulnerabilities and threats comes from the technological complexity of an IoT solution and the diversity of applications and environments the IoT solution serves. Therefore, IoT security can be assessed in two levels. The first level regards the IoT architectural stack, which is common to different domains and applications. The second level is solution-specific and requires specialised services depending on the domain of applications.

The starting point of the analysis is a model of IoT architecture, illustrated in a simplified format in the diagram below.

Simplified IoT  architecture

Simplified-IoT-architecture-STL-Partners

Source: STL Partners

 

Table of contents

  • Executive Summary
    • Security can enable MNOs to build beyond connectivity in IoT
    • Next steps: Building on security in the Coordination Age
  • Introduction
    • Why IoT security is rising up the agenda
  • Defining IoT security
    • Key IoT vulnerabilities
    • Enterprises’ view on securing IoT
    • How to meet enterprise needs: Delivering security across three dimensions
  • Mobile operators’ roles in IoT security
    • Telco strategy comparison: IoT security offers vs dedicated business units
    • Assessing operators’ security services by function
    • Takeaways
  • Future growth trends for operators to capitalise on
    • eSIM and integrated eSIM (iSIM) capabilities
    • 5G private network security services
    • Managing encryption requirements
    • Blockchain in telecommunications
    • Secure communication through quantum information and communication technology

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Innovation leader case study: Telefónica Tech AI of Things

The origins of Telefónica Tech AI of Things

Telefónica LUCA was set up in 2016 to “enable corporate clients to understand their data and encourage a transparent and responsible use of that data”.

Before the creation of LUCA, Telefónica’s focus had been on developing assets and making acquisitions (e.g. Synergic Partners) to build strong internal capabilities around data and analytics – with some data monetisation capabilities housed within their Telefónica Digital unit (a global business unit selling products beyond connectivity, which was disbanded in 2016). Typical projects the team undertook related to using network data to make better decisioning for the network and marketing teams, and providing Telefónica Digital with external monetisation opportunities such as Smart Steps (aggregated, anonymised data for creation of vertical products) and Smart Digits (provision of consent-based data to the advertising industry).

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Creating the autonomous LUCA unit made a statement that Telefónica was serious about its strategy to offer data products to enterprise customers. Quoting from the original press release, “LUCA offered three lines of products and services:

The Business Insights area brings the value of anonymous and aggregated data on Telefónica’s networks for a wide range of clients. This includes Smart Steps, which is focused on mobility analysis solutions for more efficient planning. For example, to optimise transport networks and tourist management in cities, or in the case of a health emergency, in helping to better understand population movements and in limiting the spread of pandemics.

The analytical and external consultancy services for national and international clients will be provided by Synergic Partners, a company specialized in Big Data and Data Science which was acquired by Telefónica at the end of 2015.

Furthermore, LUCA will help its clients by providing BDaaS (Big Data as a Service) to empower clients to get the most out of their own data, using the Telefónica cloud infrastructure.”

The following table shows a timeline from the origins of LUCA in the Telefónica Digital business unit through to its merger into the Telefónica Tech AI of Things business in 2019 – illustrating the progression of its products and other major activities.

Timeline of Telefónica’s data monetisation business

Telefonica-data-monetisation-luca-AI-IoT

Source: STL Partners, Charlotte Patrick Consult

Points to note on the timeline above:

  • Telefónica stood out from its peers with the purchase of Synergic Partners in 2015 (bringing in 120 consultancy headcount). This provided not only another leg to the business with consulting capabilities, but also additional headcount to scope and sell their existing product sets.
  • Looking at the timeline, it took Telefónica two years from this purchase and the establishment LUCA to expand its portfolio. In 2018, a range of new, mainly IoT-related capabilities, were launched, built up from existing projects with individual customers.
  • Telefónica has added machine learning to its products across the timeframe, but in 2019 the development of NLP capability for use in Telefónica’s existing products, and an internal data science platform, were then productised for customers (see below discussion about its Aura product set).
  • As the number of products has expanded, the number of partnerships has also expanded, bringing specific platforms and capabilities which can be combined with Telefónica’s own data capabilities to provide added value (examples include CARTO which creates geographic visualisations of Telefónica’s data).
  • Looking at changing vertical priorities:
    • Telefónica has always been strong in the advertising sector, starting with products from O2 UK in 2012. The exact nature of what it has offered has changed over time and some capabilities have been sold, however, it still has a strong mobile marketing business and expects it data to become of more interest to brands/media agencies as the use of cookies diminishes across the next few years.
    • The retail sector offers opportunity, but has been challenging to target over the years. Although Telefónica has interesting data for retail companies, creating replicable products is challenging as the large retailers each have differing requirements and working with small cell data in-store can be expensive. The product set is therefore currently being simplified, as the pandemic has also reduced demand from retailers.

One of Telefónica’s key capabilities which is not clearly displayed in the timeline is the provision of services to the marketing teams of the various verticals it targets. These include analytics products which Telefónica has developed from its internal capabilities and other functionality such as pricing tools.

The formation of Telefónica Tech

In 2019, Telefónica LUCA became part of the newly formed, autonomous Telefónica Tech business unit. The organisation is split into two business areas: cybersecurity & cloud, and the assets from Telefónica LUCA combined with the IoT unit. The goal of Telefónica Tech is to:

  • Enable the financial markets to clearly see revenue progression. Telefónica’s stated aim is for sustained double digit growth, which it achieved with year-on-year growth of 13.6% in 2020, although the IoT and Big Data segment only grew 0.8% y-o-y in 2020, due to the impact of COVID-19 on IoT deployments, especially in retail. Showing signs of recovery, in H121 revenue growth in the IoT and Big Data segment rose to 8.1% y-o-y, and to 26% y-o-y for the whole of Telefónica Tech.
  • Coordinate innovation, particularly around post-pandemic opportunities such as remote working, e-health, e-commerce and digital transformation
  • Take advantage of global synergies and leveraging existing assets
  • Ease M&A and partnerships activity (it already has 300 partners to better reach new markets, including relations with 60 start-ups across products)
  • Build relationships with cloud providers (it has existing relationships with Microsoft, Google and SAP).

To better leverage existing assets, Telefónica LUCA was integrated with Telefónica’s IoT capabilities to create a more unified set of capabilities:

  1. IoT is seen as an enabling opportunity for AI, which can bring added value to Telefónica’s 10,000 IoT customers (with 35 million live IoT SIMs worldwide). Opportunities include provision of intelligence around “things” (for example, products to analyse sensor data) and then the addition of Business Insight services (i.e. analysis of aggregated, anonymised Telefónica data which adds further insight alongside the data coming from IoT devices).
  2. AI is now often a commodity discussion with C-Level prospects and Telefónica wishes to be seen as a strategic partner. Telefónica’s AI of Things proposition offers an execution layer and integration experts with security-by-design capabilities.
  3. Combining capabilities provides sales teams with an end-to-end value proposition, as the addition of AI is often complimentary to cloud transformation projects and the implementation of digital platforms.

There is a growing ecosystem in IoT and data which will generate more opportunities as both IoT solutions and ML/AI solutions mature, although it is not a straightforward decision for Telefónica on how to compete within this ecosystem.

Table of contents

  • Executive Summary
    • How successful has Telefónica been in data monetisation?
    • Learnings from Telefónica’s experience
    • Key success factors
    • Telefónica’s future strategy
  • Introduction
    • The origins of Telefónica Tech AI of Things
    • The formation of Telefónica Tech
  • Vision, mission and strategy
    • Scaling the business
    • Building a product set
    • Learnings from Telefónica Tech AI of Things
  • Organisational strategy
    • Where should the data monetisation team live?
    • Structure of Telefónica Tech AI of Things Team
    • External partnerships
    • Future plans
  • Data portfolio strategy
    • Tools and infrastructure
    • AI Suite
    • Vertical strategy
    • Product development beyond analytics
  • Conclusion and future moves

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How to identify and meet new customer needs

Customer-led innovation at Telia and Elisa

In order to secure competitive advantage and long-term growth, telcos need to identify and meet new customer needs. The importance of this is confirmed by the STL Partner’s Telco investment priorities survey published in January 2021. Understanding customer needs and innovation, both essential for addressing new needs and driving growth, featured in the top ten priorities.

Telco top investment  priorities

top-telco-investment-priorities-stl

Source:  STL Partners, Telecoms priorities: Ready for the crunch?

This report seeks to identify best practice for telcos. Through in-depth interviews with senior managers in Elisa and Telia, and an expert in disruptive innovation, we identify the critical success factors and lessons learned in these organisations.

Telia created Division X in 2017, a separate business unit focused on commercialising and growing revenue from emerging businesses and technologies such as IoT (including 5G), data insights, and digital B2C services. Its focus is on customer needs and speed of execution, to spearhead and accelerate innovation, which it deems necessary in Telia’s drive to “reinvent better connected living”.

International Digital Services is Elisa’s third main business division, alongside Consumer and Corporate, which serve the domestic market. As International Digital Services has matured, it has focussed specifically on addressing new needs and developing new services, in both industrial and corporate domains.

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The report is based on interviews with:

  • Liisa Puurunen, Vice President, Brand, CX and start-ups, International Digital Services, Elisa — Liisa has a background in leading new businesses and start-ups in Elisa in the Consumer division and International Digital Services. Liisa’s role is to understand where there are new needs to be met, and to get best practise in place across the whole customer journey, within both industrial and corporate domains.
  • Annukka Matilainen, Development Director for Omnichannel and Smart Automation, Elisa —Annukka led the Consumer team’s response to COVID-19
  • Stephanie Huf, Head of Marketing, Division X, Telia — Stephanie’s role is to support the business lines in Division X to in engaging with customers to identify their needs. For example, her team identifies what customers want, defines the value propositions and works with product and business teams to test these in line with customer insight. (Since participating in this research Stephanie Huf has moved to a new role.)
  • Anette Bohman, Strategy Director, Division X, Telia  — Anette supports and guides Division X in defining Telia’s future.
  • John McDonald, FIRSTEP — John is a strategist in disruptive innovation in the health industry in Canada. He helps leaders create alignment around how the forces of disruption are unfolding and where to place the bets. FIRSTEP works with health organisations searching for fresh insights that spark new opportunities for growth.

Create a separate team to maximise new business opportunities

A separate team has many benefits

New business requires a separate, dedicated team. Its needs are different from day-to-day business and it needs its own focus.

One of the biggest learnings for Elisa in addressing new opportunities, is that there needs to be a ‘sandbox team’ with its own resources and budgets, rules, methods and mindset. It must have access to senior managers for decision making and funding, and strong leadership.

The sandbox team needs to be remote from the demands of day-to-day operations and implementation. If finding new needs is only part of someone’s job it is difficult to manage, as short-term demands will inevitably take precedence. Delivery and experimentation are different functions and they should be separate.

Liisa Puurunen’s team is a start-up in its own right. It is leaner than the usual Elisa approach and people are only brought into the team when there is a test to be done, keeping it flexible.

Rationale for a separate team

separate-team-rationale
Source: STL Partners

Contents

  • Executive Summary
    • Create a dedicated and separate team
    • Take a customer centric approach at all stages of innovation
    • Types of innovation will meet different new needs
  • Introduction
  • Create a separate team to maximise new business opportunities
    • A separate team has many benefits
    • Telia Smart Family: The case for a separate innovations team
    • Evaluate success in relevant ways that may be non-traditional
  • Take a customer centric approach to all stages of innovation
    • Ensure a customer centric culture
    • Start with a customer problem
  • Meeting needs and scaling bets
    • Co-create with customers, but choose them carefully
    • Elisa’s empowered teams enable a successful response to COVID-19
  • Types of innovation to meet different new needs
    • New needs in the core versus new businesses
    • Dedicate some resource to extreme innovation
    • Telia Data Insights: New Business innovation in response to COVID-19
    • The case for disruptive innovation
  • Plan exit strategies
    • Perseverance and pivoting can bring success
    • Be prepared to kill your darlings

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Why the consumer IoT is stuck in the slow lane

A slow start for NB-IoT and LTE-M

For telcos around the world, the Internet of Things (IoT) has long represented one of the most promising growth opportunities. Yet for most telcos, the IoT still only accounts for a low single digit percentage of their overall revenue. One of the stumbling blocks has been relatively low demand for IoT solutions in the consumer market. This report considers why that is and whether low cost connectivity technologies specifically-designed for the IoT (such as NB-IoT and LTE-M) will ultimately change this dynamic.

NB-IoT and LTE-M are often referred to as Massive IoT technologies because they are designed to support large numbers of connections, which periodically transmit small amounts of data. They can be distinguished from broadband IoT connections, which carry more demanding applications, such as video content, and critical IoT connections that need to be always available and ultra-reliable.

The initial standards for both technologies were completed by 3GPP in 2016, but adoption has been relatively modest. This report considers the key B2C and B2B2C use cases for Massive IoT technologies and the prospects for widespread adoption. It also outlines how NB-IoT and LTE-M are evolving and the implications for telcos’ strategies.

This builds on previous STL Partners’ research, including LPWA: Which way to go for IoT? and Can telcos create a compelling smart home?. The LPWA report explained why IoT networks need to be considered across multiple generations, including coverage, reliability, power consumption, range and bandwidth. Cellular technologies tend to be best suited to wide area applications for which very reliable connectivity is required (see Figure below).

IoT networks should be considered across multiple dimensions

IoT-networks-disruptive-analysis-stl-2021
Source: Disruptive Analysis

 

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The smart home report outlined how consumers could use both cellular and short-range connectivity to bolster security, improve energy efficiency, charge electric cars and increasingly automate appliances. One of the biggest underlying drivers in the smart home sector is peace of mind – householders want to protect their properties and their assets, as rising population growth and inequality fuels fear of crime.

That report contended that householders might be prepared to pay for a simple and integrated way to monitor and remotely control all their assets, from door locks and televisions to solar panels and vehicles.  Ideally, a dashboard would show the status and location of everything an individual cares about. Such a dashboard could show the energy usage and running cost of each appliance in real-time, giving householders fingertip control over their possessions. They could use the resulting information to help them source appropriate insurance and utility supply.

Indeed, STL Partners believes telcos have a broad opportunity to help coordinate better use of the world’s resources and assets, as outlined in the report: The Coordination Age: A third age of telecoms. Reliable and ubiquitous connectivity is a key enabler of the emerging sharing economy in which people use digital technologies to easily rent the use of assets, such as properties and vehicles, to others. The data collected by connected appliances and sensors could be used to help safeguard a property against misuse and source appropriate insurance covering third party rentals.

Do consumers need Massive IoT?

Whereas some IoT applications, such as connected security cameras and drones, require high-speed and very responsive connectivity, most do not. Connected devices that are designed to collect and relay small amounts of data, such as location, temperature, power consumption or movement, don’t need a high-speed connection.

To support these devices, the cellular industry has developed two key technologies – LTE-M (LTE for Machines, sometimes referred to as Cat M) and NB-IoT (Narrowband IoT). In theory, they can be deployed through a straightforward upgrade to existing LTE base stations. Although these technologies don’t offer the capacity, throughput or responsiveness of conventional LTE, they do support the low power wide area connectivity required for what is known as Massive IoT – the deployment of large numbers of low cost sensors and actuators.

For mobile operators, the deployment of NB-IoT and LTE-M can be quite straightforward. If they have relatively modern LTE base stations, then NB-IoT can be enabled via a software upgrade. If their existing LTE network is reasonably dense, there is no need to deploy additional sites – NB-IoT, and to a lesser extent LTE-M, are designed to penetrate deep inside buildings. Still, individual base stations may need to be optimised on a site-by-site basis to ensure that they get the full benefit of NB-IoT’s low power levels, according to a report by The Mobile Network, which notes that operators also need to invest in systems that can provide third parties with visibility and control of IoT devices, usage and costs.

There are a number of potential use cases for Massive IoT in the consumer market:

  • Asset tracking: pets, bikes, scooters, vehicles, keys, wallets, passport, phones, laptops, tablets etc.
  • Vulnerable persontracking: children and the elderly
  • Health wearables: wristbands, smart watches
  • Metering and monitoring: power, water, garden,
  • Alarms and security: smoke alarms, carbon monoxide, intrusion
  • Digital homes: automation of temperature and lighting in line with occupancy

In the rest of this report we consider the key drivers and barriers to take-up of NB-IoT and LTE-M for these consumer use cases.

Table of Contents

  • Executive Summary
  • Introduction
  • Do consumers need Massive IoT?
    • The role of eSIMs
    • Takeaways
  • Market trends
    • IoT revenues: Small, but growing
  • Consumer use cases for cellular IoT
    • Amazon’s consumer IoT play
    • Asset tracking: Demand is growing
    • Connecting e-bikes and scooters
    • Slow progress in healthcare
    • Smart metering gains momentum
    • Supporting micro-generation and storage
    • Digital buildings: A regulatory play?
    • Managing household appliances
  • Technological advances
    • Network coverage
  • Conclusions: Strategic implications for telcos

 

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A3 for enterprise: Where should telcos focus?

A3 capabilities operators can offer enterprise customers

In this research we explore the potential enterprise solutions leveraging analytics, AI and automation (A3) that telcos can offer their enterprise customers. Our research builds on a previous STL Partners report Telco data monetisation: What’s it worth? which modelled the financial opportunity for telco data monetisation – i.e. purely the machine learning (ML) and analytics component of A3 – for 200+ use cases across 13 verticals.

In this report, we expand our analysis to include the importance of different types of AI and automation in implementing the 200+ use cases for enterprises and assess the feasibility for telcos to acquire and integrate those capabilities into their enterprise services.

We identified eight different types of A3 capabilities required to implement our 200+ use cases.

These capability types are organised below roughly in order of the number of use cases for which they are relevant (i.e. people analytics is required in the most use cases, and human learning is needed in the fewest).

The ninth category, Data provision, does not actually require any AI or automation skills beyond ML for data management, so we include it in the list primarily because it remains an opportunity for telcos that do not develop additional A3 capabilities for enterprise.

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Most relevant A3 capabilities across 200+ use cases

9-types-of-A3-analytics-AI-automation

Most relevant A3 capabilities for leveraging enterprise solutions

People analytics: This is the strongest opportunity for telcos as it uses their comprehensive customer data. Analytics and machine learning are required for segmentation and personalisation of messaging or action. Any telco with a statistically-relevant market share can create products – although specialist sales capabilities are still essential.

IoT analytics: Although telcos offering IoT products do not immediately have access to the payload data from devices, the largest telcos are offering a range of products which use analytics/ML to detect patterns or spot anomalies from connected sensors and other devices.

Other analytics: Similar to IoT, the majority of other analytics A3 use cases are around pattern or anomaly detection, where integration of telco data can increase the accuracy and success of A3 solutions. Many of the use cases here are very specific to the vertical. For example, risk management in financial services or tracking of electronic prescriptions in healthcare – which means that a telco will need to have existing products and sales capability in these verticals to make it worthwhile adding in new analytics or ML capabilities.

Real time: These use cases mainly need A3 to understand and act on triggers coming from customer behaviour and have mixed appeal to telcos. Telcos already play a significant role in a small number of uses cases, such as mobile marketing. Some telcos are also active in less mature use cases such as patient messaging in healthcare settings (e.g. real-time reminders to take medication or remote monitoring of vulnerable adults). Of the rest of the use cases that require real time automation, a subset could be enhanced with messaging. This would primarily be attractive to mobile operators, especially if they offer broader relevant enterprise solutions – for example, if a telco was involved in a connected public transport solution, then it could also offer passenger messaging.

Remote monitoring/control: Solutions track both things and people and use A3 to spot issues, do diagnostic analysis and prescribe solutions to the problems identified. The larger telcos already have solutions in some verticals, and 5G may bring more opportunities, such as monitoring of remote sites or traffic congestion monitoring.

Video analytics: Where telcos have CCTV implementations or video, there is opportunity to add in analytics solutions (potentially at the edge).

Human interactions: The majority of telco opportunities here relate to the provision of chatbots into enterprise contact centres.

Human learning: A group of low feasibility use cases around training (for example, an engineer on a manufacturing floor who uses a heads-up augmented/virtual reality (AR/VR) display to understand the resolution to a problem in front of them) or information provision (for example, providing retail customers with information via AR applications).

 

Table of Contents

  • Executive Summary
    • Which A3 capabilities should telcos prioritise?
    • What makes an investment worthwhile?
    • Next steps
  • Introduction
  • Vertical opportunities
    • Key takeaways
  • A3 technology: Where should telcos focus?
    • Key takeaways
    • Assessing the telco opportunity for nine A3 capabilities
  • Verizon case study
  • Details of vertical opportunities
  • Conclusion
  • Appendix 1 – full list of 200 use cases

 

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Telco A3: Skilling up for the long term

Telcos must master automation, analytics and AI (A3) skills to remain competitive

A3 will permeate all aspects of telcos’ and their customers’ operations, improving efficiency, customer experience, and the speed of innovation. Therefore, whether a telecoms operator is focused on its core connectivity business, or seeking to build new value beyond connectivity, developing widespread understanding of value of A3 and disseminating fundamental automation and AI skills across the organisation should be a core strategic goal. Our surveys on industry priorities suggest that operators recognise this need, and automation and AI are correspondingly rising up the agenda.

Expected technology priority change by organisation type, May 2020

technology investment priorities telecoms May 2020

*Updated January 2021 survey results will be published soon. Source: STL Partners survey, 222 respondents.

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Key findings on operators’ A3 strategies

Based on deep dive interviews with 8 telcos, as well as insights from 8 more telcos gathered from previous research programmes.

  • Less advanced telcos are creating a set of basic structures and procedures, as well as beginning to develop a single view of the customer
  • Having a single version of the truth appears to be an ongoing issue for all – alongside continued work on data quality
  • As full end-to-end automation is not a realistic goal for the next few years, interviewees were seeking to prioritise the right journeys to be automated in the short term
  • Reskilling and education of staff was an area of importance for many but not all
  • Just one company had less ambitious data-related aims due to the specialist nature of their services and smaller size of the company – saying that they worked with data on an as-needed basis and had no plans to develop dedicated data science headcount

Preparing for the future: There are four areas where A3 will impact telcos’ businesses

four A3 areas impacting telcos

Source: Charlotte Patrick Consult, STL Partners

In this report we outline the skills and capabilities telcos will need in order to navigate these changes. We break out these skills into four layers:

  1. The basic skillset: What operators need to remain competitive over the short term
  2. The next 5 years: The skills virtually all telcos will need to build or acquire to remain competitive in the medium term (exceptions include small or specialist telcos, or those in less competitive markets)
  3. The next 10 years: The skills and organisational changes telcos will need to achieve within a 10 year timeframe to remain competitive in the long term
  4. Beyond connectivity (5–10 year horizon): This includes A3 skills that telcos will need to be successful strategic partners for customers and suppliers, and to thrive in ecosystem business models. These will be essential for telcos seeking to play a coordination role in IoT, edge, or industry ecosystems.

Table of contents

  • Executive Summary
  • Telcos’ current strategic direction
    • Deep dive into 8 operator strategies
    • Overview of 8 more operator strategies
  • How A3 technologies are evolving
    • Deep dive into 40 A3 applications that will impact telcos’ businesses
    • Internal capabilities
    • Customer requirements
    • Technology changes
    • Organisational change
  • A timeline of telco A3 skills evolution
    • The basic skillset
    • The next 5 years
    • The next 10 years
    • Beyond connectivity

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DataSpark: Lessons on building a new telco (data) business

Data analytics as a new business

This case study looks at DataSpark, an autonomous business unit of Singtel (www.dsanalytics.com) and evaluates the benefits of creating a separate organisational structure within a telco to provide technology and support for the development of analytics, AI and automation as a new business. It is created after conversations with Shaowei Ying, Chief Operating Officer of DataSpark. The company’s activities include both the creation of internal capabilities and data monetisation capabilities for external customers.

DataSpark was formed in 2014 at a time when not many telcos were actively exploring new data business opportunities. The unit consisted of a small group of data professionals with skills around, particularly, location data. Singtel’s CEO was a strong supporter of leveraging telco data to establish competitive differentiation and therefore tasked them with looking at various location-related external monetisation opportunities. It was considered natural to create internal use cases for the data to defray the cost of the data preparation. In particular, the same mobility intelligence was of use to radio network planners optimising their network roll out using not just congestion, but now subscribers’ mobility patterns, too.

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DataSpark’s progress to date

Telcos’ external monetisation units, such as DataSpark, are not yet large enough to split out the revenues in their reports and accounts. However, in the 2018 and 2019 Management Discussion and Analysis DataSpark’s progress was reported to include:

  • Activity to bring mobility data to sectors such as transport and out-of-home media in Singapore and Australia
  • Partnership in out-of-home advertising with large players taking a data-as-a-service solution to optimise their assets
  • Provision of insights including first party enterprise data in the consumer goods sector to deliver new use cases in advertising and retail store inventory optimisation
  • Recent support for governments in predicting spread of Covid-19, including understanding the socio-economic impact of the virus.

Service example: COVID-19 insight for the Australian local government

COVID-19 data analytics innovation

Source: DataSpark

Table of Contents

  • Executive Summary
    • Two diverging strategies for a small, independent data unit
    • Scaling up the data business as an integrated unit
  • Introduction
    • DataSpark’s progress to date
  • DataSpark’s approach to building a data unit
    • What services does it offer?
    • Go-to-market: Different approaches for internal and external customers
    • Organisational structure: Where should a data unit go?
  • How to scale a data business?
    • The immediate growth opportunities
    • Following in others’ footsteps
    • Building new capabilities for external monetisation
  • Assessing future strategies for DataSpark
    • Scenario 1: Double down on internal data applications
    • Scenario 2: Continue building an independent business

 

Read more about STL Partners’ AI & automation research at stlpartners.com/ai-analytics-research/

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AI is starting to pay: Time to scale adoption

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AI adoption yields positive results

Over the last five years, telcos have made measurable progress in AI adoption and it is starting to pay off.  When compared to all industries, telcos have become adept at handling large data sets and implementing automation. Over the last several years the telecoms industry has gone from not knowing where or how to implement AI, to having developed and implemented hundreds of AI and automation applications for network operations, fraud prevention, customer channel management, and sales and marketing. We have discussed these use cases and operator strategies and opportunities in detail in previous reports.

For the more advanced telcos, the challenge is no longer setting up data management platforms and systems and identifying promising use cases for AI and automation, but overcoming the organisational and cultural barriers to becoming truly data-centric in mindset, processes and operations. A significant part of this challenge includes disseminating AI adoption and expertise of these technologies and associated skills to the wider organisation, beyond a centralised AI team.The benchmark for success here is not other telcos, or companies in other industries with large legacy and physical assets, but digital- and cloud-native companies that have been established with a data-centric mindset and practices from the start. This includes global technology companies like Microsoft, Google and Amazon, who increasingly see telecoms operators as customers, or perhaps even competitors one day, as well as greenfield players such as Rakuten, Jio and DISH, which as well as more modern networks have fewer ingrained legacy processes and cultural practices to overcome.

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Telecoms has a high AI adoption rate compared with other industries

AI pays off

Source: McKinsey

In this report, we assess several telcos’ approach to AI and the results they have achieved so far, and draw some lessons on what kind of strategy and ambition leads to better results. In the second section of the report, we explore in more detail the concrete steps telcos can take to help accelerate and scale the use of AI and automation across the organisation, in the hopes of becoming more data-driven businesses.

While not all telcos have an ambition to drive new revenue growth through development of their own IP in AI, to form the basis of new enterprise or consumer services, all operators will need AI to permeate their internal processes to compete effectively in the long term. Therefore, whatever the level ambition, disseminating fundamental AI and data skills across the organisation is crucial to long term success. STL Partners believes that the sooner telcos can master these skills, the higher their chances of successfully applying them to drive innovation both in core connectivity and new services higher up the value chain.

Contents

  • Executive Summary
  • Introduction
  • Developing an AI strategy: What is it for?
    • Telefónica: From AURA and LUCA to Telefónica Tech
    • Vodafone: An efficiency focused strategy
    • Elisa: A vertical application approach
    • Takeaways: Comparing three approaches
  • AI maturity progression
    • Adopt big data analytics: The basic building blocks
    • Creating a centralised AI unit
    • Creating a new business unit
    • Disseminating AI across the organisation
  • Using partnerships to accelerate and scale AI
    • O2 and Cardinality
    • AT&T Acumos
  • Conclusion and recommendations
  • Index

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SK Telecom: Lessons in 5G, AI, and adjacent market growth

SK Telecom’s strategy

SK Telecom is the largest mobile operator in South Korea with a 42% share of the mobile market and is also a major fixed broadband operator. It’s growth strategy is focused on 5G, AI and a small number of related business areas where it sees the potential for revenue to replace that lost from its core mobile business.

By developing applications based on 5G and AI it hopes to create additional revenue streams both for its mobile business and for new areas, as it has done in smart home and is starting to do for a variety of smart business applications. In 5G it is placing an emphasis on indoor coverage and edge computing as basis for vertical industry applications. Its AI business is centred around NUGU, a smart speaker and a platform for business applications.

Its other main areas of business focus are media, security, ecommerce and mobility, but it is also active in other fields including healthcare and gaming.

The company takes an active role internationally in standards organisations and commercially, both in its own right and through many partnerships with other industry players.

It is a subsidiary of SK Group, one of the largest chaebols in Korea, which has interests in energy and oil. Chaebols are large family-controlled conglomerates which display a high level and concentration of management power and control. The ownership structures of chaebols are often complex owing to the many crossholdings between companies owned by chaebols and by family members. SK Telecom uses its connections within SK Group to set up ‘friendly user’ trials of new services, such as edge and AI

While the largest part of the business remains in mobile telecoms, SK Telecom also owns a number of subsidiaries, mostly active in its main business areas, for example:

  • SK Broadband which provides fixed broadband (ADSL and wireless), IPTV and mobile OTT services
  • ADT Caps, a securitybusiness
  • IDQ, which specialises in quantum cryptography (security)
  • 11st, an open market platform for ecommerce
  • SK Hynixwhich manufactures memory semiconductors

Few of the subsidiaries are owned outright by SKT; it believes the presence of other shareholders can provide a useful source of further investment and, in some cases, expertise.

SKT was originally the mobile arm of KT, the national operator. It was privatised soon after establishing a cellular mobile network and subsequently acquired by SK Group, a major chaebol with interests in energy and oil, which now has a 27% shareholding. The government pension service owns a 11% share in SKT, Citibank 10%, and 9% is held by SKT itself. The chairman of SK Group has a personal holding in SK Telecom.

Following this introduction, the report comprises three main sections:

  • SK Telecom’s business strategy: range of activities, services, promotions, alliances, joint ventures, investments, which covers:
    • Mobile 5G, Edge and vertical industry applications, 6G
    • AIand applications, including NUGU and Smart Homes
    • New strategic business areas, comprising Media, Security, eCommerce, and other areas such as mobility
  • Business performance
  • Industrial and national context.

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Overview of SKT’s activities

Network coverage

SK Telecom has been one of the earliest and most active telcos to deploy a 5G network. It initially created 70 5G clusters in key commercial districts and densely populated areas to ensure a level of coverage suitable for augmented reality (AR) and virtual reality (VR) and plans to increase the number to 240 in 2020. It has paid particular attention to mobile (or multi-access) edge computing (MEC) applications for different vertical industry sectors and plans to build 5G MEC centres in 12 different locations across Korea. For its nationwide 5G Edge cloud service it is working with AWS and Microsoft.

In recognition of the constraints imposed by the spectrum used by 5G, it is also working on ensuring good indoor 5G coverage in some 2,000 buildings, including airports, department stores and large shopping malls as well as small-to-medium-sized buildings using distributed antenna systems (DAS) or its in-house developed indoor 5G repeaters. It also is working with Deutsche Telekom on trials of the repeaters in Germany. In addition, it has already initiated activities in 6G, an indication of the seriousness with which it is addressing the mobile market.

NUGU, the AI platform

It launched its own AI driven smart speaker, NUGU in 2016/7, which SKT is using to support consumer applications such as Smart Home and IPTV. There are now eight versions of NUGU for consumers and it also serves as a platform for other applications. More recently it has developed several NUGU/AI applications for businesses and civil authorities in conjunction with 5G deployments. It also has an AI based network management system named Tango.

Although NUGU initially performed well in the market, it seems likely that the subsequent launch of smart speakers by major global players such as Amazon and Google has had a strong negative impact on the product’s recent growth. The absence of published data supports this view, since the company often only reports good news, unless required by law. SK Telecom has responded by developing variants of NUGU for children and other specialist markets and making use of the NUGU AI platform for a variety of smart applications. In the absence of published information, it is not possible to form a view on the success of the NUGU variants, although the intent appears to be to attract young users and build on their brand loyalty.

It has offered smart home products and services since 2015/6. Its smart home portfolio has continually developed in conjunction with an increasing range of partners and is widely recognised as one of the two most comprehensive offerings globally. The other being Deutsche Telekom’s Qivicon. The service appears to be most successful in penetrating the new build market through the property developers.

NUGU is also an AI platform, which is used to support business applications. SK Telecom has also supported the SK Group by providing new AI/5G solutions and opening APIs to other subsidiaries including SK Hynix. Within the SK Group, SK Planet, a subsidiary of SK Telecom, is active in internet platform development and offers development of applications based on NUGU as a service.

Smart solutions for enterprises

SKT continues to experiment with and trial new applications which build on its 5G and AI applications for individuals (B2C), businesses and the public sector. During 2019 it established B2B applications, making use of 5G, on-prem edge computing, and AI, including:

  • Smart factory(real time process control and quality control)
  • Smart distribution and robot control
  • Smart office (security/access control, virtual docking, AR/VRconferencing)
  • Smart hospital (NUGUfor voice command for patients, AR-based indoor navigation, facial recognition technology for medical workers to improve security, and investigating possible use of quantum cryptography in hospital network)
  • Smart cities; e.g. an intelligent transportation system in Seoul, with links to vehicles via 5Gor SK Telecom’s T-Map navigation service for non-5G users.

It is too early to judge whether these B2B smart applications are a success, and we will continue to monitor progress.

Acquisition strategy

SK Telecom has been growing these new business areas over the past few years, both organically and by acquisition. Its entry into the security business has been entirely by acquisition, where it has bought new revenue to compensate for that lost in the core mobile business. It is too early to assess what the ongoing impact and success of these businesses will be as part of SK Telecom.

Acquisitions in general have a mixed record of success. SK Telecom’s usual approach of acquiring a controlling interest and investing in its acquisitions, but keeping them as separate businesses, is one which often, together with the right management approach from the parent, causes the least disruption to the acquired business and therefore increases the likelihood of longer-term success. It also allows for investment from other sources, reducing the cost and risk to SK Telecom as the acquiring company. Yet as a counterpoint to this, M&A in this style doesn’t help change practices in the rest of the business.

However, it has also shown willingness to change its position as and when appropriate, either by sale, or by a change in investment strategy. For example, through its subsidiary SK Planet, it acquired Shopkick, a shopping loyalty rewards business in 2014, but sold it in 2019, for the price it paid for it. It took a different approach to its activity in quantum technologies, originally set up in-house in 2011, which it rolled into IDQ following its acquisition in 2018.

SKT has also recently entered into partnerships and agreements concerning the following areas of business:

 

Table of Contents

  • Executive Summary
  • Introduction and overview
    • Overview of SKT’s activities
  • Business strategy and structure
    • Strategy and lessons
    • 5G deployment
    • Vertical industry applications
    • AI
    • SK Telecom ‘New Business’ and other areas
  • Business performance
    • Financial results
    • Competitive environment
  • Industry and national context
    • International context

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Fixed wireless access growth: To 20% homes by 2025

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Fixed wireless access growth forecast

Fixed Wireless Access (FWA) networks use a wireless “last mile” link for the final connection of a broadband service to homes and businesses, rather than a copper, fibre or coaxial cable into the building. Provided mostly by WISPs (Wireless Internet Service Providers) or mobile network operators (MNOs), these services come in a wide range of speeds, prices and technology architectures.

Some FWA services are just a short “drop” from a nearby pole or fibre-fed hub, while others can work over distances of several kilometres or more in rural and remote areas, sometimes with base station sites backhauled by additional wireless links. WISPs can either be independent specialists, or traditional fixed/cable operators extending reach into areas they cannot economically cover with wired broadband.

There is a fair amount of definitional vagueness about FWA. The most expansive definitions include cheap mobile hotspots (“Mi-Fi” devices) used in homes, or various types of enterprise IoT gateway, both of which could easily be classified in other market segments. Most service providers don’t give separate breakouts of deployments, while regulators and other industry bodies report patchy and largely inconsistent data.

Our view is that FWA is firstly about providing permanent broadband access to a specific location or premises. Primarily, this is for residential wireless access to the Internet and sometimes typical telco-provided services such as IPTV and voice telephony. In a business context, there may be a mix of wireless Internet access and connectivity to corporate networks such as VPNs, again provided to a specific location or building.

A subset of FWA relates to M2M usage, for instance private networks run by utility companies for controlling grid assets in the field. These are typically not Internet-connected at all, and so don’t fit most observers’ general definition of “broadband access”.

Usually, FWA will be marketed as a specific service and package by some sort of network provider, usually including the terminal equipment (“CPE” – customer premise equipment), rather than allowing the user to “bring their own” device. That said, lower-end (especially 4G) offers may be SIM-only deals intended to be used with generic (and unmanaged) portable hotspots.
There are some examples of private network FWA, such as a large caravan or trailer park with wireless access provided from a central point, and perhaps in future municipal or enterprise cellular networks giving fixed access to particular tenant structures on-site – for instance to hangars at an airport.

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FWA today

Today, fixed-wireless access (FWA) is used for perhaps 8-9% of broadband connections globally, although this varies significantly by definition, country and region. There are various use cases (see below), but generally FWA is deployed in areas without good fixed broadband options, or by mobile-only operators trying to add an additional fixed revenue stream, where they have spare capacity.

Fixed wireless internet access fits specific sectors and uses, rather than the overall market

FWA Use Cases

Source: STL Partners

FWA has traditionally been used in sparsely populated rural areas, where the economics of fixed broadband are untenable, especially in developing markets without existing fibre transport to towns and villages, or even copper in residential areas. Such networks have typically used unlicensed frequency bands, as there is limited interference – and little financial justification for expensive spectrum purchases. In most cases, such deployments use proprietary variants of Wi-Fi, or its ill-fated 2010-era sibling WiMAX.

Increasingly however, FWA is being used in more urban settings, and in more developed market scenarios – for example during the phase-out of older xDSL broadband, or in places with limited or no competition between fixed-network providers. Some cellular networks primarily intended for mobile broadband (MBB) have been used for fixed usage as well, especially if spare capacity has been available. 4G has already catalysed rapid growth of FWA in numerous markets, such as South Africa, Japan, Sri Lanka, Italy and the Philippines – and 5G is likely to make a further big difference in coming years. These mostly rely on licensed spectrum, typically the national bands owned by major MNOs. In some cases, specific bands are used for FWA use, rather than sharing with normal mobile broadband. This allows appropriate “dimensioning” of network elements, and clearer cost-accounting for management.

Historically, most FWA has required an external antenna and professional installation on each individual house, although it also gets deployed for multi-dwelling units (MDUs, i.e. apartment blocks) as well as some non-residential premises like shops and schools. More recently, self-installed indoor CPE with varying levels of price and sophistication has helped broaden the market, enabling customers to get terminals at retail stores or delivered direct to their home for immediate use.

Looking forward, the arrival of 5G mass-market equipment and larger swathes of mmWave and new mid-band spectrum – both licensed and unlicensed – is changing the landscape again, with the potential for fibre-rivalling speeds, sometimes at gigabit-grade.

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Table of contents

  • Executive Summary
  • Introduction
    • FWA today
    • Universal broadband as a goal
    • What’s changed in recent years?
    • What’s changed because of the pandemic?
  • The FWA market and use cases
    • Niche or mainstream? National or local?
    • Targeting key applications / user groups
  • FWA technology evolution
    • A broad array of options
    • Wi-Fi, WiMAX and close relatives
    • Using a mobile-primary network for FWA
    • 4G and 5G for WISPs
    • Other FWA options
    • Customer premise equipment: indoor or outdoor?
    • Spectrum implications and options
  • The new FWA value chain
    • Can MNOs use FWA to enter the fixed broadband market?
    • Reinventing the WISPs
    • Other value chain participants
    • Is satellite a rival waiting in the wings?
  • Commercial models and packages
    • Typical pricing and packages
    • Example FWA operators and plans
  • STL’s FWA market forecasts
    • Quantitative market sizing and forecast
    • High level market forecast
  • Conclusions
    • What will 5G deliver – and when and where?
  • Index

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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The future of assurance: How to deliver quality of service at the edge

Why does edge assurance matter?

The assurance of telecoms networks is one of the most important application areas for analytics, automation and AI (A3) across telcos operations. In a previous report estimating the potential value of A3 across telcos’ core business, including networks, customer channels, sales and marketing, we estimated that service assurance accounts for nearly 10% of the total potential value of A3 (see the report A3 for telcos: Mapping the financial value). The only area of greater combined value was in resource management across telecoms existing networks and planned deployments.

Within service assurance, the biggest value buckets are self-healing networks, impact on customer experience and churn, and dynamic SLA management. This estimate was developed through a bottom up analysis of specific applications for automation, analytics and AI within each segment, and their potential to deliver cost savings or revenue uplift for an average sized telecoms operator (see the original report for the full methodology).

Breakdown of the value of A3 in service assurance, US$ millions

Breakdown of the value of A3 in service assurance (US$ millions)

Source: STL Partners, Charlotte Patrick Consult

While this previous research demonstrates there is significant value for telcos in improving assurance on their legacy networks, over the next five years edge assurance will become an increasingly important topic for operators.

What we mean by edge assurance is the new capabilities operators will require to enable visibility across much more distributed, cloud-based networks, and monitoring of a wider and more dynamic range of services and devices, in order to deliver high quality experience and self-healing networks. This need is driven by operators’ accelerating adoption of virtualisation and software-defined networking, for example with increasing experimentation and excitement around open RAN, as well as some operators’ ambitions to play a significant role in the edge computing market (see our report Telco edge computing: How to partner with hyperscalers for analysis of telcos’ ambitions in edge computing).

To give an idea of the scale of the challenge ahead of operators in assuring increasingly distributed network functions and infrastructure, STL Partners’ expects a Tier-1 operator will deploy more than 8,000 edge servers to support virtual RAN by 2025 (see Building telco edge infrastructure: MEC, private LTE and vRAN for the full forecasts).

Forecast of Tier 1 operator edge servers by domain

Forecast of Tier-1 operator edge servers by domain

Source: STL Partners

Given this dramatic shift in network operations, without new edge assurance capabilities:

  • A telco will not be able to understand where issues are occurring across the (virtualised) network and the underlying infrastructure, and diagnose the root cause
  • The promises of cost saving and better customer experience from self-healing networks will not be fully realised in next-generation networks
  • Potential revenue generators such as network slicing and URLLC will be of limited value to customers if the telco can’t offer sufficient SLAs on reliability, latency and visibility
  • It will not be possible to make promises to ecosystem partners around service quality.

Despite the significant number of unknowns in the future of telco activities around 5G, IoT and edge computing, this research ventures a framework to allow telcos to plan for their future service assurance needs. The first section describes the drivers affecting telcos decision-making around the types of assurance that they need at the edge. The second sets out products and capabilities that will be required and types of assurance products that telcos could create and monetise.

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Table of contents

  • Executive Summary
    • The three main telco strategies in edge assurance
    • What exactly do telcos need to assure?
  • Why edge assurance matters
  • Factors affecting edge assurance development
    • What are telcos measuring?
    • Internal assurance applications
    • Location of measurement and analysis
    • Ownership status of equipment and assets being assured
    • Requirements of external assurance users
    • Requirements from specific applications
    • Telco business model
  • The status of edge assurance and recommendations for telcos
    • Edge assurance vendors
    • Telco assurance products
  • Appendix

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Reliance Unlimit: How to build a successful IoT ecosystem

Reliance Unlimit’s success so far

Unlimit, Reliance Jio’s standalone IoT business in India, established in 2016, understood from the start that the problem with the IoT wasn’t the availability of technology, but how to quickly pull it all together into a clear, affordable solutions for the end customer. The result is that less than four years later, it has deployed more than 35,000 end-to-end IoT projects for a prestigious portfolio of customers, including Nissan Motor, MG Motor, Bata, DHL, GSK and Unilever. To meet their varying and evolving needs, Unlimit had built a IoT ecosystem of almost 600 partner companies by the end of 2019. Of these, nearly 100 are fully certified partners, with which Unlimit co-innovates solutions tailored to the Indian market.

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The state of the IoT: Balancing cost and complexity

In 1968, Theodore Paraskevakos, a Greek American inventor and businessman, explored the idea of making two machines communicate to each other. He first developed a system for transmitting the caller’s number to the receiver’s device. Building on this experiment, in 1977 he founded Metretek Inc, a company that conducted commercial automatic meter reading, which is essentially today’s commercial smart meter. From then, the world of machine to machine communications (M2M) developed rapidly. The objective was mainly to remotely monitor devices in order to understand conditions and performance. The M2M world was strongly telecommunications-oriented and focused on solving specific business problems. Given this narrow focus, there was little diversity in devices, data sets were specific to one or two measurements, and the communications protocols were well known. Given this context, it is fair to describe first-generation M2M solutions as a siloed, with little – if any – interaction with other data and solutions.

The benefits and challenges of the IoT

The purpose of the Internet of Things (IoT) is to open those silos and incorporate solution designers and developers into the operating environment. In this evolved environment, there might be several applications and solutions, each delivering a unique operational benefit. Each of those solutions require different devices, which produce different data. And those devices require life cycle management, the data needs to be analysed to inform better decisions, and automation integrated to improve efficiency in the operational environment. The communication methods between those devices can also vary significantly, depending on the environment, where the data is, and the type of applications and intelligence required. Finally, all this needs to run securely.

Therefore, the IoT has opened the silos, but it has brought complexity. The question is then whether this complexity is worth it for the operational benefits.

There are several studies highlighting the advantages of IoT solutions. The recent Microsoft IoT Signals publication, which surveys over 3000 decision makers in companies operating across different sectors, clearly demonstrates the value that IoT is bringing to organisations. The top three benefits are:

  • 91% of respondents claim that the IoT has increased efficiency
  • 91% of respondents claim that the IoT has increased yield
  • 85% of respondents claim that the IoT has increased quality.

The sectors leading IoT adoption

The same study highlights how these benefits are materialising in different business sectors. According to this study – and many others – manufacturing is seen as a top adopter of IoT solutions, as also highlighted in STL Partners research on the Industrial IoT.

Automotive, supply chain and logistics are other sectors that have widely adopted the IoT. Their leadership comes from a long M2M heritage, since telematics was a core application of M2M, and is an important part of the supply chain and logistics process.

The automotive sector’s early adoption of IoT was also driven by regulatory initiatives in different parts of the world, for instance to support remotely monitored emergency services in case of accidents (e.g. EU eCall). To enable this, M2M SIMs were embedded in cars, and only activated in the case of an accident, sending a message to an emergency centre. From there, the automotive industry and mobile network operators gradually developed a broader range of applications, culminating in the concept of connected cars. The connected car is much more sophisticated than a single emergency SIM – it is an IoT environment in which an array of sensors is gathering different data, sharing that data externally in various forms of V2X settings, supporting in-vehicle infotainment, and also enabling semiautonomous mobility. Sometime in the future, this will mature into fully autonomous mobility.

The complexity of an IoT solution

The connected car clearly represents the evolution from siloed M2M solutions to the IoT with multiple interdependent data sources and solutions. Achieving this has required the integration of various technologies into an IoT architecture, as well as the move towards automation and prediction of events, which requires embedding advanced analytics and AI technology frameworks into the IoT stack.

High level view of an IoT architecture

Overview of IoT architecture

Source: Saverio Romeo, STL Partners

There are five levels on an IoT architecture:

  1. The hardware level includes devices, sensors, gateways and hardware development components such as microcontrollers.
  2. The communication level includes the different types of IoT connectivity (cellular, LP-WAN, fixed, satellite, short-range wireless and others) and the communication protocols used in those forms of connectivity.
  3. The middleware software backend level is a set of software layers that are traditionally called an IoT platform. A high-level breakdown of the IoT platform includes a connectivity management layer, a device management layer, and data management and orchestration, data analytics and visualisations layers.
  4. The application level includes application development enablement tools and the applications themselves. Those tools enable the development of applications using machine-generated data and various other sources of data –all integrated by the IoT platform. It also includes applications that use results of these analytics to enable remote and automated actions on IoT devices.
  5. Vertically across these levels, there is a security layer. Although this is simplified into a single vertical layer, in practice there are separate security features integrated into IoT solutions at each layer of the architecture. Those features work together to offer layer-to-layer and end-to-end security. This is a complex process that required a detailed use of security-by-design methodology.

The IoT architecture is therefore composed of different technological parts that need to be integrated in order to work correctly in the different circumstances of potential deployment. The IoT architecture also needs to enable scalability supporting the expansion of a solution in terms of number of devices and volume and types of data. Each architectural layer is essential for the IoT solution to work, and they must interact with each other harmoniously, but each requires different technological expertise and skills.

An organisation that wants to offer end-to-end IoT solutions must therefore make a strategic choice between “in-house” IoT architecture development, or form strategic partnerships with existing IoT technology platform providers, and integrate their solutions into a coherent architecture to support an IoT ecosystem.

In the following sections of this report, we discuss Unlimit’s decision to take an ecosystem approach to building its IoT business, and the steps it took to get where it is today.

Table of contents

  • Executive Summary
    • Four lessons from Unlimit on building IoT ecosystems
    • How Unlimit built a successful IoT ecosystem
    • What next?
  • The state of the IoT: Balancing cost and complexity
    • The benefits and challenges of the IoT
    • The sectors leading IoT adoption
    • The complexity of an IoT solution
    • The nature of business ecosystems
  • How Unlimit built a successful IoT business
    • So far, Unlimit looks like a success
    • How will Unlimit sustain leadership and growth?
  • Lessons from Unlimit’s experience

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Telco data monetisation: What is it worth?

Data revenue opportunities are variable

Monetisation of telco data has been an area of activity for the last six years. However, telcos’ interest levels have varied over time due to the complexity of delivering and selling such a diverse range of products, as well as highly variable revenue opportunities depending on the vertical. Telcos’ appetite to pursue data monetisation has also been heavily impacted by the fortunes of other new telco products, in particular IoT, owing to the link between many data/analytics products and IoT solutions.

This report assesses the opportunity for telcos to monetise their data and provide associated data analytics products in two parts:

  1. First, we look at the range of products and services a telco needs to create in order to deliver financial value.
  2. Then, we explore the main use cases and actual financial value of telco data analytics products across 12 verticals, plus horizontal solutions that apply to multiple verticals.

Telco data monetisation: Calculation methodology

The methodology used to model the financial value of telco data analytics is outlined in the figure below.

  • The starting point for this analysis is 210 data or data analytics use cases, spread across 12 verticals and the horizontal solutions applicable to multiple verticals.
  • We then assess how difficult it is for a telco to address each use case, based on pre-requisite supporting platforms and solutions, regulatory constraints, etc. (shown in red). This evaluation enables us to assess how likely telcos are to develop products for each use case.
  • Thirdly, we assess which types of telco are able to develop the use case (in yellow). For example, telcos in a market with particularly restrictive regulation around use of personal data are simply not able to create certain products.
  • Finally, it is necessary to understand whether the data/analytics products created for a use case can be offered as an independent, standalone product, or more likely to be provided as a bolt-on service to another, pre-existing solution. This question is primarily pertinent in the IoT space where basic data/analytics are likely to be included in the price of the IoT service.
    • For products that we expect to be sold independently, we calculate the potential revenue based on estimated pricing for the type of data product, where known, and likely volumes that a telco will sell in a year.
    • For data analytics products closely linked to IoT, we attach no monetary value.

Calculation methodology for the feasibility and value of telco data monetisation use cases

Rationale behind data monetisation potential

Source: STL Partners, Charlotte Patrick Consult

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Viewing the data

Underlying the analysis in this report is a database tool including a detailed assessment of each of the 210 data monetisation use cases we have identified, with numerical analysis and charting capabilities. We know many of our readers will be interested to explore the detailed data, and so have made it available for download on the website in the form of an Excel spreadsheet.

Full use case database and analysis available on our website

Source: STL Partners

Table of Contents

  • Executive Summary
  • Introduction
    • Calculation methodology
  • What is this market worth to telcos?
  • Creating products for data monetisation
    • Telco products for the ecosystem
    • Data and analytics for IoT
    • Use of location in data monetisation
  • Maximising value in different verticals
    • Advertising and market research
    • Agriculture
    • Finance
    • Government
    • Insurance
    • Healthcare
    • Manufacturing
    • Real estate and construction
    • Retail
    • Telecom, media and technology
    • Transportation
    • Utilities
    • Horizontal solutions for all verticals
  • Conclusion and recommendations
    • How to pick a winning project
  • Index

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Telco ecosystems: How to make them work

The ecosystem business framework

The success of large businesses such as Microsoft, Amazon and Google as well as digital disrupters like Airbnb and Uber is attributed to their adoption of platform-enabled ecosystem business frameworks. Microsoft, Amazon and Google know how to make ecosystems work. It is their ecosystem approach that helped them to scale quickly, innovate and unlock value in opportunity areas where businesses that are vertically integrated, or have a linear value chain, would have struggled. Internet-enabled digital opportunity areas tend to be unsuited to the traditional business frameworks. These depend on having the time and the ability to anticipate needs, plan and execute accordingly.

As businesses in the telecommunications sector and beyond try to emulate the success of these companies and their ecosystem approach, it is necessary to clarify what is meant by the term “ecosystem” and how it can provide a framework for organising business.

The word “ecosystem” is borrowed from biology. It refers to a community of organisms – of any number of species – living within a defined physical environment.

A biological ecosystem

The components of a biological ecosystem

Source: STL Partners

A business ecosystem can therefore be thought of as a community of stakeholders (of different types) that exist within a defined business environment. The environment of a business ecosystem can be small or large.  This is also true in biology, where both a tree and a rainforest can equally be considered ecosystem environments.

The number of organisms within a biological community is dynamic. They coexist with others and are interdependent within the community and the environment. Environmental resources (i.e. energy and matter) flow through the system efficiently. This is how the ecosystem works.

Companies that adopt an ecosystem business framework identify a community of stakeholders to help them address an opportunity area, or drive business in that space. They then create a business environment (e.g. platforms, rules) to organise economic activity among those communities.  The environment integrates community activities in a complementary way. This model is consistent with STL Partners’ vision for a Coordination Age, where desired outcomes are delivered to customers by multiple parties acting together.

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Characteristics of business ecosystems that work

In the case of Google, it adopted an ecosystem approach to tackle the search opportunity. Its search engine platform provides the environment for an external stakeholder community of businesses to reach consumers as they navigate the internet, based on what consumers are looking for.

  • Google does not directly participate in the business-consumer transaction, but its platform reduces friction for participants (providing a good customer experience) and captures information on the exchange.

While Google leverages a technical platform, this is not a requirement for an ecosystem framework. Nespresso built an ecosystem around its patented coffee pod. It needed to establish a user-base for the pods, so it developed a business environment that included licensing arrangements for coffee machine manufacturers.  In addition, it provided support for high-end homeware retailers to supply these machines to end-users. It also created the online Nespresso Club for coffee aficionados to maintain demand for its product (a previous vertically integrated strategy to address this premium coffee-drinking niche had failed).

Ecosystem relevance for telcos

Telcos are exploring new opportunities for revenue. In many of these opportunities, the needs of the customer are evolving or changeable, budgets are tight, and time-to-market is critical. Planning and executing traditional business frameworks can be difficult under these circumstances, so ecosystem business frameworks are understandably of interest.

Traditional business frameworks require companies to match their internal strengths and capabilities to those required to address an opportunity. An ecosystem framework requires companies to consider where those strengths and capabilities are (i.e. external stakeholder communities). An ecosystem orchestrator then creates an environment in which the stakeholders contribute their respective value to meet that end. Additional end-user value may also be derived by supporting stakeholder communities whose products and services use, or are used with, the end-product or service of the ecosystem (e.g. the availability of third party App Store apps add value for end customers and drives demand for high end Apple iPhones). It requires “outside-in” strategic thinking that goes beyond the bounds of the company – or even the industry (i.e. who has the assets and capabilities, who/what will support demand from end-users).

Many companies have rushed to implement ecosystem business frameworks, but have not attained the success of Microsoft, Amazon or Google, or in the telco arena, M-Pesa. Telcos require an understanding of the rationale behind ecosystem business frameworks, what makes them work and how this has played out in other telco ecosystem implementations. As a result, they should be better able to determine whether to leverage this approach more widely.

Table of Contents

  • Executive Summary
  • The ecosystem business framework
  • Why ecosystem business frameworks?
    • Benefits of ecosystem business frameworks
  • Identifying ecosystem business frameworks
  • Telco experience with ecosystem frameworks
    • AT&T Community
    • Deutsche Telekom Qivicon
    • Telecom Infra Project (TIP)
    • GSMA Mobile Connect
    • Android
    • Lessons from telco experience
  • Criteria for successful ecosystem businesses
    • “Destination” status
    • Strong assets and capabilities to share
    • Dynamic strategy
    • Deep end-user knowledge
    • Participant stakeholder experience excellence
    • Continuous innovation
    • Conclusions
  • Next steps
    • Index

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