Mobile Operator Business Models

Overview

- High Value Strategic Planning Tool
- Expert Analysis of MNO Opportunities
- In Depth Business Model Comparison

Mobile Operators face unprecedented challenges over the next few years. As revenues begin to flatline – the result of market saturation allied to declining ARPUs – and the surge in data usage pushes backhaul costs ever higher, how will operators survive the squeeze? And can they avoid a nightmare scenario wherein costs overtake revenues?

This report examines the critical challenges facing MNOs and delivers essential adaptive strategies necessary to maintain attractive margins in the future.  These dynamic solutions cover both the optimisation of core revenues plus the development of new revenue streams, while also providing strategies designed to dramatically reduce operating costs.

This ground breaking study includes an innovative matrix which enables tier 1 and tier 2 operators in both developed and developing markets to prioritise their strategic decisions and maximise their revenue potential.

Table of Contents

Executive Summary

1. The Problem Stated: A Saturated World

1.1 Introduction    13
1.2 A Saturated World    14
Figure 1.1: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2003-2010    14
Table 1.1: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2003-2010    14
Table 1.2: Historical Mobile Penetration Rates Split by 8 Key Regions 2003-2010    15
Table 1.3: Forecast Mobile Penetration Rates Split by 8 Key Regions 2011-2016    15
Figure 1.2: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2011-2016    16
Table 1.4: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2011-2016    16
1.2 MNO ARPUs are Declining    16
1.2.1Attributing Factors    16
Figure 1.3: Operator-billed Monthly ARPU ($) Split by 8 Key Regions 2005-2010    17
Table 1.5: Operator-billed Monthly ARPU ($) Split by 8 Key Regions 2005-2010    18
1.2.2 ARPU Base Line Analysis: Developed Markets    18
Figure 1.4: Base Line Analysis of Historic ARPU, Developed Markets 2005-2010    18
Table 1.6: Base Line Analysis of Historic ARPU, Developed Markets 2005-2010    19
1.2.3 ARPU Base Line Analysis: Developing/Emerging  Markets    19
Figure 1.5: Base Line Analysis of Historic ARPU, Developing/Emerging Markets 2005-2010    19
Table 1.7: Base Line Analysis of Historic ARPU, Developing/Emerging Markets 2005-2010    20
1.2.4 Regional ARPU Forecasts    20
Figure 1.6: Mobile ARPU ($) Split by 8 Key Regions 2011-2016    20
Table 1.8: Mobile ARPU ($) Split by 8 Key Regions 2011-2016    21
1.3 MNO Revenues are Plateauing    21
Figure 1.7: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2005-2010    21
Table 1.9: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2005-2010    22
Figure 1.8: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2011-2016    22
Table 1.10: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2011-2016    23

2. The Problem Stated: A Data-Centric World

2.1 Rising Opex: Data Delivery Costs    24
2.1.1 The Rise of the Mobile Internet    24
Table 2.1: Mobile Internet User Base (m) Split by 8 Key Regions 2006-2010    25
2.1.2 The Rise in Data Traffic    26
Figure 2.2: Total Data Traffic per Annum from Mobile Handsets (PB)  Split by 6 Data Categories 2009-2015    26
Table 2.2: Total Data Traffic per Annum from Mobile Handsets (PB)  Split by 6 Data Categories 2009-2015    27
Figure 2.3: Total Data Traffic Per Annum (PB) Carried Via Cellular Networks  Split by 8 Key Regions 2010-2015    27
Table 2.3: Total Data Traffic Per Annum (PB) Carried Via Cellular Networks  Split by 8 Key Regions 2010-2015    28
2.1.3 Cost Implications of the Data Surge    28
Table 2.4: Scenarios for Data Delivery Costs, 2015 Relative to 2010    29
Figure 2.4: Global Operator-Billed Service Revenues versus  Delivery Costs of Unoptimised Data ($bn) 2010 and 2015    29
2.2 Rising Capex: Network Buildout    29
2.2.1 Spectrum Costs    30
Table 2.5: German 800MHz Band Auction, May 2010    30
i. Case Study: Indian Spectrum Auction    31
Table 2.6: Bharti Airtel: 3G Subscribers (m) and ARPU from 3G Customers ($)  Split by Scenario (Modest, Median & High) 2011-2015    32
Figure 2.6: Bharti Airtel: Scenario-Based Cumulative Service Revenues ($m) from 3G Subscribers Split by Scenario (Modest, Median & High) 2011-2015    32
Table 2.7: Bharti Airtel: Scenario-Based Cumulative Service Revenues ($m) from 3G Subscribers Split by Scenario (Modest, Median & High) 2011-2015    33
2.2.2 Infrastructure Costs    33

3. The Problem Stated: The Evolving Mobile Ecosystem

3.1 The Traditional Mobile Value Chain & Value Web    34
Figure 3.1: Traditional Value Chain of Mobile Content    35
Figure 3.2: Mobile Content Value Web    35
Figure 3.3: App Store Value Chain    36
3.2 App Stores For All    36
Figure 3.4: Global Annual App Downloads (m) Split by 3 Distribution Channels 2007-2010    37
Table 3.1: Global Annual App Downloads (m) Split by 3 Distribution Channels 2007-2010    37
Figure 3.5 Global Annual App Revenues ($m) Split by 3 Distribution Channels 2007-2010    38
Table 3.2 Global Annual App Revenues ($m) Split by 3 Distribution Channels 2007-2010    38
3.2.1 Challenges for Network Operators    38
i. The Need for Scale    38
Figure 3.6: The Vicious Circle of the Addressable User Base    40
ii. The Content Legacy    40
Figure 3.7: The Content Legacy    41
iii. Monetising Download Volumes    41
iv. The Portal Revisited?    41
v. Fragmentation    42
3.3 Conclusion    43

4. The Problem Stated: Regulatory Factors

4.1 The Green Imperative    44
4.1.1 Developing Markets    44
4.1.2 Developed Markets    45
4.2 Pricing Controls    46
Figure 4.1: EU Average SMS Prices (€) Split by Retail & Wholesale Q2 2008-Q2 2010    46
Table 4.1: EU Average SMS Prices (€) Split by Retail & Wholesale Q2 2008-Q2 2010    46
Figure 4.2: EU Average Prices per MB of Roaming Data (€) Split Retail & Wholesale  Q2 2008-Q2 2010    47
Table 4.2: EU Average Prices per MB of Roaming Data (€) Split by Retail & Wholesale  Q2 2008-Q2 2010    47

5. Adaptive Strategies: Optimising Existing Revenue Streams

5.1 Customer Segmentation    49
5.1.1 Case Study – Orange    50
Table 5.1 Orange Animal Contract Tariffs, Lowest Rate in March 2011    50
Figure 5.1: Orange UK Postpaid Annualised Churn Rates 2006-2010    50
5.1.2 Extending The Contract is No Longer An Option    51
5.2 After Sales Service: Enhancing Customer Relationship Management    51
5.3 Prepaid/Postpaid Migration    52
5.4 Revamping the Bundle    52
5.4.1 Bundling the Smartphone    53
Figure 5.2: Orange France & T-Mobile Deutschland, Subscriber Retention Costs 2006-2010    53
5.4.2 Beyond the Smartphone: Bundling Other Devices    54
Table 5.2: Selected Connected Device Retail Costs, UK MNOs, April 2011    54
5.4.3 Assessing the Data Plan    55
i. To Tier or Not to Tier    55
ii. Returning to Flat Rate: 3 UK    56
Figure 5.3: UK Mobile Subscriber Base (mn), Split by MNO and Prepaid/Contract 2010    57
Table 5.3: UK Mobile Subscriber Base (mn) Split by MNO and Prepaid/Contract 2010    57
Figure 5.4: UK MNO ARPUs, Q4 2010 vs Implied All in One ASPU    58
Table 5.4: UK MNO ARPUs, Q4 2010 vs Implied All in One ASPU    58
iii. New Flat Rate Packages: US    58
iv. The Smartphone Premium    59
5.5 Making the Most of Mobile Content    59
5.5.1 A Third Party Solution?    59
5.5.2 Addressing Fragmentation    59
i. Case Study: GSMA OneAPI Initiative    59
ii. Case Study: Wholesale Application Community    60
iii. Will Alliances Bring Sufficient Scale?    61
iv. Monetising the Mass Market    62
a. Solution 1: Deploy Thin Clients    63
5.5.3 New Business Models: The Data/Content Bundle    63

6. Adaptive Strategies: New Revenue Streams

6.1 Opportunities in the Cloud    65
6.1.1  Introduction – The Transition to Cloud    65
6.1.2 Operator as Cloud Provider: Infrastructure as a Service    67
6.1.3 Operator as Cloud Provider: Platform as a Service    67
i. Consumer Case Study: Vodafone 360    67
Figure 6.1: Vodafone 360 H1 by Samsung    68
ii. Case Study: Cell C MyTools    68
iii. Enterprise Case Study: Verizon Wireless/Sierra Wireless    69
Figure 6.2: Sierra Wireless AirVantage Solution    69
6.1.4 Underlying Business Models    69
6.2 Beyond 3G – New Revenue Streams in a 4G Environment    71
6.2.1 Intelligent Networks:  Revenue Opportunities From Converged Services    71
6.2.2 Revenue Opportunities in Broadband Provision    72
6.3 Mobile Money Opportunities    73
Figure 6.3: Safaricom Data Revenues (KES bn) Split by Broadband, M-PESA & SMS  H1 2009-H1 2011    75
Table 6.1: Safaricom Data Revenues (KES bn) Split by Broadband, M-PESA & SMS  H1 2009-H1 2011    75
6.3.2 The Operator as Financial Service Enabler/Provider    76
Figure 6.4: MNO Mobile Money Revenue Opportunity ($m)  Split by Banking, Transfers & Remittances & NFC 2011-2015    77
Table 6.2: MNO Mobile Money Revenue Opportunity ($m)  Split by Banking, Transfers & Remittances & NFC 2011-2015    77
6.4 The M2M Opportunity    77
6.4.1 Defining Mobile M2M    77
6.4.2 Sizing the MNO M2M Opportunity    79
Figure 6.6: Operator M2M Opportunity:  Annual Connectivity & Enablement Revenues 2010-2016    80
Table 6.3: Operator M2M Opportunity:  Annual Connectivity & Enablement Revenues 2010-2016    80

7. Adaptive Strategies: Taking the Network Strain

7.1 Assessing the Scale of the Challenge – Offload Solutions    81
7.1.1 Established Offload Solutions – WiFi and Femtocells    82
Figure 7.1 Data Traffic (PB/Annum) Generated by Smartphones, Featurephones & Tablets, 2010-2015    82
Table 7.1 Data Traffic (PB/Annum) Generated by Smartphones, Featurephones & Tablets, 2010-2015    82
7.1.2 Emerging Offload Solutions – IMB    83
Figure 7.2: IMB Schematic    83
7.2 Network Optimisation    84
7.3 Addressing Base Station Opex    85
7.3.1 Addressing Site Lease Costs - Network Sharing    85
i. Active and Passive RAN sharing    86
Figure 7.3: Active vs Passive RAN Sharing Infrastructure Models    86
7.3.2 Improving the Efficiencies in the Base Station    87
Figure 7.4: Traditional Base Station Design    87
7.4 Reducing Opex in the RAN – the Cloud RAN Solution    88
Figure 7.5: lightRadio Network Architecture    89
7.5 Flattening the Network Architecture    89
7.6 Greening the Network – Reducing Opex and Meeting Sustainability Commitments    90
7.6.1 Case Study: China Mobile    90
Figure 7.6: China Mobile, Base Stations Powered by Sustainable Energy 2008-2010    91
Table 7.2: China Mobile, Base Stations Powered by Sustainable Energy 2008-2010    91
Table 7.3: Base Line Analysis of China Mobile Subscriber Growth vs CO2 Emissions and Energy Usage, 2007-2010    91
Figure 7.7: Base Line Analysis of China Mobile Subscriber Growth vs CO2 Emissions and Energy Usage, 2007-2010    92
7.6.2 Transitioning to Green Networks: the Environmental and Financial Imperative    92
Figure 7.8: CO2 Emissions (Mt) from Base Station Electricity Split by Scenario 2011-2014    93
Table 7.4: CO2 Emissions (Mt) from Base Station Electricity Split by Scenario, 2011-2014    93
Table 7.5: Base Station Electricity Costs ($m) Split by Scenario, 2011-2014    93
Figure 7.9: Base Station Electricity Costs ($m) Split by Scenario, 2011-2014    94
Appendix: Further Reading    95
Table A1: Suggested Further Reading    95

Companies Referenced

3, Airtel, AirVantage, Aito, Amazon, Apple, AT&T, Barclaycard, BBC, Best Buy, Bharti, Buongiorno, Buzzcity, Byte Mobile, China Mobile, Clearwire, Deutsche Telekom, Digital Chocolate, Ericsson, Everything Everywhere, Facebook, France Telecom, Funambol, funYun, GetJar, Google, Handango, Huawei, IPWireless, KDDI, Ladbrokes, LG, LightSquared, MBNL, MediaFLO, Mobixell, Motricity, M-PESA, MTS, Netscape, Nokia Siemens Networks, Novarra, NTT DoCoMo, O2, Orange, Safaricom, Samsung, SFR, Shazam, Sierra Wireless, Smart, Softbank, Sprint, Telefonica, Telenor, Tesco, T-Mobile, T-Systems, Verizon Wireless, Vodafone, Walmart, Yahoo

Extra Info

‡ 8 key regions includes:

North America, Latin America, Western Europe, Central & Eastern Europe, Far East & China, Indian Subcontinent, Rest of Asia Pacific and Africa & Middle East.