Sense check: Can data growth save telco revenues?

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Some telcos are hoping that mobile data growth will resurge and transform their fortunes, though STL Partners has previously argued that data growth will not be enough. In this report we re-examine this argument looking at global trends and present the insights and lessons from six operator case-studies including DNA Finland, T-Mobile US and Reliance Jio.

Description

Format: PDF filePages: 47 pagesCharts: 25Author: Peter BoylandPublication Date: April 2017

Table of Contents

  • Executive Summary
  • Introduction
  • Background: the telco ‘hunger gap’
  • Methodology
  • Review of global trends in data growth
  • The explosion in mobile data growth
  • The link between data consumption and ARPU
  • The rise of 4G
  • Data tariff bundles increase in volume
  • Mobile data offloading
  • Multiplay bundling and the fixed network advantage
  • International data roaming
  • Zero rating and net neutrality
  • Case studies – different data strategies
  • Four data growth strategies
  • The traditional growth model
  • The disruptor/challenger model
  • The innovator model
  • The OTT proposition
  • Case studies comparison: Investment vs risk in summary
  • Case study: Innovator: DNA (Finland)
  • Case study: Disruptor/Innovator: T-Mobile US
  • Case study: Super-disruptor: Reliance Jio (India)
  • Case study: Disruptor: Free (France)
  • Case study: Traditional/Innovator: Vodafone UK
  • Case study: Traditional: Cosmote (Greece)
  • Conclusions
  • Case studies comparison: Investment vs risk in summary
  • Telcos need to seek fresh business models
  • Network investment will need to be even more intelligently targeted than with 3G/4G
  • New growth opportunities are emerging
  • A little thoughtful innovation goes a long way
  • Recommendations

Table of Figures

  • Figure 1: Trust in the increasing value of (and spend) in broadband data
  • Figure 2: Trust in the increasing value of (and spend) in broadband data
  • Figure 3: STL Partners can find no evidence of long-term revenue growth driven by increased mobile broadband demand in mature markets (outside duopolies)
  • Figure 4: The telco “hunger gap” between the decline in traditional and data revenues
  • Figure 5: Cisco global data growth 2016-2021
  • Figure 6: Total estimated UK mobile retail revenues
  • Figure 7: SMS and MMS sent in the UK, 2007-2015
  • Figure 8: Selected telco data growth strategies
  • Figure 9: Analysis of mobile operator growth strategies
  • Figure 10: DNA revenues and churn 2012-2016
  • Figure 11: DNA mobile data growth 2010-2016
  • Figure 12: DNA mobile data growth forecast
  • Figure 13: USA average monthly data use, 2010-2015
  • Figure 14: Deutsche Telekom non-voice % of ARPU, 2009-2016
  • Figure 15: T-Mobile US total revenues and non-voice ARPU, 2009-2016
  • Figure 16: Reliance Jio subscription growth
  • Figure 17: Free Mobile 4G subscriptions and 4G data, 2015-2016
  • Figure 18: Iliad Free revenue growth 2012-2016
  • Figure 19: France average mobile data use per SIM, 2009-2015
  • Figure 20: France mobile value added service revenues, 2009-2015
  • Figure 21: Vodafone UK data use and total mobile ARPU, 2011-2016
  • Figure 22: UK mobile retail ARPU, 2010-2016
  • Figure 23: UK estimated mobile retail revenues, 2010-2015
  • Figure 24: Vodafone UK total mobile revenue 2013-2016
  • Figure 25: Greece data use and total mobile revenues

Technologies and industry terms referenced include: Cosmote, Data growth, Data volume, Disruption, DNA, Free Mobile, Innovation, mobile, Operator strategy, Reliance Jio, Revenue growth, SMS, T-Mobile, text messaging, Vodafone, Voice