Innovation leader case study: Telefónica Tech AI of Things

The origins of Telefónica Tech AI of Things

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

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

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

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

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

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

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

Timeline of Telefónica’s data monetisation business

Telefonica-data-monetisation-luca-AI-IoT

Source: STL Partners, Charlotte Patrick Consult

Points to note on the timeline above:

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

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

The formation of Telefónica Tech

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

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

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

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

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

Table of contents

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

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The Internet of Things: Impact on M2M, where it’s going, and what to do about it?

Introduction

From RFID in the supply chain to M2M today

The ‘Internet of Things’ first appeared as a marketing term in 1999 when it was applied to improved supply-chain strategies, leveraging the then hot-topics of RFID and the Internet.

Industrial engineers planned to use miniaturised, RFID tags to track many different types of asset, especially relatively low cost ones. However, their dependency on accessible RFID readers constrained their zonal range. This also constrained many such applications to the enterprise sector and within a well-defined geographic footprint.

Modern versions of RFID labelling have expanded the addressable market through barcode and digital watermarking approaches, for example, while mobile has largely removed the zonal constraint. In fact, mobile’s economies of scale have ushered in a relatively low-cost technology building block in the form of radio modules with local processing capability. These modules allow machines and sensors to be monitored and remotely managed over mobile networks. This is essentially the M2M market today.

M2M remained a specialist, enterprise sector application for a long time. It relied on niche, systems integration and hardware development companies, often delivering one-off or small-scale deployments. For many years, growth in the M2M market did not meet expectations for faster adoption, and this is visible in analyst forecasts which repeatedly time-shifted the adoption forecast curve. Figure 1 below, for example, illustrates successive M2M forecasts for the 2005-08 period (before M2M began to take off) as analysts tried to forecast when M2M module shipment volumes would breach the 100m units/year hurdle:

Figure 1: Historical analyst forecasts of annual M2M module shipment volumes

Source: STL Partners, More With Mobile

Although the potential of remote connectivity was recognised, it did not become a high-volume market until the GSMA brought about an alignment of interests, across mobile operators, chip- and module-vendors, and enterprise users by targeting mobile applications in adjacent markets.

The GSMA’s original Embedded Mobile market development campaign made the case that connecting devices and sensors to (Internet) applications would drive significant new use cases and sources of value. However, in order to supply economically viable connected devices, the cost of embedding connectivity had to drop. This meant:

  • Educating the market about new opportunities in order to stimulate latent demand
  • Streamlining design practices to eliminate many layers of implementation costs
  • Promoting adoption in high-volume markets such as automotive, consumer health and smart utilities, for example, to drive economies of scale in the same manner that led to the mass-adoption of mobile phones

The late 2000’s proved to be a turning point for M2M, with the market now achieving scale (c. 189m connections globally as of January 2014) and growing at an impressive rate (c. 40% per annum). 

From M2M to the Internet of Things?

Over the past 5 years, companies such as Cisco, Ericsson and Huawei have begun promoting radically different market visions to those of ‘traditional M2M’. These include the ‘Internet of Everything’ (that’s Cisco), a ‘Networked Society’ with 50 billion cellular devices (that’s Ericsson), and a ‘Cellular IoT’ with 100 billion devices (that’s Huawei).

Figure 2: Ericsson’s Promise: 50 billion connected ‘things’ by 2020

Source: Ericsson

Ericsson’s calculation builds on the idea that there will be 3 billion “middle class consumers”, each with 10 M2M devices, plus personal smartphones, industrial, and enterprise devices. In promoting such visions, the different market evangelists have shifted market terminology away from M2M and towards the Internet of Things (‘IoT’).

The transition towards IoT has also had consequences beyond terminology. Whereas M2M applications were previously associated with internal-to-business, operational improvements, IoT offers far more external market prospects. In other words, connected devices allow a company to interact with its customers beyond its strict operational boundaries. In addition, standalone products can now deliver one or more connected services: for example, a connected bus can report on its mechanical status, for maintenance purposes, as well as its location to deliver a higher quality, transit service.

Another consequence of the rise of IoT relates to the way that projects are evaluated. In the past, M2M applications tended to be justified on RoI criteria. Nowadays, there is a broader, commercial recognition that IoT opens up new avenues of innovation, efficiency gains and alternative sources of revenue: it was this recognition, for example, that drove Google’s $3.2 billion valuation of Nest (see the Connected Home EB).

In contrast to RFID, the M2M market required companies in different parts of the value chain to share a common vision of a lower cost, higher volume future across many different industry verticals. The mobile industry’s success in scaling the M2M market now needs to adjust for an IoT world. Before examining what these changes imply, let us first review the M2M market today, how M2M service providers have adapted their business models and where this positions them for future IoT opportunities.

M2M Today: Geographies, Verticals and New Business Models

Headline: M2M is now an important growth area for MNOs

The M2M market has now evolved into a high volume and highly competitive business, with leading telecoms operators and other service providers (so-called ‘M2M MVNOs’ e.g. KORE, Wyless) providing millions of cellular (and fixed) M2M connections across numerous verticals and applications.

Specifically, 428 MNOs were offering M2M services across 187 countries by January 2014 – 40% of mobile network operators – and providing 189 million cellular connections. The GSMA estimates the number of global connections to be growing by about 40% per annum. Figure 3 below shows that as of Q4 2013 China Mobile was the largest player by connections (32 million), with AT&T second largest but only half the size.

Figure 3: Selected leading service providers by cellular M2M connections, Q4 2013

 

Source: Various, including GSMA and company accounts, STL Partners, More With Mobile

Unsurprisingly, these millions of connections have also translated into material revenues for service providers. Although MNOs typically do not report M2M revenues (and many do not even report connections), Verizon reported $586m in ‘M2M and telematics’ revenues for 2014, growing 47% year-on-year, during its most recent earnings call. Moreover, analysis from the Telco 2.0 Transformation Index also estimates that Vodafone Group generated $420m in revenues from M2M during its 2013/14 March-March financial year.

However, these numbers need to be put in context: whilst $500m growing 40% YoY is encouraging, this still represents only a small percentage of these telcos’ revenues – c. 0.5% in the case of Vodafone, for example.

Figure 4: Vodafone Group enterprise revenues, implied forecast, FY 2012-18

 

Source: Company accounts, STL Partners, More With Mobile

Figure 4 uses data provided by Vodafone during 2013 on the breakdown of its enterprise line of business and grows these at the rates which Vodafone forecasts the market (within its footprint) to grow over the next five years – 20% YoY revenue growth for M2M, for example. Whilst only indicative, Figure 4 demonstrates that telcos need to sustain high levels of growth over the medium- to long-term and offer complementary, value added services if M2M is to have a significant impact on their headline revenues.

To do this, telcos essentially have three ways to refine or change their business model:

  1. Improve their existing M2M operations: e.g. new organisational structures and processes
  2. Move into new areas of M2M: e.g. expansion along the value chain; new verticals/geographies
  3. Explore the Internet of Things: e.g. new service innovation across verticals and including consumer-intensive segments (e.g. the connected home)

To provide further context, the following section examines where M2M has focused to date (geographically and by vertical). This is followed by an analysis of specific telco activities in 1, 2 and 3.

 

  • Executive Summary
  • Introduction
  • From RFID in the supply chain to M2M today
  • From M2M to the Internet of Things?
  • M2M Today: Geographies, Verticals and New Business Models
  • Headline: M2M is now an important growth area for MNOs
  • In-depth: M2M is being driven by specific geographies and verticals
  • New Business Models: Value network innovation and new service offerings
  • The Emerging IoT: Outsiders are raising the opportunity stakes
  • The business models and profitability potentials of M2M and IoT are radically different
  • IoT shifts the focus from devices and connectivity to data and its use in applications
  • New service opportunities drive IoT value chain innovation
  • New entrants recognise the IoT-M2M distinction
  • IoT is not the end-game
  • ‘Digital’ and IoT convergence will drive further innovation and new business models
  • Implications for Operators
  • About STL Partners and Telco 2.0: Change the Game
  • About More With Mobile

 

  • Figure 1: Historical analyst forecasts of annual M2M module shipment volumes
  • Figure 2: Ericsson’s Promise: 50 billion connected ‘things’ by 2020
  • Figure 3: Selected leading service providers by cellular M2M connections, Q4 2013
  • Figure 4: Vodafone Group enterprise revenues, implied forecast, FY 2012-18
  • Figure 5: M2M market penetration vs. growth by geographic region
  • Figure 6: Vodafone Group organisational chart highlighting Telco 2.0 activity areas
  • Figure 7: Vodafone’s central M2M unit is structured across five areas
  • Figure 8: The M2M Value Chain
  • Figure 9: ‘New entrant’ investments outstripped those of M2M incumbents in 2014
  • Figure 10: Characterising the difference between M2M and IoT across six domains
  • Figure 11: New business models to enable cross-silo IoT services
  • Figure 12: ‘Digital’ and IoT convergence