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

5G: Bridging hype, reality and future promises

The 5G situation seems paradoxical

People in China and South Korea are buying 5G phones by the million, far more than initially expected, yet many western telcos are moving cautiously. Will your company also find demand? What’s the smart strategy while uncertainty remains? What actions are needed to lead in the 5G era? What questions must be answered?

New data requires new thinking. STL Partners 5G strategies: Lessons from the early movers presented the situation in late 2019, and in What will make or break 5G growth? we outlined the key drivers and inhibitors for 5G growth. This follow on report addresses what needs to happen next.

The report is informed by talks with executives of over three dozen companies and email contacts with many more, including 21 of the first 24 telcos who have deployed. This report covers considerations for the next three years (2020–2023) based on what we know today.

“Seize the 5G opportunity” says Ke Ruiwen, Chairman, China Telecom, and Chinese reports claimed 14 million sales by the end of 2019. Korea announced two million subscribers in July 2019 and by December 2019 approached five million. By early 2020, The Korean carriers were confident 30% of the market will be using 5G by the end of 2020. In the US, Verizon is selling 5G phones even in areas without 5G services,  With nine phone makers looking for market share, the price in China is US$285–$500 and falling, so the handset price barrier seems to be coming down fast.

Yet in many other markets, operators progress is significantly more tentative. So what is going on, and what should you do about it?

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5G technology works OK

22 of the first 24 operators to deploy are using mid-band radio frequencies.

Vodafone UK claims “5G will work at average speeds of 150–200 Mbps.” Speeds are typically 100 to 500 Mbps, rarely a gigabit. Latency is about 30 milliseconds, only about a third better than decent 4G. Mid-band reach is excellent. Sprint has demonstrated that simply upgrading existing base stations can provide substantial coverage.

5G has a draft business case now: people want to buy 5G phones. New use cases are mostly years away but the prospect of better mobile broadband is winning customers. The costs of radios, backhaul, and core are falling as five system vendors – Ericsson, Huawei, Nokia, Samsung, and ZTE – fight for market share. They’ve shipped over 600,000 radios. Many newcomers are gaining traction, for example Altiostar won a large contract from Rakuten and Mavenir is in trials with DT.

The high cost of 5G networks is an outdated myth. DT, Orange, Verizon, and AT&T are building 5G while cutting or keeping capex flat. Sprint’s results suggest a smart build can quickly reach half the country without a large increase in capital spending. Instead, the issue for operators is that it requires new spending with uncertain returns.

The technology works, mostly. Mid-band is performing as expected, with typical speeds of 100–500Mbps outdoors, though indoor performance is less clear yet. mmWave indoor is badly degraded. Some SDN, NFV, and other tools for automation have reached the field. However, 5G upstream is in limited use. Many carriers are combining 5G downstream with 4G upstream for now. However, each base station currently requires much more power than 4G bases, which leads to high opex. Dynamic spectrum sharing, which allows 5G to share unneeded 4G spectrum, is still in test. Many features of SDN and NFV are not yet ready.

So what should companies do? The next sections review go-to-market lessons, status on forward-looking applications, and technical considerations.

Early go-to-market lessons

Don’t oversell 5G

The continuing publicity for 5G is proving powerful, but variable. Because some customers are already convinced they want 5G, marketing and advertising do not always need to emphasise the value of 5G. For those customers, make clear why your company’s offering is the best compared to rivals’. However, the draw of 5G is not universal. Many remain sceptical, especially if their past experience with 4G has been lacklustre. They – and also a minority swayed by alarmist anti-5G rhetoric – will need far more nuanced and persuasive marketing.

Operators should be wary of overclaiming. 5G speed, although impressive, currently has few practical applications that don’t already work well over decent 4G. Fixed home broadband is a possible exception here. As the objective advantages of 5G in the near future are likely to be limited, operators should not hype features that are unrealistic today, no matter how glamorous. If you don’t have concrete selling propositions, do image advertising or use happy customer testimonials.

Table of Contents

  • Executive Summary
  • Introduction
    • 5G technology works OK
  • Early go-to-market lessons
    • Don’t oversell 5G
    • Price to match the experience
    • Deliver a valuable product
    • Concerns about new competition
    • Prepare for possible demand increases
    • The interdependencies of edge and 5G
  • Potential new applications
    • Large now and likely to grow in the 5G era
    • Near-term applications with possible major impact for 5G
    • Mid- and long-term 5G demand drivers
  • Technology choices, in summary
    • Backhaul and transport networks
    • When will 5G SA cores be needed (or available)?
    • 5G security? Nothing is perfect
    • Telco cloud: NFV, SDN, cloud native cores, and beyond
    • AI and automation in 5G
    • Power and heat

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Telco Cloud: Why it hasn’t delivered, and what must change for 5G

Related Webinar – 5G Telco Clouds: Where we are and where we are headed

This research report will be expanded upon on our upcoming webinar 5G Telco Clouds: Where we are and where we are headed. In this webinar we will argue that 5G will only pay if telcos find a way to make telco clouds work. We will look to address the following key questions:

  • Why have telcos struggled to realise the telco cloud promise?
  • What do telcos need to do to unlock the key benefits?
  • Why is now the time for telcos to try again?

Join us on April 8th 16:00 – 17:00 GMT by using this registration link.

Telco cloud: big promises, undelivered

A network running in the cloud

Back in the early 2010s, the idea that a telecoms operator could run its network in the cloud was earth-shattering. Telecoms networks were complicated and highly-bespoke, and therefore expensive to build, and operate. What if we could find a way to run networks on common, shared resources – like the cloud computing companies do with IT applications? This would be beneficial in a whole host of ways, mostly related to flexibility and efficiency. The industry was sold.

In 2012, ETSI started the ball rolling when it unveiled the Network Functions Virtualisation (NFV) whitepaper, which borrowed the IT world’s concept of server-virtualisation and gave it a networking spin. Network functions would cease to be tied to dedicated pieces of equipment, and instead would run inside “virtual machines” (VMs) hosted on generic computing equipment. In essence, network functions would become software apps, known as virtual network functions (VNFs).

Because the software (the VNF) is not tied to hardware, operators would have much more flexibility over how their network is deployed. As long as we figure out a suitable way to control and configure the apps, we should be able to scale deployments up and down to meet requirements at a given time. And as long as we have enough high-volume servers, switches and storage devices connected together, it’s as simple as spinning up a new instance of the VNF – much simpler than before, when we needed to procure and deploy dedicated pieces of equipment with hefty price tags attached.

An additional benefit of moving to a software model is that operators have a far greater degree of control than before over where network functions physically reside. NFV infrastructure can directly replace old-school networking equipment in the operator’s central offices and points of presence, but the software can in theory run anywhere – in the operator’s private centralised data centre, in a datacentre managed by someone else, or even in a public hyperscale cloud. With a bit of re-engineering, it would be possible to distribute resources throughout a network, perhaps placing traffic-intensive user functions in a hub closer to the user, so that less traffic needs to go back and forth to the central control point. The key is that operators are free to choose, and shift workloads around, dependent on what they need to achieve.

The telco cloud promise

Somewhere along the way, we began talking about the telco cloud. This is a term that means many things to many people. At its most basic level, it refers specifically to the data centre resources supporting a carrier-grade telecoms network: hardware and software infrastructure, with NFV as the underlying technology. But over time, the term has started to also be associated with cloud business practices – that is to say, the innovation-focussed business model of successful cloud computing companies

Figure 2: Telco cloud defined: New technology and new ways of working

Telco cloud: Virtualised & programmable infrastructure together with cloud business practices

Source: STL Partners

In this model, telco infrastructure becomes a flexible technology platform which can be leveraged to enable new ways of working across an operator’s business. Operations become easier to automate. Product development and testing becomes more straightforward – and can happen more quickly than before. With less need for high capital spend on equipment, there is more potential for shorter, success-based funding cycles which promote innovation.

Much has been written about the vast potential of such a telco cloud, by analysts and marketers alike. Indeed, STL Partners has been partial to the same. For this reason, we will avoid a thorough investigation here. Instead, we will use a simplified framework which covers the four major buckets of value which telco cloud is supposed to help us unlock:

Figure 3: The telco cloud promise: Major buckets of value to be unlocked

Four buckets of value from telco cloud: Openness; Flexibility, visibility & control; Performance at scale; Agile service introduction

Source: STL Partners

These four buckets cover the most commonly-cited expectations of telcos moving to the cloud. Swallowed within them all, to some extent, is a fifth expectation: cost savings, which have been promised as a side-effect. These expectations have their origin in what the analyst and vendor community has promised – and so, in theory, they should be realistic and achievable.

The less-exciting reality

At STL Partners, we track the progress of telco cloud primarily through our NFV Deployment Tracker, a comprehensive database of live deployments of telco cloud technologies (NFV, SDN and beyond) in telecoms networks across the planet. The emphasis is on live rather than those running in testbeds or as proofs of concept, since we believe this is a fairer reflection of how mature the industry really is in this regard.

What we find is that, after a slow start, telcos have really taken to telco cloud since 2017, where we have seen a surge in deployments:

Figure 4: Total live deployments of telco cloud technology, 2015-2019
Includes NFVi, VNF, SDN deployments running in live production networks, globally

Telco cloud deployments have risen substantially over the past few years

Source: STL Partners NFV Deployment Tracker

All of the major operator groups around the world are now running telco clouds, as well as a significant long tail of smaller players. As we have explained previously, the primary driving force in that surge has been the move to virtualise mobile core networks in response to data traffic growth, and in preparation for roll-out of 5G networks. To date, most of it is based on NFV: taking existing physical core network functions (components of the Evolved Packet Core or the IP Multimedia Subsystem, in most cases) and running them in virtual machines. No operator has completely decommissioned legacy network infrastructure, but in many cases these deployments are already very ambitious, supporting 50% or more of a mobile operator’s total network traffic.

Yet, despite a surge in deployments, operators we work with are increasingly frustrated in the results. The technology works, but we are a long way from unlocking the value promised in Figure 2. Solutions to date are far from open and vendor-neutral. The ability to monitor, optimise and modify systems is far from ubiquitous. Performance is acceptable, but nothing to write home about, and not yet proven at mass scale. Examples of truly innovative services built on telco cloud platforms are few and far between.

We are continually asked: will telco cloud really deliver? And what needs to change for that to happen?

The problem: flawed approaches to deployment

Learning from those on the front line

The STL Partners hypothesis is that telco cloud, in and of itself, is not the problem. From a theoretical standpoint, there is no reason that virtualised and programmable network and IT infrastructure cannot be a platform for delivering the telco cloud promise. Instead, we believe that the reason it has not yet delivered is linked to how the technology has been deployed, both in terms of the technical architecture, and how the telco has organised itself to operate it.

To test this hypothesis, we conducted primary research with fifteen telecoms operators at different stages in their telco cloud journey. We asked them about their deployments to date, how they have been delivered, the challenges encountered, how successful they have been, and how they see things unfolding in the future.

Our sample includes individuals leading telco cloud deployment at a range of mobile, fixed and converged network operators of all shapes and sizes, and in all regions of the world. Titles vary widely, but include Chief Technology Officers, Heads of Technology Exploration and Chief Network Architects. Our criteria were that individuals needed to be knee-deep in their organisation’s NFV deployments, not just from a strategic standpoint, but also close to the operational complexities of making it happen.

What we found is that most telco cloud deployments to date fall into two categories, driven by the operator’s starting point in making the decision to proceed:

Figure 5: Two starting points for deploying telco cloud

Function-first "we need to virtualise XYZ" vs platform-first "we want to build a cloud platform"

Source: STL Partners

The operators we spoke to were split between these two camps. What we found is that the starting points greatly affect how the technology is deployed. In the coming pages, we will explain both in more detail.

Table of contents

  • Executive Summary
  • Telco cloud: big promises, undelivered
    • A network running in the cloud
    • The telco cloud promise
    • The less-exciting reality
  • The problem: flawed approaches to deployment
    • Learning from those on the front line
    • A function-first approach to telco cloud
    • A platform-first approach to telco cloud
  • The solution: change, collaboration and integration
    • Multi-vendor telco cloud is preferred
    • The internal transformation problem
    • The need to foster collaboration and integration
    • Standards versus blueprints
    • Insufficient management and orchestration solutions
    • Vendor partnerships and pre-integration
  • Conclusions: A better telco cloud is possible, and 5G makes it an urgent priority

Big data analytics – Time to up the ante

Introduction

Recent years have seen an explosion in the amount of data being generated by people and devices, thanks to more advanced network infrastructure, widespread adoption of smartphones and related applications, and digital consumer services. With the expansion of the Internet of Things (IoT), the amount of data being captured, stored, searched and analysed will only continue to increase. Such is the volume and variety of the data that it is beyond traditional processing software and is therefore referred to as ‘big data’.

Big data is of a greater magnitude and variety than traditional data, it comes from multiple sources and can be comprised of various formats, generated, stored and utilised in batches and/or in real-time. There is much talk and discussion around big data and analytics and its potential in many sectors, including telecommunications. As Figure 1 shows, analysis of big data can give an improved basis upon which to base human-led and automated decisions by providing better insight and allowing greater understanding of the situation being addressed.

Figure 1: Using Big Data can result in richer data insights

Source: STL Partners

This report analyses how telcos are pursuing big data analytics, and how to be successful in this regard.  This report seeks to answer the following questions:

  • When does data become ‘big’ and why is it an important issue for telcos?
  • What is the current state of telco big data implementations?
  • Who is doing what in terms of intelligent use of data and analytics?
  • How can big data analytics improve internal operational efficiencies?
  • How can big data be used to improve the relationship between telcos and their customers?
  • Where are the greatest revenue opportunities for telcos to employ big data, e.g. B2B, B2C?
  • Which companies are leading the way in enabling telcos to successfully realise big data strategies?
  • What is required in terms of infrastructure, dedicated teams and partners for successful implementation?

This report discusses implementations of big data and examines how the market will develop as telco awareness, understanding and readiness to make use of big data improves.  It provides an overview of the opportunities and use cases that can be realised and recommends what telcos need to do to achieve these.

Contents:

  • Executive Summary
  • Big data analytics is important
  • …but it’s not a quick win
  • …it’s a strategic play that takes commitment
  • How is ‘big data analytics’ different from ‘analytics’?
  • Opportunities for telcos: typically internal then external
  • Market development and trends
  • Challenges and restrictions in practice
  • What makes a successful big data strategy?
  • Next steps
  • Introduction
  • Methodology
  • An overview of big data analytics
  • Volume, variety and velocity – plus veracity and value
  • The significance of big data for telcos and their future strategies
  • Market development and trends
  • Challenges and restrictions
  • Optimisation and efficiency versus data monetisation
  • Telcos’ big data ecosystem
  • Case studies and results 
  • Early results
  • Big data analytics use cases
  • Examples of internal use-cases
  • Examples of external use cases
  • Findings, conclusions and recommendations

Figures:

  • Figure 1: Using Big Data can result in richer data insights
  • Figure 2: The data-centric telco: infusing data to improve efficiency across functions
  • Figure 3: Options for telcos’ big data implementations
  • Figure 4: Telco’s big data partner ecosystem
  • Figure 5: The components of a telco-oriented big data

Great customer experience: What’s the secret?

Introduction: How important is customer centricity for telecoms operators?

The need for improvement

Many network operators appreciate the need to improve their customers’ overall experience if their businesses are to prosper. Their executives understand the effect customer experience has on churn and customer lifetime value, and in turn on market share, operating costs, and revenues. This relationship is illustrated in Figures 2 and 3 for mobile telecoms, pay TV and internet. Using ‘Net Promoter Scores’ (NPS), the most widely accepted measure of customer satisfaction, it shows the relationship between NPS promoters (those more positive than negative and willing to promote the brand), passives (neither positive nor negative) and detractors (those who actively dissuade others), and churn and lifetime value.

Figure 2: NPS Promoters, Passives & Detractors vs Churn and Lifetime Value

Source: Bain & Co

Figure 3: Lifetime Value of Promoters, Passives and Detractors

Source: Bain & Co

While most appreciate in general terms what customer centricity means, it is not always well understood what good customer centric service should look like in practice, or how it can be achieved. Many would say that a service where all systems worked properly, customer queries were answered correctly, problems resolved quickly and few if any complaints were made to the national regulator, was providing a fully satisfactory service to its customers, and therefore providing a good customer experience. Given the complexities of delivering a mobile telecoms service, for many operators, delivering those would be an achievement.

However, that may not be what a customer regards as a good experience, and operators need to bear in mind that their customers compare them with other service providers, and not just other telecoms providers. They need to ask themselves if they should therefore aspire to something better than the satisfactory operation of their networks and services. To decide if that is the case, operators need to determine what a good customer experience is from a user’s standpoint, and establish means of assessing whether they have delivered that or not.

Contents:

  • Executive Summary
  • Introduction
  • How important is customer centricity for telecoms operators?
  • The need for improvement
  • What does customer centricity mean for operators?
  • Customer centric networks
  • Network performance to meet user needs
  • Customer premises networks
  • Customer centric services in a digital world
  • Improving service
  • Systems integration & AI
  • All channels to look and behave the same
  • Using AI to improve customer experience
  • Customer centric service enhancements
  • Customer centric service
  • Lessons from Ritz-Carlton, a premium service
  • Cricket: US MVNO increasing NPS, cutting churn
  • TELUS: Creating, recognising and measuring success
  • TELUS performance: Measuring success
  • Conclusions

Figures:

  • Figure 1: Key Steps to Deliver Satisfactory and Exceptional Service
  • Figure 2: NPS Promoters, Passives & Detractors vs Churn and Lifetime Value
  • Figure 3: Lifetime Value of Promoters, Passives and Detractors
  • Figure 4: US Consumer NPS Scores for Different Industries
  • Figure 5: Average NPS for Telecommunications Operators in 9 Developed Countries
  • Figure 6: Highest Scoring Companies in US for Their Sector 11Highest Scoring Companies in US for Their Sector
  • Figure 7: Importance of criteria for choosing a mobile internet provider
  • Figure 8: MobiNEX segmentation dimensions
  • Figure 9:  Mobinex H2 2016 – Average scores by country
  • Figure 10: Operator and Country Scores for Reliability and Speed
  • Figure 11: Cricket wireless tariff structure
  • Figure 12: Single customer view and omni-channel insights of CMOs
  • Figure 13: TOBi, Vodafone’s AI chatbot
  • Figure 14: Amelia functions and applications
  • Figure 15: Impact of AI on media company call handling
  • Figure 16: Change in cricket NPS score from Q3 2014 to Q3 2015
  • Figure 17: TELUS monthly churn
  • Figure 18: TELUS employee engagement
  • Figure 19: Number of complaints made to the CCTS by year
  • Figure 20: TELUS ARPU 2007 – 2016
  • Figure 21: TELUS EBITDA