What do enterprises want from telcos?

Enterprises are striving for success…

All enterprises want success. The language and specifics that define this may differ across sectors – but the underlying drivers are the same. They include financial, strategic, operational and market-facing factors, as described below.

Success drivers

enterprise

Source: STL Partners

…against a new, transformed backdrop

Demand and supply forces have changed: Customers expect more, but resources are increasingly constrained. Enterprises are pondering the range of new technologies and practices to help them meet the challenges of a Coordination Age:

  • Coordinating outcomes and experiences for customers
  • Collaborating to enable the delivery of more value
  • Bridging the digital and physical worlds

The Coordination Age

Enterprise

Source: STL Partners

Telcos’ national scope and assets mean they are well placed to participate in some of the new opportunity areas of the Coordination Age. Although technologies and applications running over the telcos’ connectivity are often developed at global scale, how they are implemented within local and national markets is likely to vary from one country to the next, owing to regulatory constraints and how these have shaped the structure and priorities of the market. Telcos can help enterprises navigate this path.

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Do enterprises believe telcos can help?

What enterprises think of telcos depends on their tech maturity, their knowledge and experience of telcos, the telcos’ technology capability and the sector that they are in, as shown below.

Factors influencing enterprise consideration

 

enterprisesSource: STL Partners

Telcos must work to understand enterprise needs in their specific markets and how they are best placed to serve those needs.

Table of contents

  • Executive summary
  • Introduction
  • Understanding telco enterprise strategies
  • Seven enterprise growth opportunities

Related research

STL Partners has a research solution focused on growing enterprise revenues. Reports that could be of interest include:

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The data-driven telco: How to progress

Becoming data-driven is an evolving journey

Telcos have started on the path to leveraging data more fully but techniques, technologies and their implications are continuously emerging and evolving – posing new opportunities and challenges for the teams responsible for plotting their course.

Although somewhat overused, the “data-driven” refrain provides a banner under which the Chief Data Officer (CDO) and other teams throughout the telco can remind the organisation of the importance of the work that they are doing.  As new technologies become available and capabilities such as automation progress in their sophistication, there will continue to be a steady stream of demands on the data team from across the organisation.  There will also be an increase in demand from outside the organization as telcos begin to play in multiple new ecosystems.

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STL Partners conducted primary and secondary research to determine the current priorities for telcos that have progressed some way down the data-driven track.  During our primary research, we spoke to four Chief Data Officers (CDOs) – or equivalent – at Orange, Zain, Telefónica and Vodafone and asked them about their core focus areas in the short- and mid-term and how they were driving forward the data-driven telco agenda. Topics for discussion included:

  • Their vision and expected future strategy
  • Their current focus areas
  • The work that they are undertaking to improve organisational structure and culture
  • Their priorities for future technology roll out.

As shown in the figure below, we note that some areas of priority remain unchanged from previous years and continue to be a focus in 2023, while new ones (shown in red) are appearing on the horizon.

Priorities for the CDO and their team

Roles of data-driven telco CDO

Source: STL Partners

Priorities are evolving from being focused specifically on accessing data and other relatively discrete A3 projects, to much more strategic and organisation-wide activities. As such, the scope of the CDO role is expanding.

Table of contents

  • Executive Summary
    • Recommendations
    • Vision and strategy
    • Organisation and culture
    • Technology
    • Next steps
  • Introduction
  • Priority 1: Select the right internal focus
    • How to select the most impactful projects
    • How to maintain a pipeline of successful projects
  • Priority 2: Create a joined-up organisation
    • A joined-up organization structure
    • Promoting the data culture
    • Skill sets of the Chief Data Officer (CDO)
  • Priority 3: Delivering a useable data set
    • Building a long-term data quality practise
    • Hybrid-cloud data deployment
  • Priority 4: Building data tools for all
  • Conclusion

Related research

 

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The state of telco transformation

There are two possible interpretations of the phrase “the state of transformation”:

  1. How is transformation going at telcos, i.e. where are telcos on the path to transformation
  2. The condition of transformation, i.e. what does it mean to be in the process of transforming.

Over the summer of 2022, STL Partners carried out nine in-depth interviews with telco employees that were involved in influencing, coordinating, or implementing large change projects at their organisations. These change makers came from various disciplines: Strategy, HR, Transformation project management, Networks, Technology, as well as Research. Our first intention was to illuminate the first interpretation (where are telcos on the path to
transformation), but our findings suggest that transformation paths (and indeed end states) are unique to each operator, making it difficult to compare progress between telcos.

No one path – overlapping changes in multiple areas

Source: STL Partners

We have mainly come away with findings on the latter point – identifying the types of change initiatives underway and the challenges that change-makers are encountering on their journeys.

This report brings together insights from our interviews, contextualised with further information from secondary sources and ongoing conversations with operators, to give a sense of what telcos mean when they talk about transformation and what their challenges are in becoming more adaptable as organisations to find growth.

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Why is Transformation important to telcos

Far from being an irrelevant or out-dated concept, telcos continue to transform internally. Transformation is understood as a deep change initiative that might involve a shift in foundational technology or a broad-based change in the way an organisation does things, i.e. the culture, processes and the people required – or both.

Most commonly, transformation involves the integration of digital technologies/tools (e.g. cloud, automation, data analytics) into organisational processes to improve business outcomes – with an impact on ways of working (“digital transformation”).

Some telcos talk about transformation in terms of functional initiatives (e.g. IT modernisation), ostensibly affecting a subset of the business, while others talk about transformation from an organisation-wide perspective (e.g. a change in culture like Lean Six Sigma).

The common feature between telco narratives about transformation is that they are motivated by
trying to improve the organisation’s ability to achieve their future vision. This could involve:

  • Making the business more efficient,
  • Creating new value/finding new revenues,
  • Improving outcomes for customers.

Transformations are also undertaken when the vision changes (e.g. when a new leader takes the helm). STL observes that interview respondents described technology-led transformations as aligned to efficiency benefits in the first instance, while organisation-led change was more aligned to responsiveness, particularly in relation to customer needs (improving outcomes). Respondents tended to describe combined technology- and organisation-led change initiatives when there was an ambition to do new things/create new value for customers.

The meaning of transformation – activities cited in interviews

Source: STL Partners

Respondents also mentioned:

  • Transformation in the context of the industry, particularly the possibility that new technologies may change the shape of an industry (e.g. tech companies may find it easier to enter telecoms with their technology capabilities, while telcos may find it difficult to extend services up the technology value chain).
  • The enterprise opportunity represented by digital transformation services.

These were not topics for further exploration in our interviews. Industry transformation is a topic for STL’s Executive Briefing Service – however the threat of industry disruption can and should be an inspiration for corporate transformation. Digital transformation services are covered in our Enterprise stream.

Table of contents

  • Executive Summary
  • Introduction
  • Why is Transformation important to telcos
    • Different change trajectories
  • The condition of transformation – being in the process of it
    • Where do telcos have transformation efforts underway
    • How are transformation projects approached at telcos?
    • Who is responsible for transformation?
  • Barriers to transformation
    • Change leadership issues
    • People challenges
    • Execution difficulties
  • What is holding telcos back from being future-ready organisations?
    • Out with the old…
    • …In with the new
  • Conclusion
    • Recommendations

Related Research

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Capturing the 5G SA opportunity: towards a multi-vendor approach

The 5G SA opportunity

5G SA is an exciting prospect for telecoms operators. With many operators’ revenues from traditional connectivity beginning to stagnate, or even decline, there is increased pressure for operators to create differentiation and offer new services, including by expanding across the value chain from connectivity-only providers.

STL Partners has described this new era, whereby operators must shift their business models to adapt to the new demands, as the Coordination Age 2. From the 1850s until around 1990, the Communications Age enabled people to communicate over long distances via telephony. Next came the Information Age, in which people could directly access content and applications, increasingly provided by non-telecommunications players. In the Coordination Age, ‘things’ are increasingly connecting to other ‘things’, leading to an exponential increase in volumes of data, but thanks to advanced analytics and artificial intelligence (AI) we can also address some of the most pressing issues facing the world today: ensuring resource efficiency and improving productivity to help us to do more with less.

Operators need to define their role in the emerging coordination age


Source: STL Partners

Transitioning to the Coordination Age requires operators to shift their goals and business models accordingly. Operators will need to offer or enable tightly coupled network services and applications to different industries, and continue to refresh, optimise and scale at an unprecedented rate.

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The transformative potential of 5G SA

5G SA, in comparison to its NSA counterpart, is the evolution of 5G that can deliver on the promises associated with the next generation of cellular networking. 5G SA is intended to be cloud native and adopt cloud-native principles. Without SA, 5G networks are less able to quickly launch new services, enable new use cases, or introduce more scalable, automated operating models.

The opportunities to which 5G SA is expected to give rise have been explored extensively in previous STL research. The ‘full potential’ of 5G SA includes promises around higher throughput, greater capacity, the ability to leverage enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), and massive machine type communications (mMTC). In summary; do more (including enabling more connections at any given time), faster (down to a latency of a few milliseconds) and at a lower cost (through a variety of actors, including lower power consumption than 4G). These new capabilities are exciting for operators: enabling operators to develop powerful new applications for their customers with truly differentiated use cases.

One particular opportunity that 5G SA represents is network slicing. Slicing can be defined as ‘a mechanism to create and dynamically manage functionally discrete, virtualised networks over a common infrastructure,’ and has been the subject of several STL reports. The increased flexibility and agility of network slicing can enable operators to provide unique policies and differentiated services to their enterprise customers and recoup the substantial investments that rolling out 5G SA requires. However, the benefits and opportunities of 5G SA have implications far beyond the new services it can enable. For the first time, 5G is cloud-native by design, with modular service-based architecture giving
rise to greater flexibility and programmability. Furthermore, it leverages IT concepts of virtualization, cloudification, and DevOps processes. This does not so much enable as actively encourage a more agile operating model. Some of the exciting features of 5G SA include:

  • Automation – Increased automation throughout the network, including deployment, orchestration, assurance, and optimisation can give rise to “zero touch” networks that do not require human intervention, and can self repair and update autonomously on an ongoing basis. The aim of network automation is to reduce human error and the time taken to resolve issues through closed-loop network assurance.
  • Disaggregation – Relies on an open standard network operating system whereby different functional components of networking equipment can be deployed individually and then combined in a modular, fit for purpose way, to suit the requirements of an operator’s network. This architecture relies on the interworking between the multi-vendor components within the 5G core. Disaggregation can allow vendors to offer best in class capabilities for each individual component, providing operators with unprecedented choice and customizability.
  • Avoiding vendor lock-in through a diversified supply base – One of the key benefits of a disaggregated approach to the 5G core is to break vendor lock-in that has tended to dominate legacy approaches. Vendor lock-in can be a key limitation on the speed of innovation and service deployment.
  • Agility – Adopting a continuous improvement and development means accelerated innovation and speed of deployment. A software-orientated infrastructure can enable changes in business processes such as product development management to happen at a greater pace and speed time to market for new revenue generating products and features.
  • Scalability through adopting ‘hyperscale economics’ – Explored by STL Partners in previous research, this term describes the emulation of business and software practices developed by hyperscalers to deliver service innovation at scale whilst simultaneously reducing the level of capex relative to revenue.

Cloud native is the only way to truly unlock the benefits of 5G thanks to the automation, efficiency,
optimisation and mode of delivery that it enables. Ultimately, it allows operators to maximise the
opportunity of 5G to develop differentiated services to consumer and enterprises customers.

 

Table of Contents:

  • Executive Summary
    • Recommendations
  • Preface
  • The 5G SA opportunity
    • The transformative potential of 5G SA
    • 5G SA requires operators to develop and foster a new set of skills
    • Some open questions remain around 5G SA
  • The early adopter 5G SA landscape
    • Orange
    • Vodafone
    • Dish
  • Tier 2 and Tier 3 operator approaches to 5G SA
    • Adherents to a single vendor approach
    • Proponents of a multi-vendor approach
    • Several factors can influence an operators’ vendor strategy
  • Recommendations

Related research

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Four goals for the data-driven telco

Becoming a data-driven telco

There have been many case studies over the last five years demonstrating the disruption caused by “data-driven businesses”, i.e. those using insights to understand customers, automate processes, change their business models and drive new revenues. In the future, this concept will become an integral part of what it takes to compete successfully, allowing organisations to understand and run all parts of their operations, work with their customers and partners and take part in external activities in new ecosystems. This applies to telecoms operators as much as any other industry.

This research builds on a range of reports STL Partners has previously published on strategic topics related to telcos’ use of data, including:

This research turns to the practical topics of delivering on these strategic goals. The diagram below offers an overview of the drivers and barriers affecting delivery areas such as telco data management and machine learning (ML) in the short and longer term.

Drivers and barriers to being a data-driven telco

Source: STL Partners

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What capabilities should telcos develop?

Telcos are reasonably sophisticated users of data, but their particularly complex web of legacy systems requires a good deal of work around data management and governance to enable the extraction of data sets to give 360-degree view of the customer – and increasingly to provide training data for algorithms.

In the mid-term, telcos that are successful in selling IoT and becoming ecosystem players will require new A3 to deal with the increasing number of services, devices, price points and parties involved in providing service to a customer. Our research suggests that there is a range of new A3 technologies that can provide the automation and intelligence for this, as well as for the underlying data management processes.

In the longer-term, A3 will speed up decision making, impacting company strategy, new product and service creation, and customer experience. Humans will increasingly be supported by AI-, ML- and automation-powered tools in their decision-making. A similar progression will occur among competitors in telecoms, and in adjacent markets, increasing the complexity and speed of doing business. Besides integrating A3 into human workflows, working at increasing speed will depend on getting richer insights out of the available data with techniques such as small data and creation of synthetic data.

Capabilities for a data-driven telco

Source: STL Partners

 

Table of contents

  • Executive Summary
    • Capabilities telcos should develop over the medium term
    • What will telcos focus on in the mid-term?
    • Next steps
  • Becoming a data-driven telco
    • Short term drivers
    • Barriers in the short term
    • Long term drivers
    • Barriers in the long term
  • Availability of data
    • Use of data fabrics
    • Better data labelling
    • Rise of synthetic data
    • More intelligent data selection
    • Telco strategies for cloud usage
  • Equipping people
    • Augmented analytics and business intelligence
    • Decision intelligence
  • Work on governance
    • Governance across the telco
    • Agility in governance
    • Governance for AI and machine learning
    • Ethical governance
    • Improved measurement of governance
    • Governance in ecosystems
  • Index

The Future of Work: How AI can help telcos keep up

What will the Future of Work look like?

The Future of Work is a complex mix of external and internal drivers which will exert pressure on the telco to change – both immediately and into the long-term. Drivers include government policy, general changes in cultural attitudes and new types of technology. For example, intelligent tools will see humans and machines working more closely together. AI and automation will be major drivers of change, but they are also tools to address the impact of this change.

AI and automation both drive and solve Future of Work challenges

Futuore of work AI automation analytics

Source: STL Partners

This report leverages secondary research from a variety of consultancies, research houses and academic institutions. It also builds on STL Partners’ previous research around the use of A3 and future new technologies in telecoms, as well as organisational learning to increase telco ability to absorb change and thrive in dynamic environments:

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The Future of Work

We begin by summarising secondary research around the Future of Work. Key topics we explore are:

Components of the Future of Work

Future of work equation

Source: STL Partners

  1. The term Fourth Industrial Revolution is often used interchangeably with the technologies involved in Industry 4.0. However, this report uses a broader definition (quoted from Salesforce):
    • “The blurring of boundaries between the physical, digital, and biological worlds. It’s a fusion of advances in artificial intelligence (AI), robotics, the Internet of Things (IoT), 3D printing, genetic engineering, quantum computing, and other technologies.” 
  2. Societal and cultural change includes changes in government and public attitude, particularly around climate change and issues of equality. It also includes changing attitudes of employees towards work.
  3. Business environment change encompasses a variety of topics around competitive dynamics (e.g. national versus global economies of scale) and changing market conditions, in particular with relation to changing corporate structures (hierarchies, team structures, employees versus contractors).
  4. Pandemic-related change: The move towards homeworking and hastening of some existing/new trends (e.g. automation, ecommerce).

Content

  • Executive Summary
  • Introduction
  • The Future of Work
    1. The Fourth Industrial Revolution
    2. Societal and cultural change
    3. Business environment change
    4. Pandemic-related change
  • How will FoW trends impact telcos in the next 5 to 10 years?
    • Expected market conditions
    • Implications for telcos’ strategic direction
    • Workforce and cultural change
  • Telco responses to FoW trends and how A3 can help
    • Strategic direction
    • Skills development
    • Organisational and cultural change
  • Appendix 1
  • Index

Related Research

 

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AI & automation for telcos: Mapping the financial value

This is an update to STL Partners report A3 for telcos: Mapping the financial value, published in May 2020, which estimated the financial value of automation, AI and analytics (A3) through bottom up analysis of potential capex/opex savings or revenue uplift from integrating A3 into 150+ processes across a telco’s core operations.

The value is measured on an annual basis in dollar terms and as a proportion of total revenue for a “standard telecoms operator”. Access to the full methodology and definition of a standard telco is available in the report Appendix.

We categorise the value of automation, AI and analytics (A3) in telecoms across operational area, as well as type and purpose of A3 technology. Our graphic below summarises the value of A3 across the following six types of technology:

  1. Making sense of complex data: Analytics and machine learning used to understand large, mostly structured data sets, looking for patterns to diagnose problems and predict/prescribe resolutions.
  2. Automating processes: Intelligent automation and RPA to enable decision making, orchestration and task completion within telco processes.
  3. Personalising customer interactions: Analytics and machine learning used to understand customer data, create segmentation, identify triggers and prescribe actions to be taken.
  4. Support business planning: Analytics and machine learning used in forecasting and optimisation exercises.
  5. Augmenting human capabilities: AI solutions such as natural language processing and text analytics used to understand human intent or sentiment, to support interactions between customers or employees and telco systems.
  6. Frontier AI solutions: A number of individual AI solutions which have particular, specialist uses within a telco.

For further detail on this categorisation methodology, see STL Partners report The telco A3 application map

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What’s new in 2022

The colouring of the use case categories in the graphic below remains largely unchanged from May 2020. Some uses of A3 were reasonably mature in that timeframe and already rolled out in a typical telco, so their value was already well understood.

We estimate that the most valuable use case categories, primarily in networks and operations, deliver over $50 millions in annual benefits – and sometimes up to hundreds of millions. Throughout this report we express the value in dollar terms and as a percentage of savings within each domain. This is because while $50 million is clearly a significant sum, it accounts for just 0.33% of total revenues for our standard operator, so showing values for unique use case categories as a proportion of total revenues undermines the potential value A3 can add to individual teams, and in turn contribute to significant aggregate value across an operator.

Overview of the financial value of A3

financual-value-A3

Source: STL Partners, Charlotte Patrick Consult

In our May 2020 research, many of the more sophisticated uses of A3 were understood in theory but yet to be implemented. Researching these various newer uses cases throughout 2021 has revealed that many are now, at least partly, rolled out (although some are still waiting for cleaner data or more orchestration capabilities).

However, there were a few new case studies with financial benefits that necessitated more than small changes to the 2020 financial value calculations. Summarising the changes illustrated in the graphic above:

  • The most noticeable change in uptake for A3 was in the BSS domain. Vendors and telcos were not discussing much beyond RPA and basic analytics in 2020, but there are now a whole range of potential uses for ML (typically in the box labelled “Revenue management” in the graphic above). The question of how much additional financial value to assign to this is interesting – some of the A3 will ensure that the rating and charging systems can cope with the additional volume and complexity around 5G and IoT billing, so an allocation of revenue uplift has been assigned. However, this revenue benefit only accounts for around 6% of the additional $83 million in value from A3 in networks and operations estimated in this update.
  • We have added partner management as a new use case category, within operations. This is to allow A3 value to be added as telcos work with more partners and in new ecosystems, and accounts for 6% of additional value in networks and operations in this update.
  • An increase in the assumed value of A3 within marketing programs, owing to the addition of ML to improve the design of new offers.
  • The value of a previous use case category labelled “Troubleshooting” has been subsumed into “Unassisted channels”, as telcos find it difficult to implement troubleshooting tools for customers.
  • Some increase in financial benefit around customer chatbots and field services, due to new case studies showing financial value.

Our report includes a section for each of the first three columns of the graphic above (Networks and operations, customer channels, marketing and sales). The final column (other functions) doesn’t currently have financial calculations underpinning it as values are thought to be insubstantial in comparison to the first three columns.

Table of contents

  • Executive summary
  • Overview of the financial value of automation, AI and analytics (A3)
  • Financial value by business unit
    • BSS, OSS and networks
    • Customer channels
    • Sales and marketing
  • Appendix
    • Methodology for Calculating Financial Value
    • Augmented Analytics Capabilities

Related Research

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How telcos can make the world a safer place

Telecoms networks can support public safety

In the wake of the pandemic and multiple natural disasters, such as fire and flooding, both policymakers and people in general are placing a greater focus on preserving health and ensuring public safety. This report begins by explaining the concept of a digital nervous system – large numbers of connected sensors that can monitor events in real-time and thereby alert organizations and individuals to imminent threats to their health and safety.

With the advent of 5G, 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. The application of reliable and ubiquitous connectivity to enable governments, companies and individuals to live in a safer world is one way in which operators can contribute to the Coordination Age.

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The chapters in this report consider the potential to use the data collected by telecoms networks to help counter the health and safety threats posed by:

  • Environmental factors, such as air pollution and high-levels of pollen,
  • Natural disasters, such as wildfires, flooding and earthquakes,
  • Infectious diseases
  • Violence, such as riots and shooting incidents
  • Accidents on roads, rivers and coastlines

In each case, the report considers how to harness new data collected by connected sensors, cameras and other monitors, in addition to data already captured by mobile networks (showing where people are and where they are moving to).  It also identifies who telcos will need to work with to develop and deploy such solutions, while discussing potential revenue streams.  In most cases, the report includes short case studies describing how telcos are trialling or deploying actual solutions, generally in partnership with other stakeholders.

The final chapter focuses on the role of telcos – the assets and the capabilities they have to improve health and safety.

It builds on previous STL Partners research including:

Managing an unstable world

Prior to the damage wrought by the pandemic, the world was gradually becoming a safer place for human beings. Global life expectancy has been rising steadily for many decades and the UN expects that trend to continue, albeit at a slower pace. That implies the world is safer than it was in the twentieth century and people are healthier than they used to be.

Global gains in life expectancy are slowing down

health and safety

Source: United Nations – World Population Prospects

But a succession of pandemics, more extreme weather events and rising pollution may yet reverse these positive trends. Indeed, many people now feel that they live in an increasingly unstable and dangerous world. Air pollution and over-crowding are worsening the health impact of respiratory conditions and infections, such as SARS-CoV-2. As climate change accelerates, experts expect an increase in flash flooding, wildfires, drought and intense heat. As extreme weather impacts the food and water supplies, civil unrest and even armed conflict could follow. In the modern world, the four horsemen of the apocalypse might symbolize infectious disease, extreme weather, pollution and violence.

As the human race grapples with these challenges, there is growing interest in services and technologies that could make the world a safer and healthier place. That demand is apparent among both individuals (hence the strong sales of wearable fitness monitors) and among public sector bodies’ rising interest in environment and crowd monitoring solutions.

As prevention is better than cure, both citizens and organisations are looking for early warning systems that can help them prepare for threats and take mitigating actions. For example, an individual with an underlying health condition could benefit from a service that warns them when they are approaching an area with poor air quality or large numbers of densely-packed people. Similarly, a municipality would welcome a solution that alerts them when large numbers of people are gathering in a public space or drains are close to being blocked or are overflowing.  The development of these kinds of early warning systems would involve tracking both events and people in real-time to detect patterns that signal a potential hazard or disruption, such as a riot or flooding.

Advances in artificial intelligence (AI), as well as the falling cost of cameras and other sensors, together with the rollout of increasingly dense telecoms networks, could make such systems viable. For example, a camera mounted on a lamppost could use image and audio recognition technologies to detect when a crowd is gathering in the locality, a gun has been fired, a drain has been flooded or an accident has occurred.

Many connected sensors and cameras, of course, won’t be in a fixed location – they will be attached to drones, vehicles and even bicycles, to support use cases where mobility will enhance the service. Such uses cases could include air quality monitoring, wildfire and flooding surveillance, and search and rescue.

Marty Sprinzen, CEO of Vantiq (a provider of event-driven, real-time collaborative applications) believes telecoms companies are best positioned to create a “global digital nervous system” as they have the networks and managed service capabilities to scale these applications for broad deployment. “Secure and reliable connectivity and networking (increasingly on ultrafast 5G networks) are just the beginning in terms of the value telcos can bring,” he wrote in an article for Forbes, published in November 2020. “They can lead on the provisioning and management of the literally billions of IoT devices — cameras, wearables and sensors of all types — that are integral to real-time systems. They can aggregate and analyze the massive amount of data that these systems generate and share insights with their customers. And they can bring together the software providers and integrators and various other parties that will be necessary to build, maintain and run such sophisticated systems.”

Sprinzen regards multi-access edge computing, or MEC, as the key to unlocking this market. He describes MEC as a new, distributed architecture that pushes compute and cloud-like capabilities out of data centres and the cloud to the edge of the network — closer to end-users and billions of IoT devices. This enables the filtering and processing of data at the edge in near real-time, to enable a rapid response to critical events.

This kind of digital nervous system could help curb the adverse impact of future pandemics. “I believe smart building applications will help companies monitor for and manage symptom detection, physical distancing, contact tracing, access management, safety compliance and asset tracking in the workplace,” Sprinzen wrote. “Real-time traffic monitoring will ease urban congestion and reduce the number and severity of accidents. Monitoring and management of water supplies, electrical grids and public transportation will safeguard us against equipment failures or attacks by bad actors. Environmental applications will provide early warnings of floods or wildfires. Food distribution and waste management applications will help us make more of our precious resources.”

Vantiq says one if its telco customers is implementing AI-enabled cameras, IoT sensors, location data and other technologies to monitor various aspects of its new headquarters building. He didn’t identify the telco, but added that it is the lead technology partner for a city that’s implementing a spectrum of smart city solutions to improve mobility, reduce congestion and strengthen disaster prevention.

Table of contents

  • Executive Summary
  • Introduction
  • Managing an unstable world
  • Monitoring air quality
    • Exploiting existing cellular infrastructure
    • Is mobile network data enough?
    • Smart lampposts to play a broad role
    • The economics of connecting environmental sensors
    • Sensors in the sky
  • Natural disasters
    • Spotting wildfires early
    • Earthquake alert systems
    • Crowdsourcing data
    • Infectious diseases
  • On street security
  • Conclusions – the opportunities for telcos
    • Ecosystem coordination – kickstarting the market
    • Devices – finding the right locations
    • Network – reliable, low cost connectivity
    • Data platform
    • Applications
  • Index

 

 

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A3 in customer experience: Possibilities for personalisation

The value of A3 in customer experience

This report considers the financial value to a telco of using A3 technologies (analytics, automation and AI) to improve customer experience. It examines the key area which underpins much of this financial value – customer support channels – considering the trends in this area and how the area might change in future, shaping the requirement for A3.

Calculating the value of improving customer experience is complex: it can be difficult to identify the specific action that improved a customer’s perception of their experience, and then to assess the impact of this improvement on their subsequent behaviour.

While it is difficult to draw causal links between telcos’ A3 activities and customer perceptions and behaviours, there are still some clearly measurable financial benefits from these investments. We estimate this value by leveraging our broader analysis of the financial value of A3 in telecoms, and then zooming in on the specific pockets of value which relate to improved customer experience (e.g. churn reduction).

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The diagram below illustrates that there are two parts of the customer journey where A3 will add most value to customer experience:

  1. The performance of the network, services, devices and applications is increasingly dependent on automation and intelligence, with the introduction of 5G and cloud-native operations. Without A3 capabilities it will be difficult to meet quality of service standards, understand customer-affecting issues and turn up new services at speed.
  2. The contact centre remains one of the largest influencers of customer experience and one of the biggest users of automation, with the digital channels increasing in importance during the pandemic. Understanding the customer and the agent’s needs and providing information about issues the customer is experiencing to both parties are areas where more A3 should be used in future.

Where is the financial benefit of adding A3 within a typical telco customer journey?

A3 customer experience

Source: STL Partners, Charlotte Patrick Consult

As per this diagram, many of the most valuable uses for A3 are in the contact centre and digital channels. Improvements in customer experience will be tied with trends in both. These priority trends and potential A3 solutions are outlined the following two tables:
• The first shows contact centre priorities,
• The second shows priorities for the digital channels.

Priorities in the contact centre

A3 Contact centre

Priorities in the digital channel

A3 Digital channel

Table of Contents

  • Executive Summary
  • The value of A3 in customer experience
  • Use of A3 to improve customer experience
  • The most important uses of A3 for improving the customer experience
    • Complex data
    • Personalisation
    • Planning
    • Human-machine interaction
    • AI point solution
  • Conclusion
  • Appendix: Methodology for calculating financial value
  • Index

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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The $300bn COVID digital health dividend

This report introduces a new sizing model for digital healthcare that reflects the recent impact of the COVID pandemic on the sector, with the goal of identifying the new opportunities and risks presented to operators and others attempting or considering investment in the market. A key finding is that market development has been accelerated four years ahead of its prior trajectory, meaning that players should significantly reassess the urgency and scale of their strategic application.

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Why healthcare?

STL Partners has long argued that if telecoms operators want to build new businesses beyond connectivity, they will need 1) clarity on which customer needs to address and 2) long term commitment to investment and innovation to address them. Adding value farther up the value chain requires significant new skills and capabilities, so we believe telecoms operators must be deliberate in their choice of which customers they want to serve, i.e. which verticals, and what they want to do for them. For more detail, see STL Partners’ report How mobile operators can build winning 5G business models.

We believe that healthcare is a vertical that is well suited to telecoms operators’ strategic scope:

  • Healthcare is a consistently growing need in every country in the world
  • It is a big sector that can truly move the needle on telcos’ revenues, accounting for nearly 10% of GDP globally in 2018, up from 8.6% of GDP in 2000 according to WHO data
  • It operates within national economies of scale (even if the technology is global, implementation of that technology requires local knowledge and relationships)
  • The sector has historically been slower than others in its adoption of new technologies, partly due to quality and regulatory demands, factors that telcos are used to dealing with
  • Improving healthcare outcomes is meaningful work that all employees and stakeholders can relate to.

Many telcos also believe that healthcare is a vertical with significant opportunity, as demonstrated by operators’ such as TELUS and Telstra’s big investments into building health IT businesses, and smaller but ongoing efforts from many others. See STL Partners’ report How to crack the healthcare opportunity for profiles of nine telecoms operators’ strategies in the healthcare vertical.

Our research into the telecoms industry’s investment priorities in 2021 shows that the accelerated uptake of digital health solutions throughout the COVID pandemic has only shifted health further up the priority list for operators.

Figure 1: Digital health is among telcos’ top investment priorities in 2021

digital health telecoms priority

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

However, few operators have put their full effort into driving the transformation of healthcare delivery and outcomes through digital solutions. From our conversations with operators around the world, we believe this is in large because they are not yet fully convinced that addressing the challenges associated with transforming healthcare – fragmented and complex systems, slow moving public processes, impact on human lives – will pay off. Are they capable of solving these challenges, and is the business opportunity big enough to justify the risk?

Taking a cautious “wait and see” approach to developing a digital health business, launching a couple of trials or PoCs and seeing if they deliver value, or investing in a digital health start-up or two, may have been a viable approach for operators before the COVID pandemic hit, but with the acceleration in digital health adoption this is no longer the case. Now that COVID has forced healthcare providers and patients to embrace new technologies, the proof points and business cases the industry has been demanding have become a lot clearer. As a result, the digital health market is now four years ahead of where it was at the beginning of 2020, so operators seeking to build a business in healthcare should commit now while momentum and appetite for change is strong.

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How is COVID changing healthcare delivery?

The first and most significantly affected area of the digital health landscape throughout 2020 was virtual consultations and telehealth, where almost overnight doctors shifted as many appointments on to phone or video calls as possible. For example, in the UK the proportion of doctor’s visits happening over the phone or video rose from around 13% in late 2019 to 48% at the peak of the pandemic in April-June 2020, while US based virtual consultation provider Teladoc’s total visits tripled between Q219 and Q220, to 2.8mn.

By necessity, regulatory barriers to adoption of virtual consultations were lowered. Other barriers, such as insurers or governments not reimbursing or underpaying doctors for virtual appointments, and organisational and culture barriers among both patients and providers also broke down. The knock on effect has been acceleration across the broader digital health market, in areas such as remote patient monitoring and population level analytics. (See more on the immediate impact of COVID on digital health in STL article How COVID-19 is changing digital health – and what it means for telcos)

The key question is how much of an impact has COVID had, and will it last over the long term? This is what we aim to answer in this report and the accompanying global database tool. Key questions we address in this analysis are:

  • How much has COVID accelerated adoption of digital health applications?
  • What are the cost savings from accelerated uptake of digital health following COVID?
  • Which digital health application areas have been most affected by COVID?
  • Beyond the COVID impact, what is the total potential value of digital health applications for healthcare providers?
  • Which digital health application areas will deliver the biggest cost savings, globally and within specific markets?

To answer these questions we have built a bottom-up forecast model with a focus on the application areas we believe are most relevant to telecoms operators, as illustrated in Figure 2.

Figure 2: Five digital health application areas for telcos

5 digital health application areas

Source: STL Partners

We believe these are most relevant because their high dependence on connectivity, and needs for significant coordination and engagement with a broad range of local stakeholders to succeed, are well aligned with telecoms operators assets. See this STL Partners article for more detail on why these application areas are good entry points for telecoms operators.

NB We chose to omit the Personal health and wellness application area from our bottom-up model. It is a more generic and global application area than the others, dominated by players such as Google/Fitbit and Apple and with little integration thus far into formal healthcare services. While it is nonetheless an area of interest for telecoms operators, especially those that are seeking to build deeper relationships directly with consumers, it is a difficult entry point for telecoms operators seeking to build a healthcare business. This global and consumer focused nature of this application area also means that it is difficult to find reliable local data and quantify its value for healthcare systems.

What are these forecasts for?

Telecoms operators and others should use this forecast analysis to understand the potential value of digital health, including:

  • The size of the digital health opportunity in different markets
  • The market size for new applications across the four areas we modelled (remote patient monitoring, virtual care and telehealth, diagnostics and triage, data and analytics)
  • The relative size of the opportunities across the four application areas in different countries
  • The pace of digital health adoption and market growth in different countries and application areas

In other words, it shows how big the overall digital health market is, how fast it is growing, and which application areas are most valuable and/or growing fastest.

In a follow-up report, we will expand on this analysis to assess how much of this value telecoms operators specifically can capture.

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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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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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End-to-end network automation: Why and how to do it?

Automation, analytics and AI: A3 unlocks value for operators

STL Partners has been writing about automation, artificial intelligence (AI) and data analytics for several years. While the three have overlapping capabilities and often a single use case will rely upon a combination, they are also distinct in their technical outcomes.

Distinctions between the three As

Source: STL Partners

Operators have been heavily investing in A3 use cases for several years and are making significant progress. Efforts can be broadly broken down into five different domains: sales and marketing, customer experience, network planning and operations, service innovation and other operations. Some of these domains, such as sales and marketing and customer experience, are more mature, with significant numbers of use cases moving beyond R&D and PoCs into live, scaled deployments. In comparison, other domains, like service innovation, are typically less mature, despite the potential new revenue opportunities attached to them.

Five A3 use case domains

Source: STL Partners

Use cases often overlap across domains. For example, a Western European operator has implemented an advanced analytics platform that monitors network performance, and outputs a unique KPI that, at a per subscriber level, indicates the customer experience of the network. This can be used to trigger an automated marketing campaign to customers who are experiencing issues with their network performance (e.g. an offer for free mobile hotspot until issues are sorted). In this way, it spans both customer experience and network operations. For the purpose of this paper, however, we will primarily focus on automation use cases in the network domain.  We have modelled the financial value of A3 for telcos: Mapping the financial value.

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The time is ripe for network automation now

Network automation is not new. In fact, it’s been a core part of operator’s network capabilities since Almon Strowger invented the Strowger switch (in 1889), automating the process of the telephone exchange. Anecdotally, Strowger (an undertaker by profession) came up with this invention because the wife of a rival funeral parlour owner, working at the local community switchboard, was redirecting customers calling for Strowger to her own husband’s business.

Early advertising called the Strowger switch the “girl-less, cuss-less, out-of-order-less, wait-less telephone” or, in other words, free from human error and faster than the manual switchboard system. While this example is more than 100 years old, many of the benefits of automation that it achieved are still true today; automation can provide operators with the ability to deliver services on-demand, without the wait, and free from human error (or worse still, malevolent intent).

Despite automation not being a new phenomenon, STL Partners has identified six key reasons why network automation is something operators should prioritise now:

  • Only with automation can operators deliver the degree of agility that customers will demand. Customers today expect the kind of speed, accuracy and flexibility of service that can only be achieved in a cost-effective manner with high degrees of network automation. This can be both consumer customers (e.g. for next generation network services like VR/AR applications, gaming, high-definition video streaming etc.) or enterprise customers (e.g. for creating a network slice that is spun up for a weekend for a specific big event). With networks becoming increasingly customised, operators must automate their systems (across both OSS and BSS) to ensure that they can deliver these services without a drastic increase in their operating costs.
    One  wholesale operator exemplified this shift in expectations when describing their customers, which included several of the big technology companies including Amazon and Google: “They have a pace in their business that is really high and for us to keep up with their requirements and at the same time beat all our competitors we just need to be more automated”. They stated that while other customers may be more flexible and understand that instantiating a new service takes time, the “Big 5” expect services in hours rather than days and weeks.
  • Automation can enable operators to do more, such as play higher up the value chain. External partners have an expectation that telcos are highly skilled at handling data and are highly automated, particularly within the network domain. It is only through investing in internal automation efforts that operators will be able to position themselves as respected partners for services above and beyond pure connectivity. An example of success here would be the Finnish operator Elisa. They invested in automation capabilities for their own network – but subsequently have been able to monetise this externally in the form of Elisa Automate.
    A further example would be STL Partners’ vision of the Coordination Age. There is a role for telcos to play further up the value chain in coordinating across ecosystems – which will ultimately enable them to unlock new verticals and new revenue growth. The telecoms industry already connects some organisations and ecosystems together, so it’s in a strong position to play this coordinating role. But, if they wish to be trusted as ecosystem coordinators, they must first prove their pedigree in these core skills. Or, in other words, if you can’t automate your own systems, customers won’t trust you to be key partners in trying to automate theirs.
  • Automation can free up resource for service innovation. If operators are going to do more, and play a role beyond connectivity, they need to invest more in service innovation. Equally, they must also learn to innovate at a much lower cost, embracing automation alongside principles like agile development and fast fail mentalities. To invest more in service innovation, operators need to reallocate resources from other areas of their business – as most telcos are no longer rapidly growing, resource must be freed up from elsewhere.
    Reducing operating costs is a key way that operators can enable increased investment in innovation – and automation is a key way to achieve this.

A3 can drive savings to redistribute to service innovation

Source: Telecoms operator accounts, STL Partners estimates and analysis

  • 5G won’t fulfil its potential without automation. 5G standards mean that automation is built into the design from the bottom up. Most operators believe that 5G will essentially not be possible without being highly automated, particularly when considering next generation network services such as dynamic network slicing. On top of this, there will be a ranging need for automation outside of the standards – like for efficient cell-site deployment, or more sophisticated optimisation efforts for energy efficiency. Therefore, the capex investment in 5G is a major trigger to invest in automation solutions.
  • Intent-based network automation is a maturing domain. Newer technologies, like artificial intelligence and machine learning, are increasing the capabilities of automation. Traditional automation (such as robotic process automation or RPA) can be used to perform the same tasks as previously were done manually (such as inputting information for VPN provisioning) but in an automated fashion. To achieve this, rules-based scripts are used – where a human inputs exactly what it is they want the machine to do. In comparison, intent-based automation enables engineers to define a particular task (e.g. connectivity between two end-points with particular latency, bandwidth and security requirements) and software converts this request into lower level instructions for the service bearing infrastructure. You can then monitor the success of achieving the original intent.
    Use of AI and ML in conjunction with intent-based automation, can enable operators to move from automation ‘to do what humans can do but faster and more accurately’, to automation to achieve outcomes that could not be achieved in a manual way. ML and AI has a particular role to play in anomaly detection, event clustering and predictive analytics for network operations teams.
    While you can automate without AI and ML, and in fact for many telcos this is still the focus, this new technology is increasing the possibilities of what automation can achieve. 40% of our interviewees had network automation use cases that made some use of AI or ML.
  • Network virtualisation is increasing automation possibilities. As networks are increasingly virtualised, and network functions become software, operators will be afforded a greater ability than ever before to automate management, maintenance and orchestration of network services. Once networks are running on common computing hardware, making changes to the network is, in theory, purely a software change. It is easy to see how, for example, SDN will allow automation of previously human-intensive maintenance tasks. A number of operators have shared that their teams and/or organisations as a whole are thinking of virtualisation, orchestration and automation as coming hand-in-hand.

This report focuses on the opportunities and challenges in network automation. In the future, STL Partners will also look to more deeply evaluate the implications of network automation for governments and regulators, a key stakeholder within this ecosystem.

Table of Contents

  • Executive Summary
    • End-to-end network automation
    • A key opportunity: 6 reasons to focus on network automation now
    • Key recommendations for operators to drive their network automation journey
    • There are challenges operators need to overcome
    • This paper explores a range of network automation use cases
    • STL Partners: Next steps
  • Automation, analytics and AI: A3 unlocks value for operators
    • The time is ripe for network automation now
  • Looking to the future: Operators’ strategy and ambitions
    • Defining end-to-end automation
    • Defining ambitions
  • State of the industry: Network automation today
    • Which networks and what use cases: the breadth of network automation today
    • Removing the human? There is a continuum within automation use cases
    • Strategic challenges: How to effectively prioritise (network) automation efforts
    • Challenges to network automation– people and culture are key to success
  • Conclusions
    • Recommendations for vendors (and others in the ecosystem)
    • Recommendations for operators

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A3 for telcos: Mapping the financial value

What is analytics, AI and automation worth to telecoms operators?

This report is the second in a two-part series mapping the process and assessing the financial value of automation, analytics and artificial intelligence (AI) in telecoms. In the first report, The value of analytics, automation and AI for telcos – Part 1: The telco A3 application map, we outlined which type of technology was best suited to which processes across a telco’s operations.

In this report, we assess the financial value of each of the operational areas, in dollar terms, for an average telco. Based on our assessment of operator financials and operational KPIs, the figure below outlines our assumptions on the characteristics of an “average” telco used as the basis for our financial modelling. The characteristics of this telco are as shown below, with a slight skew towards developed market operator characteristics since this is currently where most industry proof points used in our modelling have been implemented.

The characteristics of an average telco

characteristics of an average telco

Source: STL Partners, Charlotte Patrick Consult

The first report in the series analysed how each A3 technology could be applied similarly across different functional units of a telecoms operator, e.g. machine learning or automation each have similar processes in network management, channel management and sales and marketing.

Evaluating AI and automation use cases in four domains

To measure financial impact, this report returns to a traditional breakdown of value by functional unit within the telco, breaking down into four key areas:

  1. Network operations: Network deployment, management and maintenance, and revenue management
  2. Fraud: Including services, online, and internal fraud risks
  3. Customer care: Including all assisted and unassisted channels
  4. Marketing and sales: Understanding customers, managing products, marketing programs, lead management and sales processes.

Through an assessment of nearly 150 individual process areas across a telecoms operator’s core operations, we estimate that A3 can deliver the average telco more than $1 billion dollars in value per year, through a combination of revenue uplift and opex and capex savings, equivalent to 7% of total annual revenues.

As illustrated below, core network operations management accounts for by far the greatest proportion of the value.

The relative value of automation, AI and analytics across telco operations

The relative value of AI, automation and analytics across telco operations

Source: STL Partners, Charlotte Patrick Consult

This likely still underrepresents the total, long term potential value of A3 to telcos, since this first iteration does not model the value of A3 processes in areas less unique to telecoms, including supply chain, finance, IT and HR. No doubt that even within the core area of operations, there are potential process areas that have yet to be discovered or proven, and which we have overlooked in our initial attempt to model the value of A3 to telcos. Meanwhile, this is focused purely on telco’s internal operations so also excludes any potential revenue uplift from new A3-enabled services, such as data monetisation or development of AI-as-a-service type solutions.

That said, operators cannot implement all of these processes at once. The enormous challenge of restructuring processes to be more automated and data-centric, putting in place the data management and analytics capabilities, training employees and acquiring new skills, among many others, means that while many leading telcos are well on their way to capturing this value in some areas, very few – if any – have implemented A3 across all process areas. As a benchmark, Telefónica is an industry leader in leveraging automation and AI to improve operational efficiency, and in 2019 it reported total operational savings of €429mn across the entire group. While this is primarily focused on customer facing channels, so likely excludes the value of A3 in many network operations processes, for instance energy efficiency which is delivering significant value to Telefónica and others, it suggests there remains lots of value still to capture.

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Methodology

The financial modelling for the value of A3 was done through an individual assessment of each of the 150+ process areas to understand the main activities within that area of operations, and how automation, analytics and/or machine learning and other AI technologies could be used within those activities. From there, we assess the value of integrating these technologies to existing operational functions to make them more efficient and effective. This means that we do not attribute any additional value to telcos from implementing new technologies that include A3 as a core element of their functionality, e.g. a multi-domain service orchestrator, implemented as part of software-defined networking.

Our bottom up assessment of each process is also validated through real-world proof points from operators or vendors. This means that more speculative areas of A3 application in operators are calculated to offer relatively limited value. As more proof points emerge, we will incorporate them into future iterations.

Table of contents

  • Executive Summary
    • Where is the largest financial benefit from A3?
    • What should telcos prioritise in the short term?
    • How long will it take for telcos to realise this value?
    • What next?
  • Introduction
    • Methodology
  • Breaking down the value of A3 by operational area
    • Network, OSS and BSS
    • Fraud management
    • Care and commercial channels
    • Marketing and sales
  • Conclusions and recommendations

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