Stakeholder model: Turn growth killers into growth makers

Introduction: The stakeholder model

Telecoms operators’ attempts to build new sources of revenue have been a core focus of STL Partners’ research activities over the years. We’ve looked at many telecoms case studies, adjacent market examples, new business models and technologies and other routes to explore how operators might succeed. We believe the STL stakeholder model usefully and holistically describes telcos’ main stakeholder groups and the ideal relationships that telcos need to establish with each group to achieve valuable growth. It should be used in conjunction with other elements of STL’s portfolio which examine strategies needed within specific markets and industries (e.g., healthcare) and telcos’ operational areas (e.g., telco cloud, edge, leadership and culture).

This report outlines the stakeholder model at a high level, identifying seven groups and three factors within each group that summarise the ideal relationship. These stakeholder and influencer groups include:

  1. Management
  2. People
  3. Customer propositions
  4. Partner and technology ecosystems
  5. Investors
  6. Government and regulators
  7. Society

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1. Management

Growth may not always start at the top of an organisation, but to be successful, top management will be championing growth, have the capabilities to lead it, and aligning and protecting the resources needed to foster it. This is true in any organisation but especially so in those where there is a strong established business already in place, such as telecoms. The critical balance to be maintained is that the existing business must continue to succeed, and the new growth businesses be given the space, time, skills and support they need to grow. It sounds straightforward, but there are many challenges and pitfalls to making it work in practice.

For example, a minor wobble in the performance of a multi-billion-dollar business can easily eclipse the total value of a new business, so it is often tempting to switch resources back to the existing business and starve the fledgling growth. Equally, perceptions of how current businesses need to be run can wrongly influence what should happen in the new ones. Unsuitable choices of existing channels to market, familiar but ill-fitting technologies, or other business model prejudices are classic bias-led errors (see Telco innovation: Why it’s broken and how to fix it).

To be successful, we believe that management needs to exhibit three broad behaviours and capabilities.

  1. Stable and committed long term vision for growth aligned with the Coordination Age.
  2. Suitable knowledge, experience and openness.
  3. Effective two-way engagement with stakeholders. (N.B. We cover the board and most senior management in this group. Other management is covered in the People stakeholder group.)

Management: Key management enablers of growth

management-leadership-vision-growth-indicators

Source: STL Partners

Stable and committed long-term vision for growth

The companies that STL has seen making more successful growth plays typically exhibit a long-term commitment to growth and importantly, learning too.

Two examples we have studied closely are TELUS and Elisa. In both cases, the CEO has held tenure in the long-term, and the company has demonstrated a clear and well managed commitment to growth.

In TELUS’s case, the primary area of growth targeted has been healthcare, and the company now generates somewhere close to 10% of its revenue from the new areas (it does not publish a number). It has been working in healthcare for over 10 years, and Darren Entwistle, its CEO, has championed this cause with all stakeholders throughout.

In Elisa’s case, the innovation has been developed in a number of areas. For example, how it couples all you can use data plans and a flat sales/capex ratio; a new network automation business selling to other telcos; and an industrial IoT automation business.

Again, CEO Veli-Matti Mattila has a long tenure, and has championed the principle of Elisa’s competitive advantage being in its ability to learn and leverage its existing IP.

…aligned with the Coordination Age

STL argues that the future growth for telcos will come by addressing the needs of the Coordination Age, and this in turn is being accelerated by both the COVID-19 pandemic and growing realisation of climate change.

Why COVID-19 and Climate change are accelerating the Coordination Age

COVID-19-and-Climate-change-Coordination-Age-STL

 

Source: STL Partners

The Coordination Age is based on the insight that most stakeholder needs are driven by a global need to make better use of resources, whether in distribution (delivery of resources when and where needed), efficiency (return on resources, e.g. productivity), and sustainability (conservation and protection of resources, e.g. climate change).

This need will be served through multi-party business models, which use new technologies (e.g. better connectivity, AI, and automation) to deliver outcomes to their customers and business ecosystems.

We argue that both TELUS and Elisa are early innovators and pathfinders within these trends.

Suitable knowledge, experience and openness

Having the right experience, character and composition in the leadership team is an area of constant development by companies and experts of many types.

The dynamics of the leadership team matter too. There needs to be leadership and direction setting, but the team must be able to properly challenge itself and particularly its leader’s strongest opinions in a healthy way. There will of course be times when a CEO of any business unit needs to take the helm, but if the CEO or one of the C-team is overly attached to an idea or course of action and will not hear or truly consider alternatives this can be extremely risky.

AT&T / Time Warner – a salutary tale?

AT&T’s much discussed venture into entertainment with its acquisitions of DirecTV and Time Warner is an interesting case in point here. One of the conclusions of our recent analysis of this multi-billion-dollar acquisition plan was that AT&T’s management appeared to take a very telco-centric view throughout. It saw the media businesses primarily as a way to add value to its telecoms business, rather than as valuable business assets that needed to be nurtured in their own right.

Regardless of media executives leaving and other expert commentary suggesting it should not neglect the development of its wider distribution strategy for the content powerhouse for example, AT&T ploughed on with an approach that limited the value of its new assets. Given the high stakes, and the personalised descriptions of how the deal arose through the CEOs of the companies at the time, it is hard to escape the conclusion that there was a significant bias in the management team. We were struck by the observation that it seemed like “AT&T knew best”.

To be clear, there can be little doubt that AT&T is a formidable telecoms operator. Many of its strategies and approaches are world leading, for example in change management and Telco Cloud, as we also highlight in this report.

However, at the time those deals were done AT&T’s board did not hold significant entertainment expertise, and whoever else they spoke with from that industry did not manage to carry them to a more balanced position. So it appears to us that a key contributing factor to the significant loss of momentum and market value that the media deals ultimately inflicted on AT&T was that they did not engineer the dynamics or character in their board to properly challenge and validate their strategy.

It is to the board’s credit that they have now recognised this and made plans for a change. Yet it is also notable that AT&T has not given any visible signal that it made a systemic error of judgement. Perhaps the huge amounts involved and highly litigious nature of the US market are behind this, and behind closed doors there is major change afoot. Yet the conveyed image is still that “AT&T knows best”. Hopefully, this external confidence is now balanced with more internal questioning and openness to external thoughts.

What capabilities should a management team possess?

In terms of telcos wishing to drive and nurture growth, STL believes there are criteria that are likely to signal that a company has a better chance of success. For example:

  • Insight into the realistic and differentiating capabilities of new and relevant markets, fields, applications and technologies is a valuable asset. The useful insight may exist in the form of experience (e.g. tenure in a relevant adjacent industry such as healthcare, or delivery of automation initiatives, working in relevant geographies, etc.), qualification (e.g. education in a relevant specialism such as AI), or longer term insight (which may be indicated by engagement with Research and Development or academic activities)

[The full range of management capabilities can be viewed in the report…..] 

 

2. People…

 

Table of Contents

  • Executive Summary
  • Introduction
  • Management
    • Stable and committed long-term vision for growth
    • …aligned with the Coordination Age
    • Suitable knowledge, experience and openness
    • Two-way engagement with stakeholders
  • People
    • Does the company have a suitable culture to enable growth?
    • Does the company have enough of the new skills and abilities needed?
    • Is the company’s general management collaborative, close to customers, and diverse?
  • Customer propositions
    • Nature of the current customer relationship
    • How far beyond telecoms the company has ventured
    • Investment in new sectors and needs
  • Partner and technology ecosystems
    • Successful adoption of disruptive technologies and business models
    • More resilient economics of scale in the core business
    • Technology and partners as an enabler of change
  • Investors
    • The stability of the investor base
    • Has the investor base been happy?
    • Current and forecast returns
  • Government and regulators
    • The tone of the government and regulatory environment
    • Current status of the regulatory situation
    • The company’s approach to government and regulatory relationships
  • Society
    • Brand presence, engagement and image
    • Company alignment with societal priorities
    • Media portrayal

Related research

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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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Culture, leadership and purpose in telcos: Four key actions

Understanding culture, leadership and purpose

STL Partners has surveyed 168 telco execs about leadership, culture and purpose in the telecoms industry.

This research is part of our overall programme to help understand and develop how telcos can optimise their performance and reinvigorate growth and innovation. Respondents were asked to think about the telco they knew best, and answer a series of questions relating to different drivers of success:

  • Culture: Values and behaviours and the telco’s employees
  • Leadership: The way in which leaders drive the organisation
  • Purpose: The reason that the telco exists and operates
  • Digital: The telco’s ‘digital’ goals, skills and capabilities

Respondents were a mix of senior executives from telecoms operators worldwide, across a variety of functions and geographies.

Findings include:

  • Half of respondents believe that it is harder to get things done in telecoms operators than elsewhere
  • Leadership vision, alignment and delivery are seen to be a significant enabler to success by 43% of respondents
  • There are mixed views of the impact of company culture on success: seen as a barrier by 57% and a significant enabler by 33%
  • Some telcos are outperforming others. For example, Elisa’s culture is perceived as significantly more effective than others
  • … and more.

We also explore correlation between answers to different questions to suggest four key actions to driving greater success.

Table of contents

  • Executive Summary
  • Introduction & methodology
  • Analysis of results
  • Full survey results
    • Culture
    • Leadership
    • Purpose
    • Digital
    • Correlation analysis
  • About STL Partners

 

Telco AI: How to organise and partner for maximum success

Not a passing fad: AI is becoming a core capability for telcos

Artificial intelligence (AI) has become a key enabler of the digital transformation journey for service providers in the telecoms industry, providing them with the insights and capabilities they need to be more agile and take a more software-centric approach to their role.

The document was researched and written independently by STL Partners, supported by Nokia. STL’s conclusions are entirely independent and build on ongoing research into the future of telecoms. STL Partners has been writing about telcos’ AI opportunities since 2016, looking first at how AI might improve the customer experience and then at the critical role AI might play in the future of network operations.

In this report, we provide a comprehensive overview of the state of AI in the telecoms industry. Supported by nearly a dozen in-depth interviews plus an online survey of more than 50 leading telcos around the world, we explore where the industry is looking to progress and how it is planning to do so — and identify the strategic and business opportunities that are being enabled by AI.

This report will be followed by a sequel that quantifies some of the business outcomes telcos can expect from specific AI application areas. In the coming months, we will also publish a report discussing how AI technology is evolving and presenting our vision of the telco AI roadmap.

What is artificial intelligence?

Before going any further, it is important to clarify what we mean by “artificial intelligence”. To us, AI is about using computing capabilities to perform tasks traditionally associated with humans (such as inference, planning, anticipation, prediction and learning) in human-like ways (e.g., autonomous, adaptive). Our definition incorporates machine learning (ML), which we define as a subset of AI that focuses on the ability of machines to receive datasets and adapt responses in pursuit of a goal.

These definitions attempt to encapsulate the distinction between AI and other forms of rules-based automation — although we acknowledge that in practice these lines are easily blurred.

Practically speaking, AI sits on a continuum of other related technologies and concepts, which we have covered at length in our previous reports. Figure 1 illustrates this continuum and depicts the stages we expect telcos will have to go through as they to move from manual to automated and then to AI-augmented processes.

Figure 1: Moving toward AI

The progression of AI maturity in four steps

Source: STL Partners

A long-term ambition for many telcos is to reach the orange zone in Figure 1: a state in which their systems and processes run and learn from themselves with human input limited to the setting of desired business goals. Beyond the targeted use of ML in certain applications, however, the industry and society as a whole are far from realising that ambition. It is still unclear what fully autonomous systems in a telco might look like in practice, let alone whether they will ever be achievable.

Today, most telcos are still figuring out how to play in the blue zone. They’re using targeted data analysis to inform largely human-led decision-making processes, or they’ve implemented some fixed-policy automation where machines follow a script written and inputted by a human. This is valuable work, but it is not the focus of this report. Instead, we focus on the middle section of Figure 1: on those fledging opportunities that move beyond rules-based automation and into the realm of ML-supported automation

Cutting through the hype

AI has generated considerable industry noise and media attention — so much so, in fact, that a recent survey of leading telcos awarded AI the title of “most overhyped emerging technology”. We believe this hype originates in a general lack of understanding of what AI is (and is not), as well as unrealistic expectations about what it can do for a business, how quickly it can be deployed, and how much ongoing work will be needed to manage it. While there is consensus that the technology has great potential, many telcos doubt it will deliver everything that has been promised up to now.

For those disillusioned by the hype, it is worth noting the impact of AI is much likelier to be evolutionary than revolutionary. The line between automation and AI is blurred; so, too, is the progression between the two. While AI has the potential to unlock new business opportunities, realising that potential will require patience and long-term investment.

And yet, the truth is that telcos are uniquely positioned to take full advantage of AI technology — largely because they’re already used to dealing with the huge volumes of data AI relies on. When telcos automate systems, networks and processes — particularly with the injection of AI — they benefit from feedback loops that further improve those automated processes. This drives simplicity in an industry rife with complexity.

The digital transformation we all talk about depends on driving out complexity and becoming more agile, and the only way to do that is by automating intelligently. Looking ahead to the launch of 5G, it will become impossible for telcos to manage billions of connected devices without AI assistance.

Telcos’ current AI focus: Improving speed and efficiency

Key learnings on telco AI initiatives

Through our research, we have identified five primary domains of activity for telcos looking to make use of AI. The first three broadly relate to business process improvement, with the end goal of reducing costs and improving efficiency.

  1. Optimising existing networks and operations. Telcos are using AI not only for network planning and optimisation, but also to improve their human resources, accounting and fraud-management functions. For example, Telefónica has built an ML model capable of monitoring the status of the network, predicting possible failures and an optimising maintenance routes.[1] This has been particularly important in its rollout and maintenance of networks across rural Latin America, where it can take an engineer up to a day to travel to the site of a network fault.
  2. Improving sales and marketing activity. This includes upselling, cross-selling and agent augmentation. Globe Telecom, for example, has created a data-management platform that collates network signal information alongside information from billing and payment systems to provide personalised offers to its mobile customers.[2]
  3. Improving the customer experience. This includes use cases such as fault resolution, churn management, chatbots and virtual assistants. Vodafone has developed the chatbot TOBi, for example, which can handle 70 percent of customer requests and employs ML technology to further improve the support it offers to customers.[3]

The remaining two domains focus on using AI to enable new ways of working that go beyond a telco’s core connectivity offering, with a focus on growing revenues.

  1. Driving (and monetising) customer data. AI can help telcos aggregate massive volumes of anonymised customer data that can then be sold to third parties. Singtel’s DataSpark has taken a step down this data-as-a-service route, providing access to GPS and mobile network data that other organisations can incorporate into their applications and services.[4]
  2. Enabling or supporting new services. This includes cybersecurity and predictive analytics. As an example, AT&T is using ML to quickly identify normal and abnormal activity in it networks.[5] This sort of solution could be sold as a managed service to other enterprises in the future, unlocking a new revenue stream.

Contents of the full report include:

  • Executive Summary
  • Not a passing fad: AI is becoming a core capability for telcos
  • What is artificial intelligence?
  • Cutting through the hype 8
  • Telcos’ current AI focus: Speed and efficiency
  • How are telcos using AI today?
  • Sharing is caring: How telco AI initiatives are organised
  • Centralised AI initiatives
  • Cross-functional R&D units
  • Individual AI initiatives
  • The stumbling blocks for AI implementation — and how to get around them
  • AI initiatives need to be powered by high-quality data
  • Data governance is an essential requirement
  • Exploring the link between data maturity and AI success
  • The tricky transition from the lab to in-field deployment
  • Accept failure and embrace innovation
  • Revamp partnership strategies
  • New challenges, new expectations
  • Finding the impact: How telcos assess the benefits of AI
  • Different types of telcos, different levels of AI maturity
  • Conclusion

Figures:

  1. Moving toward AI
  2. Telco AI initiatives by domain
  3. Centrally coordinated AI initiatives are more likely to scale
  4. Poor data and a lack of internal skills are key challenges
  5. Telcos struggle with data management at every step of the AI journey
  6. Issues with data governance do not preclude AI implementation
  7. Only 1 in 5 AI projects has advanced to live deployment
  8. Collaborative partnering is key to AI success
  9. Nearly half of telcos have not gone live with AI
  10. Fixed-line and wholesale operators lag behind


[1] Source: Telefónica

[2] Source: Cloudera

[3] Source: Vodafone

[4] Source: DataSpark

[5] Source: AT&T

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

Five telcos changing culture: Lessons from neuroscience

Introduction: The role of skills and culture in telco transformation

Skills and culture are the biggest barriers to transformation

It is generally accepted that the telecoms industry is currently undergoing a major process of transformation. In very general terms, telcos are engaged in a transition from being primarily operators of physical infrastructure and networks designed for the efficient delivery of analogue voice and packet data services, to being providers of cloud-based (distributed software, IT and virtualised) infrastructure, platforms and digital services (including communications).

STL Partners has documented this sea change in numerous previous reports focusing on different aspects of the transformation: technology, processes, business models, organisation and culture. This report focuses more closely on two interrelated aspects: skills and culture.

A recent STL Partners ‘summit’ workshop of leading SE Asian operators found that skills and culture are presently seen as the greatest barriers to transformation:

Figure 1: Benefits of and obstacles to transformation

Source: STL Partners

The above chart, reporting the results of a snap survey of attendees of the SE Asia summit, could be interpreted as implying that skills and culture change are of very little direct benefit to telcos, given that only two respondents indicated that it had “the greatest value” to their organisation. But at the same time, telcos are clearly focused on addressing the skills and culture issue, as this was overwhelmingly the most salient transformation challenge that the senior operator executives picked out. And the results of this small but high-quality survey are entirely consistent with STL Partners’ findings in other parts of the world, including research conducted for this report (see Sections 2 and 3 below).

There is a chronic shortage of essential software and IT skills in the industry

Precisely why have skills and culture emerged as such a critical challenge at this time? The skills issue is easier to analyse. The new business and technology model to which operators are transforming places a much greater emphasis on software and IT skills than traditional telco operations: skills such as software development and coding; digital product development and operations (DevOps), and marketing; cloud and IT infrastructure deployment, maintenance and support; etc. There is a chronic shortage of highly-skilled people in these areas, which varies country by country but could rightly be described as a global shortage owing to the international character of the telecoms industry. It is the top talent that is needed right now given the complexity of the technological and IT challenges that are involved in the migration from the legacy Telco 1.0 to the telco-cloud service provider (Telco 2.0).

Telcos have adopted a variety of methods to try to close the skills gap. These are discussed in more detail in Sections 2 and 3 below in the context of conversations on skills and culture we have had with five operators from different parts of the world. On skills, these operators have adopted three broad approaches:

  • Aim to fulfil the skills requirements of the business from existing staff as much as possible by giving every employee the opportunity to up- and reskill (AT&T)
  • Try to meet the skills needs of the business through a combination of selective hires and retraining; but accept that a given percentage of positions in the company after the transformation phase can only be filled by new hires, and that existing staff whose functions have become redundant or who cannot adapt will need to be let go (Telkom Indonesia, Middle Eastern operator (MEO), and international enterprise networking provider (EO))
  • Accept that the business needs to transform radically and rapidly, and a relatively high percentage of people without the requisite skills or whose roles have become redundant must be let go (former developed-market incumbent (DMI))

Content:

  • Executive Summary
  • 1. Introduction: The role of skills and culture in telco transformation
  • 2. AT&T: A textbook exercise in re-skilling and culture change
  • 3. Two other models of skills development and culture change
  • 4. Conclusion: Skills are necessary but not sufficient, without culture

Figures:

  • Figure 1: Benefits of and obstacles to transformation
  • Figure 2: Old and new telco cultures and business model
  • Figure 3: MRI scans showing parts of the brain activated by social rejection and physical pain

NFV and OSS: Virtualization meets reality

Introduction: New virtual network, same old OSS

The relationship between NFV and OSS

This report discusses the relationship between NFV (Network Functions Virtualization) and OSS (Operations Support Systems), and the difficulties that operators and the developer community are facing in migrating from legacy OSS to NFV-based methods for delivering and managing services.

OSS are essentially the software systems and applications that are used to deliver services and manage network resources and elements in legacy telecom networks – such as, to name but a few:

  • Service provisioning: designing and planning a new service, and deploying it to the network elements required to deliver it
  • Service fulfillment: in its broader definition, this corresponds to the ‘order-to-activation’ (O2A) process, i.e. the sequence of actions enabling a service order to be logged, resourced on the network, configured to the relevant network elements, and activated
  • Service assurance: group of processes involved in monitoring network performance and service quality, and in proactively preventing or retrospectively repairing defective performance or network faults
  • Inventory and network resource management: managing the physical and logical network assets and service resources; keeping track of their utilization, condition and availability to be allocated to new services or customers; and therefore, closely related to service fulfillment and assurance.

As these examples illustrate, OSS perform highly specific management functions tied to physical network equipment and components, or Physical Network Functions (PNFs). As part of the migration to NFV, many of these PNFs are now being replaced by Virtualized Network Functions (VNFs) and microservices. NFV is developing its own methods for managing VNFs, and for configuring, sequencing and resourcing them to create, deliver and manage services: so-called Management and Orchestration (MANO) frameworks.The MANO plays a critical role in delivering the expected benefits of NFV, in that it is designed to enable network functions, resources and services to be much more easily programmed, combined, modified and scaled than is possible with PNFs and with OSS that perform isolated functions or are assigned only to individual pieces of kit.The problem that operators are now confronting is that many existing OSS will need to be retained while networks are transitioning to NFV and MANO systems. This is for a number of reasons. 

  • Executive Summary
  • Next Steps
  • Introduction: New virtual network, same old OSS
  • The relationship between NFV and OSS
  • Potential solutions and key ongoing problem areas
  • Conclusion: OSS may ultimately be going away – but not anytime soon
  • OSS-NFV interoperability: three approaches
  • OSS-NFV integration method Number 1: use the existing BSS / OSS to manage both legacy and virtualized services
  • OSS-NFV integration method number 2: Use a flexible combination of existing OSS for legacy infrastructure and services, and MANO systems for NFV
  • OSS-NFV integration method number 3: Replace the existing OSS altogether using a new MANO system
  • Three critical problem areas: service assurance, information models, and skills
  • 1. Closed-loop service fulfillment and assurance
  • 2. A Common Information Model (CIM)
  • 3. Skills, organization and processes

 

  • Figure 1: Classic TMN BSS / OSS framework
  • Figure 2: Telcos’ BSS / OSS strategy for NFV
  • Figure 3: Transition from BSS / OSS-driven to NFV-driven service management as proposed by Amdocs
  • Figure 4: NFV / SDN functions as modules within the Comarch OSS architecture
  • Figure 5: Closed-loop network capacity augmentation using Netscout virtual IP probes and a common data model
  • Figure 6: Service-driven OSS-MANO integration according to Amdocs
  • Figure 7: HPE’s model for OSS-MANO integration
  • Figure 8: BSS and OSS still out of scope in OSM 1.0
  • Figure 9: Subordination of OSS to the MANO system in Open-O
  • Figure 10: Vodafone Ocean platform architecture
  • Figure 11: Vodafone’s VPN+ PoC
  • Figure 12: Operators’ main concerns regarding NFV
  • Figure 13: Closed-loop service fulfillment and assurance
  • Figure 14: Relationship between Information Model and Data Models

The Devil’s Advocate: SDN / NFV can never work, and here’s why!

Introduction

The Advocatus Diaboli (Latin for Devil’s Advocate), was formerly an official position within the Catholic Church; one who “argued against the canonization (sainthood) of a candidate in order to uncover any character flaws or misrepresentation evidence favouring canonization”.

In common parlance, the term a “devil’s advocate” describes someone who, given a certain point of view, takes a position they do not necessarily agree with (or simply an alternative position from the accepted norm), for the sake of debate or to explore the thought further.

SDN / NFV runs into problems: a ‘devil’s advocate’ assessment

The telco industry’s drive toward Network Functions Virtualization (NFV) got going in a major way in 2014, with high expectations that the technology – along with its sister technology SDN (Software-Defined Networking ) – would revolutionize operators’ abilities to deliver innovative communications and digital services, and transform the ways in which these services can be purchased and consumed.

Unsurprisingly, as with so many of these ‘revolutions’, early optimism has now given way to the realization that full-scope NFV deployment will be complex, time-consuming and expensive. Meanwhile, it has become apparent that the technology may not transform telcos’ operations and financial fortunes as much as originally expected.

The following is a presentation of the case against SDN / NFV from the perspective of the ‘devil’s advocate’. It is a combination of the types of criticism that have been voiced in recent times, but taken to the extreme so as to represent a ‘damning’ indictment of the industry effort around these technologies. This is not the official view of STL Partners but rather an attempt to explore the limits of the skeptical position.

We will respond to each of the devil’s advocate’s arguments in turn in the second half of this report; and, in keeping with good analytical practice, we will endeavor to present a balanced synthesis at the end.

‘It’ll never work’: the devil’s advocate speaks

And here’s why:

1. Questionable financial and operational benefits:

Will NFV ever deliver any real cost savings or capacity gains? Operators that have launched NFV-based services have not yet provided any hard evidence that they have achieved notable reductions in their opex and capex on the basis of the technology, or any evidence that the data-carrying capacity, performance or flexibility of their networks have significantly improved.

Operators talk a good talk, but where is the actual financial and operating data that supports the NFV business case? Are they refusing to disclose the figures because they are in fact negative or inconclusive? And if this is so, how can we have any confidence that NFV and SDN will deliver anything like the long-term cost and performance benefits that have been touted for them?

 

  • Executive Summary
  • Introduction
  • SDN / NFV runs into problems: a ‘devil’s advocate’ assessment
  • ‘It’ll never work’: the devil’s advocate speaks
  • 1. Questionable financial and operational benefits
  • 2. Wasted investments and built-in obsolescence
  • 3. Depreciation losses
  • 4. Difficulties in testing and deploying
  • 5. Telco cloud or pie in the sky?
  • 6. Losing focus on competitors because of focusing on networks:
  • 7. Change the culture and get agile?
  • 8.It’s too complicated
  • The case for the defense
  • 1. Clear financial and operational benefits:
  • 2. Strong short-term investment and business case
  • 3. Different depreciation and valuation models apply to virtualized assets
  • 4. Short-term pain for long-term gains
  • 5. Don’t cloud your vision of the technological future
  • 6. Telcos can compete in the present while building the future
  • 7. Operators both can and must transform their culture and skills base to become more agile
  • 8. It may be complicated, but is that a reason not to attempt it
  • A balanced view of NFV: ‘making a virtual out of necessity’ without making NFV a virtue in itself