Tag: Horizontal

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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Telco data monetisation: What is it worth?

Data revenue opportunities are variable

Monetisation of telco data has been an area of activity for the last six years. However, telcos’ interest levels have varied over time due to the complexity of delivering and selling such a diverse range of products, as well as highly variable revenue opportunities depending on the vertical. Telcos’ appetite to pursue data monetisation has also been heavily impacted by the fortunes of other new telco products, in particular IoT, owing to the link between many data/analytics products and IoT solutions.

This report assesses the opportunity for telcos to monetise their data and provide associated data analytics products in two parts:

  1. First, we look at the range of products and services a telco needs to create in order to deliver financial value.
  2. Then, we explore the main use cases and actual financial value of telco data analytics products across 12 verticals, plus horizontal solutions that apply to multiple verticals.

Telco data monetisation: Calculation methodology

The methodology used to model the financial value of telco data analytics is outlined in the figure below.

  • The starting point for this analysis is 210 data or data analytics use cases, spread across 12 verticals and the horizontal solutions applicable to multiple verticals.
  • We then assess how difficult it is for a telco to address each use case, based on pre-requisite supporting platforms and solutions, regulatory constraints, etc. (shown in red). This evaluation enables us to assess how likely telcos are to develop products for each use case.
  • Thirdly, we assess which types of telco are able to develop the use case (in yellow). For example, telcos in a market with particularly restrictive regulation around use of personal data are simply not able to create certain products.
  • Finally, it is necessary to understand whether the data/analytics products created for a use case can be offered as an independent, standalone product, or more likely to be provided as a bolt-on service to another, pre-existing solution. This question is primarily pertinent in the IoT space where basic data/analytics are likely to be included in the price of the IoT service.
    • For products that we expect to be sold independently, we calculate the potential revenue based on estimated pricing for the type of data product, where known, and likely volumes that a telco will sell in a year.
    • For data analytics products closely linked to IoT, we attach no monetary value.

Calculation methodology for the feasibility and value of telco data monetisation use cases

Rationale behind data monetisation potential

Source: STL Partners, Charlotte Patrick Consult

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Viewing the data

Underlying the analysis in this report is a database tool including a detailed assessment of each of the 210 data monetisation use cases we have identified, with numerical analysis and charting capabilities. We know many of our readers will be interested to explore the detailed data, and so have made it available for download on the website in the form of an Excel spreadsheet.

Full use case database and analysis available on our website

Source: STL Partners

Table of Contents

  • Executive Summary
  • Introduction
    • Calculation methodology
  • What is this market worth to telcos?
  • Creating products for data monetisation
    • Telco products for the ecosystem
    • Data and analytics for IoT
    • Use of location in data monetisation
  • Maximising value in different verticals
    • Advertising and market research
    • Agriculture
    • Finance
    • Government
    • Insurance
    • Healthcare
    • Manufacturing
    • Real estate and construction
    • Retail
    • Telecom, media and technology
    • Transportation
    • Utilities
    • Horizontal solutions for all verticals
  • Conclusion and recommendations
    • How to pick a winning project
  • Index

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M2M 2.0: Market, Business Models, and Telcos’ Role(s)

Summary: Our latest report on M2M 2.0 covers: M2M market growth, structure and dynamics; business models; the best role(s) for telcos; and leading thinking from Deutsche Telekom, Vodafone, Telenor, KPN and Swisscom. It describes how ‘Service Enablers’ are key to the telco opportunity in M2M in addition to connectivity. (July 2011, Executive Briefing Service) M2M Pie Chart Service Enablers July 2011
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Below is an extract from this 39 page Telco 2.0 Report that can be downloaded in full in PDF format by members of the Telco 2.0 Executive Briefing service here. Non-members can buy a Single User license for this report online here for £595 (+VAT) or subscribe here. For multiple user licenses or other enquiries please email contact@telco2.net or call +44 (0) 207 247 5003.

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Background

Our previous M2M 2.0 research includes: M2M 2.0: New Approaches Needed; Aligning M2M with Telco 2.0 Strategies; and M2M / Embedded Market Overview, Healthcare Focus, and Strategic Options. M2M is also a theme of the upccoming New Digital Economics Exeutive Brainstorms in H2 2011, and there is a thought-provoking video (registration required) by Ericsson on the ‘Social web of things‘ on our Best Practice Live! site.

It’s a Long Way to the Top

The grand vision of 50 Billion connected devices looks a long way distant when contemplating the ‘cottage industry’ that is M2M today.

While there are lots of possibilities for connecting devices usefully, there are numerous challenges to doing it well and growing the market to its full potential:

  • There are many different networks may be used for M2M – cellular, WiFi, WiMax, fixed, Bluetooth and other radio networks;
  • The needs of existing and potential M2M customers are very diverse;
  • There are many different types of potential M2M connectivity and services providers, from vertical specialists, through fixed and mobile telcos, other network owners, and device makers;
  • There are many diverse M2M devices, some with have 30 year life-spans, others lives measured in months;
  • And massive growth in intelligent devices that can increasingly choose different networks for different applications.

There are also industry barriers to the take-up of current offerings, such as

  • The lack of common, global, flexible solutions;
  • Performance and cost issues;
  • A low base of user and potential awareness and understanding.

Figure 3 (Extract) – The Key Challenge for M2M Growth is to Create a Broad, Open Market

M2M 2.0 rating of the industry barriers to M2M adoption

Source: Delegate Vote, 11th Telco 2.0 EMEA Brainstorm

More Money is in Service Enablers

It is our view (and that of the attendees at our last M2M brainstorm) that the pure connectivity revenues (to be paid for delivering the data from machine to machine) will become highly commoditised and low margin.

The “growth opportunity” will be in Software Enabling Services (SES), responsible for such activities as device provisioning, update/rollback of device software and firmware, data-warehousing, and some forms of data reduction pushed down into the network. These could be delivered traditionally or as Software-as-a-Service (SaaS).

How much Money, and for Whom?

The complex driving and structural factors lead to a high degree of uncertainty in the Industry’s view of the market opportunity. For example, on average, delegates thought that by 2015, service enabler revenues would comprise a value of 78% of connectivity revenues – although this average was formed by a large group that thought it would be in the range 20-40% and a small minority that thought it would be much higher (>200%)

What role(s) should Telcos play?

Operators can add value by making it easier to use their connectivity and providing more “M2M-friendly” interfaces – often described as managed connectivity. Beyond this, they can look to create and participate in the service enablers market for developers/application providers to easily identify, authenticate, provision, and maintain their device fleet; to update and rollback software on the devices and enable them to deploy processing logic into the “Internet of things” in order to render the system more robust, distributed, and autonomous.

Some operators already have the skills and resources to offer the application development, implementation and service hosting on top of this. Summarised in the report are examples of leading thinking and practice including Vodafone’s Global M2M Platform, Telenor Objects, Deutsche Telekom’s ‘Intelligent Network’, KPN’s and Swisscom’s platforms, plus we have previously reported on Verizon’s Open Development Initiative (ODI) in the US.

Figure 7 (Extract) – Why The Classical Approach to M2M May Fail

M2M 2.0 Why the classical approach may fail July 2011

Source: Telenor Presentation

The industry as a whole has made rapid progress but could do much more to stimulate the embedded mobility market and drive growth through standards, interoperability and portability. The industry’s historical reluctance to do more to open itself up has left it vulnerable to being marginalized. The GSMA’s recent acceptance of over-the-air (OTA) SIM update, opens up the promise of more practical ways for an M2M customer to switch operator. It now rests on the industry (or failing that, the regulatory authorities) to deliver this promise.

Telco 2.0 Take-Out & Next Steps

M2M is growing up as an industry, and becoming more coherent and adopting increasingly similar concepts and vocabulary. However, as the wide variation in voting testifies, there is still considerable divergence in understanding and vision.

The M2M Opportunity is potentially significant but does not necessarily belonging to cellular networks, particularly if the industry does not work out how to create more common models that allow customers to use M2M in the way they actually need to use it – flexibly, seamlessly and cheaply.

While there is much energy in the debate on Machine-to-Machine in the operator community, there is widespread recognition that it is still something of a ‘cottage industry’ for operators at present, and a welcome sense of realism in that operators seem to understand that they don’t have all the answers. The core strategic challenge is to find a model that will scale beyond bespoke vertical industry applications.

While there is not yet a straightforward consensus on the relative value of service enablers compared to connectivity, our view remains that telcos need to develop the service enabler model as the connectivity market will be highly commoditised. We will continue to work to support this community, develop the service enabler model, and promote collective industry progress on M2M.

To read the full 39 page report, including analysis of the presentations, voting and delegate analysis from the M2M 2.0 Executive Brainstorms in April 2011, and London in November 2010, and the following charts…

  • Figure 1- T-Mobile’s Forecast of European M2M Markets
  • Figure 2 – Vodafone’s Global M2M Platform
  • Figure 3 – The Key Challenge for M2M Growth is to Create a Broad, Open Market
  • Figure 4 – What is the best service enabler opportunity for telcos?
  • Figure 5 – Will connectivity and generic horizontal service enabler platforms emerge and define the market?
  • Figure 6 – What are the priorities for the industry in developing M2M opportunities?
  • Figure 7 – Why ‘classical’ approaches to M2M may fail
  • Figure 8 – Horizontally layered approach needed
  • Figure 9 – KPN Development Platform
  • Figure 10 – Forecast share of service enabler revenue by type of player
  • Figure 11 – 2015 Global Service Enabler vs. Connectivity Revenues
  • Figure 12 – Issues for the ‘Internet of Things’
  • Figure 13 – Operator opportunities in the ‘Internet of Things’
  • Figure 14 – How would you characterise Ericsson’s vision of the Social Web of Things?
  • Figure 15 – What percentage of connections will be made by cellular mobile networks in 2020?

……Members of the Telco 2.0 Executive Briefing Subscription Service can download the full 39 page report in PDF format here. Non-Members, please see here for how to subscribe, here to buy a single user license for £595, or for multi-user licenses and any other enquiries please email contact@telco2.net or call +44 (0) 207 247 5003.

Organisations, products and industry terms referenced: API, ARPU, Beecham Research, Bluetooth, Bosch, BT / Arqiva, Cincius, connected car, Deutsche Telekom, Embedded Mobile, energy, Enfora, Ericsson, Facebook, GSM, GSMA, healthcare, HLR, HTTP, IMSI, Indesit, intelligent networks, Internet of things, iPhones, Kindle, KPN, Logica, M2M, messaging, m-health, MNC, MVNE, MVNO, Novatel, Objects, Open Development Initiative, Orange, OTA, OTT, platforms, roaming, SaaS, Service Enabler, SIM, smart grid, SMS, Social Web of Things, Software-as-a-Service, spectrum policy, standardization, strategy, Swisscom, Telenor, Telenor Objects, T-Mobile, transport, USIM, Verizon, Vertical, Vertical M2M, Vodafone, WiMAX, Zigbee.