Mobile Operator Business Models: Challenges, Opportunities & Adaptive Strategies 2011-2016
Juniper Research Limited
June 1, 2011 98 Pages - SKU: JUN6404958
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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.
Key questions the report answers:
- How can MNOs leverage their existing assets to create new revenue opportunities?
- How will operator ARPUs and service revenues develop over the next five years?
- What strategies should MNOs adopt to optimise their existing revenue streams?
- How can MNOs address the opex and capacity issues associated with high levels of data traffic?
- What are the advantages of passive/active radio access network (RAN) sharing?
- Is flat-rate data pricing a viable option in the future?
- How can MNOs successfully monetise content services?
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- Executive Summary
- 1. The Problem Stated: A Saturated World
- 1.1 Introduction
- 1.2 A Saturated World
- Figure 1.1: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2003-2010
- Table 1.1: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2003-2010
- Table 1.2: Historical Mobile Penetration Rates Split by 8 Key Regions 2003-2010
- Table 1.3: Forecast Mobile Penetration Rates Split by 8 Key Regions 2011-2016
- Figure 1.2: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2011-2016
- Table 1.4: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2011-2016
- 1.2 MNO ARPUs are Declining
- 1.2.1Attributing Factors
- Figure 1.3: Operator-billed Monthly ARPU ($) Split by 8 Key Regions 2005-2010
- Table 1.5: Operator-billed Monthly ARPU ($) Split by 8 Key Regions 2005-2010
- 1.2.2 ARPU Base Line Analysis: Developed Markets
- Figure 1.4: Base Line Analysis of Historic ARPU, Developed Markets 2005-2010
- Table 1.6: Base Line Analysis of Historic ARPU, Developed Markets 2005-2010
- 1.2.3 ARPU Base Line Analysis: Developing/Emerging Markets
- Figure 1.5: Base Line Analysis of Historic ARPU, Developing/Emerging Markets 2005-2010
- Table 1.7: Base Line Analysis of Historic ARPU, Developing/Emerging Markets 2005-2010
- 1.2.4 Regional ARPU Forecasts
- Figure 1.6: Mobile ARPU ($) Split by 8 Key Regions 2011-2016
- Table 1.8: Mobile ARPU ($) Split by 8 Key Regions 2011-2016
- 1.3 MNO Revenues are Plateauing
- Figure 1.7: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2005-2010
- Table 1.9: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2005-2010
- Figure 1.8: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2011-2016
- Table 1.10: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2011-2016
- 2. The Problem Stated: A Data-Centric World
- 2.1 Rising Opex: Data Delivery Costs
- 2.1.1 The Rise of the Mobile Internet
- Table 2.1: Mobile Internet User Base (m) Split by 8 Key Regions 2006-2010
- 2.1.2 The Rise in Data Traffic
- Figure 2.2: Total Data Traffic per Annum from Mobile Handsets (PB) Split by 6 Data Categories 2009-2015
- Table 2.2: Total Data Traffic per Annum from Mobile Handsets (PB) Split by 6 Data Categories 2009-2015
- Figure 2.3: Total Data Traffic Per Annum (PB) Carried Via Cellular Networks Split by 8 Key Regions 2010-2015
- Table 2.3: Total Data Traffic Per Annum (PB) Carried Via Cellular Networks Split by 8 Key Regions 2010-2015
- 2.1.3 Cost Implications of the Data Surge
- Table 2.4: Scenarios for Data Delivery Costs, 2015 Relative to 2010
- Figure 2.4: Global Operator-Billed Service Revenues versus Delivery Costs of Unoptimised Data ($bn) 2010 and 2015
- 2.2 Rising Capex: Network Buildout
- 2.2.1 Spectrum Costs
- Table 2.5: German 800MHz Band Auction, May 2010
- i. Case Study: Indian Spectrum Auction
- Table 2.6: Bharti Airtel: 3G Subscribers (m) and ARPU from 3G Customers ($) Split by Scenario (Modest, Median & High) 2011-2015
- Figure 2.6: Bharti Airtel: Scenario-Based Cumulative Service Revenues ($m) from 3G Subscribers Split by Scenario (Modest, Median & High) 2011-2015
- Table 2.7: Bharti Airtel: Scenario-Based Cumulative Service Revenues ($m) from 3G Subscribers Split by Scenario (Modest, Median & High) 2011-2015
- 2.2.2 Infrastructure Costs
- 3. The Problem Stated: The Evolving Mobile Ecosystem
- 3.1 The Traditional Mobile Value Chain & Value Web
- Figure 3.1: Traditional Value Chain of Mobile Content
- Figure 3.2: Mobile Content Value Web
- Figure 3.3: App Store Value Chain
- 3.2 App Stores For All
- Figure 3.4: Global Annual App Downloads (m) Split by 3 Distribution Channels 2007-2010
- Table 3.1: Global Annual App Downloads (m) Split by 3 Distribution Channels 2007-2010
- Figure 3.5 Global Annual App Revenues ($m) Split by 3 Distribution Channels 2007-2010
- Table 3.2 Global Annual App Revenues ($m) Split by 3 Distribution Channels 2007-2010
- 3.2.1 Challenges for Network Operators
- i. The Need for Scale
- Figure 3.6: The Vicious Circle of the Addressable User Base
- ii. The Content Legacy
- Figure 3.7: The Content Legacy
- iii. Monetising Download Volumes
- iv. The Portal Revisited?
- v. Fragmentation
- 3.3 Conclusion
- 4. The Problem Stated: Regulatory Factors
- 4.1 The Green Imperative
- 4.1.1 Developing Markets
- 4.1.2 Developed Markets
- 4.2 Pricing Controls
- Figure 4.1: EU Average SMS Prices (€) Split by Retail & Wholesale Q2 2008-Q2 2010
- Table 4.1: EU Average SMS Prices (€) Split by Retail & Wholesale Q2 2008-Q2 2010
- Figure 4.2: EU Average Prices per MB of Roaming Data (€) Split Retail & Wholesale Q2 2008-Q2 2010
- Table 4.2: EU Average Prices per MB of Roaming Data (€) Split by Retail & Wholesale Q2 2008-Q2 2010
- 5. Adaptive Strategies: Optimising Existing Revenue Streams
- 5.1 Customer Segmentation
- 5.1.1 Case Study - Orange
- Table 5.1 Orange Animal Contract Tariffs, Lowest Rate in March 2011
- Figure 5.1: Orange UK Postpaid Annualised Churn Rates 2006-2010
- 5.1.2 Extending The Contract is No Longer An Option
- 5.2 After Sales Service: Enhancing Customer Relationship Management
- 5.3 Prepaid/Postpaid Migration
- 5.4 Revamping the Bundle
- 5.4.1 Bundling the Smartphone
- Figure 5.2: Orange France & T-Mobile Deutschland, Subscriber Retention Costs 2006-2010
- 5.4.2 Beyond the Smartphone: Bundling Other Devices
- Table 5.2: Selected Connected Device Retail Costs, UK MNOs, April 2011
- 5.4.3 Assessing the Data Plan
- i. To Tier or Not to Tier
- ii. Returning to Flat Rate: 3 UK
- Figure 5.3: UK Mobile Subscriber Base (mn), Split by MNO and Prepaid/Contract 2010
- Table 5.3: UK Mobile Subscriber Base (mn) Split by MNO and Prepaid/Contract 2010
- Figure 5.4: UK MNO ARPUs, Q4 2010 vs Implied All in One ASPU
- Table 5.4: UK MNO ARPUs, Q4 2010 vs Implied All in One ASPU
- iii. New Flat Rate Packages: US
- iv. The Smartphone Premium
- 5.5 Making the Most of Mobile Content
- 5.5.1 A Third Party Solution?
- 5.5.2 Addressing Fragmentation
- i. Case Study: GSMA OneAPI Initiative
- ii. Case Study: Wholesale Application Community
- iii. Will Alliances Bring Sufficient Scale?
- iv. Monetising the Mass Market
- a. Solution 1: Deploy Thin Clients
- 5.5.3 New Business Models: The Data/Content Bundle
- 6. Adaptive Strategies: New Revenue Streams
- 6.1 Opportunities in the Cloud
- 6.1.1 Introduction - The Transition to Cloud
- 6.1.2 Operator as Cloud Provider: Infrastructure as a Service
- 6.1.3 Operator as Cloud Provider: Platform as a Service
- i. Consumer Case Study: Vodafone 360
- Figure 6.1: Vodafone 360 H1 by Samsung
- ii. Case Study: Cell C MyTools
- iii. Enterprise Case Study: Verizon Wireless/Sierra Wireless
- Figure 6.2: Sierra Wireless AirVantage Solution
- 6.1.4 Underlying Business Models
- 6.2 Beyond 3G - New Revenue Streams in a 4G Environment
- 6.2.1 Intelligent Networks: Revenue Opportunities From Converged Services
- 6.2.2 Revenue Opportunities in Broadband Provision
- 6.3 Mobile Money Opportunities
- Figure 6.3: Safaricom Data Revenues (KES bn) Split by Broadband, M-PESA & SMS H1 2009-H1 2011
- Table 6.1: Safaricom Data Revenues (KES bn) Split by Broadband, M-PESA & SMS H1 2009-H1 2011
- 6.3.2 The Operator as Financial Service Enabler/Provider
- Figure 6.4: MNO Mobile Money Revenue Opportunity ($m) Split by Banking, Transfers & Remittances & NFC 2011-2015
- Table 6.2: MNO Mobile Money Revenue Opportunity ($m) Split by Banking, Transfers & Remittances & NFC 2011-2015
- 6.4 The M2M Opportunity
- 6.4.1 Defining Mobile M2M
- 6.4.2 Sizing the MNO M2M Opportunity
- Figure 6.6: Operator M2M Opportunity: Annual Connectivity & Enablement Revenues 2010-2016
- Table 6.3: Operator M2M Opportunity: Annual Connectivity & Enablement Revenues 2010-2016
- 7. Adaptive Strategies: Taking the Network Strain
- 7.1 Assessing the Scale of the Challenge - Offload Solutions
- 7.1.1 Established Offload Solutions - WiFi and Femtocells
- Figure 7.1 Data Traffic (PB/Annum) Generated by Smartphones, Featurephones & Tablets, 2010-2015
- Table 7.1 Data Traffic (PB/Annum) Generated by Smartphones, Featurephones & Tablets, 2010-2015
- 7.1.2 Emerging Offload Solutions - IMB
- Figure 7.2: IMB Schematic
- 7.2 Network Optimisation
- 7.3 Addressing Base Station Opex
- 7.3.1 Addressing Site Lease Costs - Network Sharing
- i. Active and Passive RAN sharing
- Figure 7.3: Active vs Passive RAN Sharing Infrastructure Models
- 7.3.2 Improving the Efficiencies in the Base Station
- Figure 7.4: Traditional Base Station Design
- 7.4 Reducing Opex in the RAN - the Cloud RAN Solution
- Figure 7.5: lightRadio Network Architecture
- 7.5 Flattening the Network Architecture
- 7.6 Greening the Network - Reducing Opex and Meeting Sustainability Commitments
- 7.6.1 Case Study: China Mobile
- Figure 7.6: China Mobile, Base Stations Powered by Sustainable Energy 2008-2010
- Table 7.2: China Mobile, Base Stations Powered by Sustainable Energy 2008-2010
- Table 7.3: Base Line Analysis of China Mobile Subscriber Growth vs CO2 Emissions and Energy Usage, 2007-2010
- Figure 7.7: Base Line Analysis of China Mobile Subscriber Growth vs CO2 Emissions and Energy Usage, 2007-2010
- 7.6.2 Transitioning to Green Networks: the Environmental and Financial Imperative
- Figure 7.8: CO2 Emissions (Mt) from Base Station Electricity Split by Scenario 2011-2014
- Table 7.4: CO2 Emissions (Mt) from Base Station Electricity Split by Scenario, 2011-2014
- Table 7.5: Base Station Electricity Costs ($m) Split by Scenario, 2011-2014
- Figure 7.9: Base Station Electricity Costs ($m) Split by Scenario, 2011-2014
- Appendix: Further Reading
- Table A1: Suggested Further Reading
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