Maximizing Data Profitability

1,288 views

Published on

Presentation at Next Generation Telecoms Summit, September 2009, Portugal.

Published in: Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,288
On SlideShare
0
From Embeds
0
Number of Embeds
66
Actions
Shares
0
Downloads
72
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Konzernentwicklung
  • Maximizing Data Profitability

    1. 1. Next Generation Telecoms Summit - Portugal 30. September 2009 Kim Kyllesbech Larsen (T-Mobile). T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    2. 2. Some discussion points …. Mobile broadband data is profitable (or can be made so). (data) Profitability can be optimized (but how?). Cost distribution & allocation is an important remedy for broadband data profitability assessment (though in the end total cost is what matters). Technology is important for data profitability with focus on cost & performance (e.g., network sharing & traffic management). In the end what really matters is overall profitability. T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    3. 3. Top internet applications going mobile – the demand for mobile broadband. E-mail / browse Play on-line Share photo Download music Stream music Social networks Video shows Watch movie Up-to 11 hours per week ca. 5 min per day (Free 100MB/month) 35+ min per day, 800+ mio photo & 8+ mio video uploads per month, 30+ mio mobile users 3.3 mio iPhone users ↑ (July 2008) 64 - 128 kbps stream 30+ mio accounts & 2.8+ bn songs ↑ 7 mio Hulu users (Apr’09), 325 min / viewer and an average Hulu video 10+ min 10 mio users & 700k instant watch (Jan’09) 100+ bn emails/day, 40+% > 5 MByte ↑ T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    4. 4. Mobile profitability – Western Europe. <ul><li>Voice ARPU expected to decline with 5% pa over the next 5 years 1 . </li></ul><ul><li>Data ARPU expected to increase with 4% pa same period 1 . </li></ul><ul><li>Data ARPU is a factor of 3 lower than Voice ARPU. </li></ul><ul><li>Data growth is not likely to compensate the decline in Voice revenue. </li></ul><ul><li>Most Western European markets have reached customer saturation with little organic growth and with revenue decline. </li></ul><ul><li>Decreasing prices and shrinking margins are putting substantial pressure on cost reduction innitiatives. </li></ul><ul><li>Nevertheless, WEU EBITDA margin is anticipated to increase slightly over the next 5 years 1 </li></ul>1 Pyramid Research Western Europe June 2009. T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    5. 5. Western European profitability expectations. Commentary <ul><li>Service revenue is projected to decline in most of WEU. </li></ul><ul><li>Opex measures are anticipated to provide margin growth compensating the revenue decline. </li></ul><ul><li>HSPA+ / LTE will be deployed over the same period providing high-quality (i.e., high speed) mobile broadband to the WEU mobile subscribers. </li></ul><ul><ul><li>Though, operators will be running 3 technologies in parallel hence likely Opex (and Capex) increase. </li></ul></ul>EBITDA versus Opex CAGR 2008 - 2012 Source: Merrill Lynch European Telecoms Matrix Q3 2009. EBITDA CAGR Opex CAGR Cost efficiency compensates revenue decline Green diamond: revenue increase Red diamond: revenue decrease T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    6. 6. Western Europe mobile environment is a study in cost optimization, while exploring new growth opportunities with mobile broadband data. Financials WEU market dynamics Revenue Opex Ebitda GROWTH (APAC / CEE) OPTIMIZATION (WEU) Years Customer subscriptions ARPU Years -2.0% pa +2.4% pa Steady-state like (WEU) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. -2.0% pa
    7. 7. The service revenue distribution is expected to undergo significant differences with mobile broadband deployment. 2008 (HSPA) 2012 (HSPA+/LTE) 2020+ (LTE) Revenue 1,2 1 Pyramid Research Western Europe June 2009, 2 Country by Country extrapolated and aggregated from Pyramid data. Mobile broadband data revenue will become increasingly important component of the total revenue. T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. 100% Data Voice & SMS 80% Data 20% Voice & SMS 90% Data 10% Data 35% > Voice & SMS 65% <
    8. 8. Mobile broadband traffic is expected to grow explosively over the next 10 years. Today 2020+ Throughput 1  100+ (CAGR 50% pa) Volume 1  300+ (CAGR 70% pa) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. > > Can technology cost be controlled under such conditions?
    9. 9. The structure of profitability. Total Revenue Technology cost (ca. 15% – 20% of Opex) Usage cost − Market invest − = EBITDA Personnel Other cost − − − Network depreciation (ca. 10% to 20%) − = Contribution Margin (after depreciation) Spectrum amortization − = EBIT Total Opex WEU between 22% and 44% with an average of 35% 2 Data revenue share 1 15% and 35% incl. msg. 1 Pyramid Research Western Europe June 2009, 2 Merrill Lynch European Telecoms Matrix Q3 2009. T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. Conceptual view
    10. 10. Average WEU mobile operator anno 2009 1 . 1 As can be estimated from Merrill-Lynch WE Telecom Matrix, business modeling, financial analysis, 2 Excluding SMS Total Revenue % of total Revenue ca.10%+ Usage cost Market invest Personnel cost Technology cost Other cost (Illustration) <ul><li>Depreciation would take another 10% to 20% off the EBITDA. </li></ul><ul><li>Amortization depends largely on individual spectrum acquisition cost and varies between countries and individual operators. </li></ul>Data revenue 2 T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. EBITDA + 35% 10% – 15% 15% - 20% 10% - 15% 10% - 15% <15%
    11. 11. Cost efficiency and its impact on margin – a 35% cost saving translate to a 5% margin improvement. <ul><li>Take an WEU mobile Operator with an EBITDA margin of 35%. </li></ul><ul><li>Technology cost contribution of 20%. </li></ul><ul><li>Operator reduces its Technology cost base with 35%. </li></ul><ul><li>Examples of cost reduction initiatives </li></ul><ul><ul><li>Network sharing. </li></ul></ul><ul><ul><li>Access technology consolidation. </li></ul></ul><ul><ul><li>Cost distribution changes (i.e., Opex to Capex shifts for EBITDA improvement). </li></ul></ul><ul><ul><li>Outsourcing / managed services. </li></ul></ul><ul><li>With everything else being equal an operator could gain a margin improvement 1 of ca. 5% saving 35% on its cost base. </li></ul>1 m new = 1- ( 1 -  o i )  (1 – m old ), with m new and m old being the new and old margins,  the cost reduction of cost component o i (which is taken relative to the total cost base). T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    12. 12. Volumetric based costing (€ per Byte) is often evoked to safe-guard profitability. While the concept is straightforward to use, it is also flawed due to wrong assumption that data traffic is voice-like. It is compelling to use volumetric-based costing and pricing rationale – though it might be wrong Minimum Cost per Byte Volumetric network capacity Maximum Cost per Byte Volumetric customer demand Profitability can be “safely assumed” if the “Price per Byte” is chosen somewhere in-between Vastly different data-traffic profiles (and resulting cost) can result in the same volumetric demand. Conceptual view T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    13. 13. Main cost and investment driver for network capacity is busy hour traffic throughput – managing broadband traffic and quality of service levels will be essential to managing technology cost. Same volumetric demand can cause vastly different network cost and invest levels. TRAFFIC PROFILE 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day Throughput 9 HOURS 4 HOURS 1 2 Traffic profile 2 same volume as 1 but 40% higher busy hour throughput To keep same user experience in busy hour more network capacity needed Higher invest level and network OPEX required Conceptual view T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    14. 14. Illustration of service BH throughput contribution. Every data service has a different network impact and in principle a different cost impact. Mobile TV high BW impact but relative little volume in this illustration. 60% 50% 40% 20% 8% 7% 3% 2% 2% 1% 1% 0.5% 0.5% 0.5% 0.4% 0.2% 0.2% 100% Mobile TV Premium Service Mobile TV Basic Service Bus. Full Connectivity Full Connectivity Bus. At Home Surfing Music download Bus. Email Pull Peer 2 Peer MIM Confined Connectivity Bus. Confined Connectivity Bus. Email Push Machine 2 Machine Real Ring-tones Email Pull MMS outgoing MMS incoming BH Throughput in Mbps Volume in MB Home surfing (wireless DSL) Conceptual view T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. Home Surfing (wireless DSL)
    15. 15. Most of today’s mobile broadband offerings have no speed (i.e., quality) versus price structure. “Fair use” policy address volumetric use and curbs speed after a volumetric limit has been reached. Today’s mobile broadband customer gets the maximum possible service irrespective of price paid. Bandwidth Time Spectrum limit Installed base limit Un-controlled demand All customers having same experience irrespective of price they pay Today’s situation – no QoS. <ul><li>Poor quality for all customers </li></ul><ul><li>Uncontrollable Opex and Capex demand </li></ul><ul><li>Service (price) differentiated quality </li></ul><ul><li>Better control of network Opex & Capex </li></ul>T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. High network expansion pressure High cost & cash impact Time Bandwidth “ Unlimited” Gold Silver Bronze (best effort) Conceptual view QoS implemented. Normal network expansion Normal cost & cash impact 5% of base 20% of BW 15% of base 40% of BW 30% of base 25% of BW 50% of base up-to 20% of BW
    16. 16. RAN is the dominant technology cost element. 60% (10% - 12%) Radio Core Network 15% IT & Platforms 25% Services, 10% Maintenance & Repair Other Costs 15% Rental & Leasing 40% Leased Lines 20% Personnel Costs 15% (Illustration) driver: (Sites) driver: (Sites, traffic) driver: (Sites, nodes) driver: (Sites, nodes) driver: (Sites, nodes, traffic) driver: (customers, traffic) driver: (customers) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    17. 17. The cost distribution challenge is how to distribute the various cost elements across voice and data services – finding the key(s) (1 of 2) RAN 60% Core 15% IT 25% Technology Cost RAN Cost (2G & 3G sites as key) Ex. 10k locations, 6k 3G Nodes with 80% co-location ratio. IT Cost (2G & 3G customers as key) Core Cost (2G & 3G customers as key) (Illustration) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    18. 18. The cost distribution challenge is how to distribute the various cost elements across voice and data services – finding the key(s) (2 of 2) Voice – Data cost distribution keys <ul><li>RAN Cost distribution keys </li></ul><ul><ul><li>Site-related cost split according with data & voice subscribers. </li></ul></ul><ul><ul><li>Transmission & Energy split according with the bandwidth demand respective for data and voice. </li></ul></ul><ul><li>Core Network distribution key(s) </li></ul><ul><ul><li>Cost split according with data & voice subscribers. </li></ul></ul><ul><ul><li>A possibility to split transmission cost according with data bandwidth demand. </li></ul></ul><ul><li>IT distribution key(s) </li></ul><ul><ul><li>Cost split according with data & voice subscribers. </li></ul></ul>Technology cost split in access technology UMTS Cost (32%) GSM Cost (68%) (Illustration) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    19. 19. The technology cost distribution keys. <ul><li>GSM & UMTS sites. </li></ul><ul><li>Data & Voice customer base. </li></ul><ul><li>Possible to weight capacity sites on data cost. </li></ul><ul><li>GSM & UMTS sites. </li></ul><ul><li>Data & Voice customer base. </li></ul><ul><li>GSM & UMTS sites. </li></ul><ul><li>Bandwidth demand. </li></ul><ul><li>GSM & UMTS sites. </li></ul><ul><li>Data & Voice customer base. </li></ul><ul><li>Alternative 50:50 between data & voice. </li></ul><ul><li>GSM & UMTS sites. </li></ul><ul><li>Data & Voice customer base. </li></ul><ul><li>Bandwidth demand. </li></ul>(Illustration) T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    20. 20. Data profitability – the lower the data revenue share of the total revenue the higher is the likelihood for poor data profitability. Data Revenue ca. 20% of Total Revenue ca. 0% 15% 50% 30% 35% 20% EBITDA Usage cost of data Market invest related to data Personnel cost related to data Technology data cost Other cost related to data % of total Opex category (Illustration) <ul><li>Considering depreciation and spectrum amortization would only make the profitability more negative. </li></ul>T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    21. 21. Data profitability – once data revenue reaches a critical “mass” of the total revenue (in general) mobile broadband data will become profitable. Data Revenue ca. 30% of Total Revenue EBITDA + 28% 20% 50% 30% 35% 30% % of total Opex category Usage cost of data Market invest related to data Personnel cost related to data Technology data cost Other cost related to data (Illustration) <ul><li>Depreciation would take another 10% to 20% off the EBITDA. </li></ul><ul><li>Depending on spectrum acquisition cost, spectrum amortization might make profitability problematic </li></ul>T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    22. 22. The mobile data evolution towards introduction of true broadband data access and services. Multimedia cellular Enhanced mobile services Enhanced mobile multimedia Mobile broadband communication Optimised mobile multimedia Year DL Throughput 2G / GSM GPRS / EDGE / EDGE 2. 3G / UMTS Introduction of WCDMA / FDD. 3G / HSDPA Downlink enhanced WCDMA/FDD HSPA / HSPA + Downlink / Uplink enhanced with overall HSPA improvements. Mobile broadband (LTE / NGMN) Broadband radio, IP based wideband Peer to Peer. Near-future wireless cellular. 1 Ultimate performance will depend on available spectrum bandwidth and link-budget. 2000 - 2003 2003 - 2004 2005 - 2006 2007 - 2012 2010+ 32 - 128kbps 64 – 384kbps 0.384 - 4 Mbps 1 0.384 – 14.4+ Mbps 1 30+ (AVG) to 200+ (PEAK) Mbps 1 Mobile broadband Based on “NGMN” paper by J. Horn T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. Conceptual view GSM (GPRS / EDGE) 3G - UMTS Enhanced UMTS Optimised UMTS
    23. 23. Ideal view – the ultimate data profitability – full network sharing scenario with 1 access technology (all voice considered data). Total Revenue = Data Revenue EBITDA 40% to 55% < 7% 15% - 20% 6% - 10% 8% - 12% < 10% % of total Revenue Usage cost Market invest Personnel cost Technology cost Other cost T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. (Illustration) EBITDA + 35% 10% – 15% 15% - 20% 10% - 15% 10% - 15% <15% The average WEU Mobile Telco anno 2009.
    24. 24. Substantial savings from combining existing 2G, 3G and next-generation networks and jointly extending network coverage. Network sharing and in particular RAN sharing can provides substantial technology cost savings Shared backhaul Fewer sites BSC : Base station controller (2G) BTS : Base transceiver station (2G) RNC : Radio network controller (3G) nodeB BTS RNC BSC Network sharing target Fewer stations Core 2 T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner. Shared backbone IT 1 Core 1 IT 2
    25. 25. Network sharing is an important remedy in optimizing cost and cash and thereby improve over all profitability. Network sharing is in particular attractive in the initial deployment and modernization phase. Initial deployment Steady State Wear-out / Modernization <ul><li>Capex prevention. </li></ul><ul><li>Opex prevention. </li></ul><ul><li>Cash optimized startup. </li></ul><ul><li>Best network. </li></ul><ul><li>Little Capex benefits. </li></ul><ul><li>Opex savings. </li></ul><ul><li>Significant write-off. </li></ul><ul><li>Re-structuring cost. </li></ul><ul><li>Better network. </li></ul><ul><li>Capex savings. </li></ul><ul><li>Opex savings. </li></ul><ul><li>Opex prevention. </li></ul><ul><li>Minor write-off. </li></ul><ul><li>Re-structuring cost. </li></ul><ul><li>Better network. </li></ul>UMTS LTE GSM / UMTS WiMax T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    26. 26. Network sharing expectations and the BIG picture. Commentary <ul><li>Network sharing is an important remedy for cost and cash optimization. </li></ul><ul><li>Network sharing can be costly to implement. </li></ul><ul><ul><li>Termination & restructuring cost. </li></ul></ul><ul><ul><li>Write-off exposure. </li></ul></ul><ul><ul><li>Organizational complexities. </li></ul></ul><ul><ul><li>Network strategic lock-in – radio network no longer differentiator. </li></ul></ul><ul><ul><li>Long-term engagement and complex exit scenarios. </li></ul></ul><ul><li>More aggressive network sharing scenarios are likely to materialize in order to further bring Technology cost down. </li></ul>RAN sharing cost benefits (Illustration) 35% Opex saving on RAN network sharing ca. 20% Opex saving on overall Tech Opex < 4% On Total Corporate Opex T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    27. 27. Summary <ul><li>Mobile broadband data is profitable (from an EBITDA perspective at least). </li></ul><ul><li>The on-set of broadband data profitability depends on data revenue reaching a critical level of the total turnover. </li></ul><ul><li>The degree of mobile broadband profitability depends on the cost distribution and cost allocation strategies. </li></ul><ul><li>Technology is one of the most important factors in optimizing (data) profitability. </li></ul><ul><li>Network sharing, traffic management and outsourcing/managed services are important remedies in cost, cash and hence (data) profitability optimization. </li></ul>T-Mobile Confidential and Proprietary All rights reserved. No part of this report may be reproduced in any material form without the written permission of the copyright owner.
    28. 28. Thank you for your attention. Contact details : [email_address] M +31 6 2409 5202 L http://www.linkedin.com/in/kimklarsen

    ×