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

Related Research

 

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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

Related research

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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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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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