Many of the topics addressed in this presentation can also be found in explained in more detail at my Blog http://techneconomyblog.com/
Gave this presentation at the Telecoms World Middle East 2014, 29th September. Had a lot of fun putting this work together and got me thinking a lot about the future of networking and the challenges we (Telcos) will be facing in preparing our networks for the next thing. This is a bout the Next Thing although its in reality "hitting" us now.
Have fun and Enjoy!
In case you have any questions or comments don't hesitate to get back to me.
IAC 2024 - IA Fast Track to Search Focused AI Solutions
Digitized! Get Ready for the Next Wave of the Digital Society
1. DIGITIZED! Get ready
for the next wave of the digital society
September 29th, 2014, Dubai, UAE
Dr. Kim Kyllesbech Larsen
Group Technology
Ooredoo Group
2. “We can't solve problems using the same kind of thinking
we used when we created them.”
2 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Albert Einstein
3. +$?
The traditional mobile business model
3 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
At a Cross-road
Monetizing
Digitization -$
Voice Revenue
In decline
SMS Revenue
In decline
Data Revenue
Slow to pick up
of Voice, SMS & Data inevitably
will decline.
4. We are (almost) all Mobile
High GDP
North
Europe
APAC
America
Mobile Penetration Urban Population 2013
4 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
APAC EMEA
Latin
America
Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research and Bank of America
Merrill Lynch Global Wireless Matrix Q1, 2014. Index Mundi is the source for the Country Age structure and data for %tage of population between 15 and 64
years of age and shown as a red dotted line which swings between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line).
5. Most urban areas have
3G Mobile Broadband
3G Penetration Urban Population Urban Area 2013
High GDP
APAC
Europe
North
America
5 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
APAC EMEA
Latin
America
Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research. Index Mundi is
the source for the Country Age structure and data for %tage of population between 15 and 64 years of age and shown as a red dotted line which swings
between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line).
6. Revenue slows down, Cost grows faster
… & that’s a problem for profitability!
6 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
REVENUE GROWTH EXCEEDS
GROWTH OF OPEX
OPEX GROWTH EXCEEDS
GROWTH OF REVENUE
CAGR 2007 to 2013
High GDP
APAC
Europe North
America
APAC EMEA Latin
America
Source: Bank of America Merrill Lynch Global Wireless Matrix Q1, 2014.
7. Customer Economics
0 – 25%
25%– 80%
Beyond 80%
ARPU Decline
Customer Growth Slows
Increasing Customer Acquisition Cost
7 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Revenue stagnation
& decline
Profitability
Pressure
Attractive
urban areas
All urban &
Sub-urban
areas
Rural Areas
Note: “Crossing the Chasm” is attributed to Geoffrey Moore from his book “Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers”.
8. 2008
2013
Source: Pyramid Research. Note: Mobile User is the unique user of a mobile
service which is different from the number of SIM cards or subscriptions.
Mobile User cannot exceed 100% (number of SIMs cards or Subscriptions
can & does exceed 100%).
8 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
2009
10% of Total Revenue
Source: Pyramid Research. Note local currency.
US$50+
Billion
Loss
2013
PHP15+
Billion
Loss
Ca. 330 M US$
As Service penetration saturates
Revenue is likely to Stagnate & Reduce
9. “Missing” Link … Digitized Revenues!?
Mistakes & Mess
deadly for profitability!
Mistakes, Incompetence &
Mess don’t really matter!
Time
SERVICE REVENUES
USERS
ARPU
VOICE REVENUE DATA REVENUE
Time
9 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
SMS REVENUE
TOTAL REVENUE
?
DIGITZED REVENUES
(The 4thWave*)
* The 4th Wave is attributed to CHETAN SHARMA, MobileFutureForward.
10. SMART GRID DATA MINING
10 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
SECURITY
DEFENCE
MOBILE
CONVINIENCE
HOME Digitized!
RETAIL
Content
HEALTH
SURVAILANCE
TOURISM
PROFESIONAL
SERVICES
TRANSPORT
BIONICS
QoE
ENVIRONMENT
11. Global Digitized Economy 2020
Managed Cloud Services
Mobile
1,400+
Billion US$
(55% Data)
Mobile App
30+
Billion US$
11 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Fixed
440+
Billion US$
(60% BB)
Mobile Banking
400+
Billion US$
Public Cloud
370+
Mobile Health Billion US$
60+
Billion US$
M2M
140+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
4+ Billion US$
Sources: http://www.statista.com/ premium
account. Typically up-to 2020 has been projected
based on available data. This applies to the following
page as well.
12. Global Digitized Economy 2020
Managed Cloud Services
Mobile
1,400+
Billion US$
(55% Data)
Mobile App
30+
Billion US$
4+ Billion US$
12 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Fixed
440+
Billion US$
(60% BB)
Mobile Banking
400+
Billion US$
Public Cloud
370+
Mobile Health Billion US$
60+
Billion US$
M2M
140+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
Another
Trillion Dollar+
Economy
in the most
obvious Mobile
Digital Services
Sources: http://www.statista.com/ premium
account. Typically up-to 2020 has been projected
based on available data. This applies to the following
page as well.
13. Global Digitized Economy 2020
Mobile
1,400+
Billion US$
(55% Data)
Mobile App
30+
Billion US$
13 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Fixed
440+
Travel & Tourism
Billion US$
(60% BB)
Mobile Banking
400+
9,800+
Billion US$
Billion US$
(<10% Public Online)
Cloud
370+
Billion US$
Mobile Health
60+
Billion US$
M2M
140+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
Another
Trillion Dollar+
Economy
in the most
obvious Mobile
Digital Services Entertainment &
Media
2,500+
Billion US$
Internet of Things
7,000+
Billion US$
Residential Financial
Transaction Volume
5,000+
Billion US$
(50+% Online Penetration)
Note: 2013 had Globaly
ca. 30% Internet Users
Healthcare
11,000+
Billion MUedSici$ne
1,400+
Billion US$
15. New Opportunities? - Privacy concerns opens up for
Non-US Technology-based innovation.
BIG BROTHER EFFECT
15 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
16. “A strategic inflection point is an event that changes the way
we think and act”, Andrew Grove
16 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
17. Video content rules the internet
Global Monthly usage in Exa-Bytes (Million GB).
30+ Billion
Full Movie DVDs
4+ DVD Movies
per person per month
Full Movie DVDs
per person per month
Note: Asia, North America & Western Europe makes up for 80% of the Total
Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI.
17 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
150 Billion
20+ DVD Movies
CDN 45+% of Total
IP Traffic
60+% of Total
IP Traffic in Metro
18. Middle East & Africa towards 2020
Ca. 1 in 5 of World Population lives here!
18 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
2020 MEA Projections:
4% of Global IP Traffic
17% of Total* is Metro-based
Exa-Bytes
74% Consumer IP Video Traffic
14% of Total is CDN-based
Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI.
Source: Pyramid Research 2013 – 2017; 2018 to 2020 is authors own projection.
5+% of Pop have fixed broadband
40% still on 2G
4+% likely to have LTE
*Total always refers to the Total IP Traffic.
Fixed Broadband Penetration
20. Technologies to consider for the
Digitized Society
(MASSIVE) CONNECTIVITY NETWORKS
CONTENT DELIVERY NETWORKS
SOFTWARE DEFINABLE NETWORKS
CLOUDS & VIRTUALIZATION INCL.
NETWORK FUNCTIONS VIRTUALIZATION
BIG DATA & MACHINE LEARNING
AUTOMATION
20 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
21. Massive Connectivity – Internet of Everything
A critical enabler for the Digitized society!
Smart lenses
Body Sensors
(exterior &
interior)
Smart
“hearing” aids
Smart glasses
IA Intelligent
Assistant (*)
i-wearable
Intelligent
shoe
Body Area Network (e.g., 5G)
Ultra-small to small range network
largely powered by the body.
(You)
Smart City Network
(Environmental)
Home Network
(Personal)
21 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
iWC
Security
E.g., Connected Cars
(Object-based)
(*) AI will be
replacing the
need for
traditional
terminal
equipment.
Vehicular
to
Vehicular
Vehicular to
infrastructure
SW Updates
Small cell
Small cell
Small cell
Small cell
Small cell
Small cell
Classical Cellular Networks
(Macro-Micro-Small)
SMART DUST – MICRO-BASED WSN
Background: Imad Mahgoub et al “Smart Dust: Sensor Network Applications, Architecture, and Design” and “Jan Holler et all “From Machine-to-Machine to the
Internet-of-Things”.
23. 23 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized! ORCHESTRATION & MANAGEMENT
24. Transport Connectivity
… Terastream … The Endgame?
A critical enabler for the Digitized Society!
Intelligence & Services
Moves to Cloud & End-User Devices
100 Gbps
DWDM
Small cell
Small cell
Small cell
10
GbE
Small cell
Node
Cellular
MSAN
R1
Pure Switching
& IP Routing
Target Min 100+ Mbps at consumer edge
24 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Illustration
OLT
Wholesale
NG-CN
R2
Data Center(s)
w. Cloud, XaaS, SDN/NFV, CDN, …
Note: Croatia Telekom (Deutsche Telekom), Croatia’s largest telecommunications company, first one to deploy the new TeraStream cloud-enabled
transport & data center architecture (in partnership with Cisco). MSAN: Multi-Service Acccess Node, OLT: Optical Lite
Termination. Sources: Peter Lothberg (DTAG) https://ripe67.ripe.net/presentations/131-ripe2-2.pdf &
http://www.internetsociety.org/deploy360/blog/2014/01/videoslides-case-study-of-terastreams-ipv6-implementation-ripe67/
25. “Softwared” Network …Cloud & Virtualization
A critical enabler for the Digitized Society!
DC Localization push
Due to huge growth in video demand
QoE Driven by growth in IP Video Streaming Demand
$$$
QoE
$$$
Cisco VNI: 60+% of all IP Traffic is projected to be Metro-based and never floods the long-haul networks. Expectations are that this ration
will not change much over period to 2020. BELL LABS “METRO NETWORK TRAFFIC GROWTH: AN ARCHITECTURE IMPACT STUDY”
indicates as much as 75% by 2017 is Metro-based. SDN: Software Definable Network, NVF: Network Virtual Function, EaaS: Everything as
a Service, CDN: Content Delivery Network, v-ABC: virtualized-ABC, RAN: Radio Access Network, BBU: Base Band Unit. Gary Lee “Cloud
Networking 25 “, Dubai, 2014. September Matt Portnoy 2014 “Virtualization Dr. Kim Kyllesbech Essentials:, Larsen, Digitized!
2012.
Metro
Transport
NG Core
Metro
Access &
Aggregation
Localized
Data Centers
(optional)
Metro
Data Centers
(optional)
(Inter)National
Data Center(s)
SDN
NVF v-CDN
v-GW v-VAS
v-RAN-BBU
Private-Cloud
Public-Cloud
EaaS, vMSS, vGW,
vBSS, …
Caching, storage, …
Public-Cloud
Infrastructure-
Cloud
End-User QoE, ROI & Transport
Cost Optimization required
Increased Operational
Efficiency
Improve Cost per Byte
v-MSAN
Caching (e.g., video), local storage
$$$
$$$
26. Economics of Cloud, Virtualization & SDN
A critical enabler for the Digitized Society!
Mobile Operator*
Addressable Cost
vRAN
?
25%
Capex
A good & reliable Why Cloud (& Virtualization)
Core
IT Infrastructure
At least Greenfield
Deployment!
Opex**
vRAN
?
15%
Core, Transport
IT Infrastructure
(*) Mature market mobile operation. (**) Excluding personnel cost. Note 1: that for ISPs or other types of internet service companies
the cost structure impacted by Cloud & Virtualization likely would be a lot higher. Note 2: An excellent treatment of Cloud Economics
can be found in Harms & Yamartino’s “The Economics of the Cloud” (Microsoft 2010).
26 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Economics of Scale
Lower cost per Server
Increased Utilization
More processing per Server
Enabling Multi-tenancy
Lower cost per tenant
transport
infrastructure required
More Agile & Elastic
Service Delivery
Increased End-User QoE
Its not for Free!
Improved ROI?
Off-the-Shelf HW solutions
Lower supplier lock-in
27. Customer Experience Management
A critical enabler for the Digitized Society!
Satisfaction
Dis-satisfaction
Expectations
unfulfilled
27 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Network
Experience
Other
Behavioral
Etc..
Data
QoE
Device
Voice SMS Data
Financial
Data
CDR CSSR
Speed
Customer
Experience
Network
State
Signaling Load
Mobility
Segment
Data
Expectations
fulfilled
Response Length
#Call back
Resolution
Social Media
Twitter
Facebook
Blogs
Real-Time
Customer Value
Management
Txt Logs
Loss
Content
Dynamics
Location
Market Surveys
(online, phone, etc)
(E)mails
URL
Click
dynamics
LinkedIn
Post
Code
Demo
graphics
Bill Upload
Fraud
Risk
Telecom Perspective
(illustration)
Spend
dynamic
Activity
Loyalty
Inter
actions
Alarms
28. Big Data, Machine Learning & Automation
A critical enabler for the Digitized Society!
Visualization Layer
- Administration
- Data Analyst
- Visualization Tools
Platform Management Layer
e.g., for Hadoop Open Source
- Zookeeper
- Pig, Hive, Sqoop
- MapReduce
PaaS
Storage Layer
- NoSQL DBs (PaaS)
- Distributed File System (e.g., HDFS)
Infrastructure Layer
- Bare Metal Clustered Workstations
- Virtual Cloud Services
Security Layer
Monitoring Layer
BFaaS
Analytics Engines
- Statistic tools
- Text analytics
- Search engine
- RT Machine learning
Data Warehouse(s)
- Analytic Appliances
Ingestion Layer
Data Sources
Unstructured Data Relational DBs
Video Images Sensors
Need to process
Unstructured data streams
Source: N. Sawant & H. Shah “Big Data Application Architecture”, 2013, Byron Ellis “Real-Time Analytics”, 2014. Note: Hadoop is not
the most optimal solution for large-scale real-time analytics or analysis including iterative machine-learning algorithms. BFaaS:
Business Function as a Service, DaaS: Data as a Service, PaaS: Platform as a Service, IaaS: Infrastructure as a Service.
28 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Near-RT & real-RT Analysis of
massive data amounts
Storage & Retrieval across a
diverse ecosystems
Monetizing Data
IaaS
IaaS
PaaS
DaaS
IaaS
IaaS
29. Big Data …
a business opportunity?
Source: Worldwide; Wikibon; 2013 Wikibon (2013 & 2017), 2020 data based on authors
own assessment.
29 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
RISKS
PRIVACY ISSUES
LACK OF SKILLS
INFLATED
EXPECTATIONS
Note this does not
reflect the value of
applying data mining.
30. Customers don’t like to
pay for digital services!
(particular if perceived
free in the physical
world)
Privacy requirements will prevent full data
monetization .. What Was & Is, Will Not Remain!
Global Content Players with well established &
trusted billing platforms will become
tough competitors to established MNOs
Crowded & Fragmented
market place
for digital services!
30 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
Failure to
monetize
The Digital
Society
31. Digitization challenges for
Emerging Markets
Backhaul, Backbone & International – Availability & Quality
Different use cases/scale than mature markets.
Relative slow cellular broadband uptake.
Kiosk-based cloud access, SME & Gov. focus
Relative long re-investment cycles (e.g., write-off periods).
Public Funding, World Bank, etc
Long ROI timelines for mass digitization.
Initial focus: Private Cloud, eGov, SME, etc…
Critical mass of ICT skills.
31 Dubai, September 2014 Dr. Kim Kyllesbech Larsen, Digitized!
32. THANK YOU!
Dr. Kim Kyllesbech Larsen
Follow Dr. Kim on Twitter @KimKLarsen
Blog: www.TechNEconomyBlog.com
Presentations: http://www.slideshare.net/KimKyllesbechLarsen
Acknowledgement: I am indebted to my wife Eva Varadi for her great
support, patience and understanding during the creation of this
presentation. Further, I would also like to thank Chetan Sharma (Future
Mobile Forward) for his incredible inspirational papers on “The 4th Wave”.
Hinweis der Redaktion
Concerns about US Intelligence Services Data Mining (and “Spying”) on all internet traffic is creating a push for a segmented internet with more control and independence from US “controlled” internet. We will see non-US Entrepreneurs developing new (and copying existing, e.g., China!) content and internet services that does not (or at leased minimize) US control and exposure. The will be substantial money in Europe for this development.
With Big Data is ALWAYS understood to data situations that match one or more of the 3 V’s = VOLUME, VARIETY & VELOCITY. It should be noted that Big Data term should only be used for situations where conventional data acquisition and analysis architectures cannot effectively solve business critical problems. Typical mobile industry data problems might actually not fall into this category as their data are dominated by well structured & semi-structured transactional data that can be well handled by classical systems.
Virtualization was first investigated by IBM back in the 60’s (i.e., its not a new concept). The formal description of virtualization was provided by Popek & Goldberg in 1974 in their seminal paper “Formal Requirements for Virtualizable Third Generation Architectures”, Communications of the ACM, Vol. 17, Number 7, July 1974. Also Cloud concepts goes all the way back to the 50’s. However, maybe contrary to some beliefs as virtualization became increasingly feasible in modern computing infrastructures so did the Cloud. In other words virtualization is an important trigger point for Cloud Computing.
While the Capex potential of RAN virtualization (vRAN) should be fairly obvious the Opex savings might be more problematic (apart from possible Maintenance). A site needs less real estate as the non-RF electronics (BBU) & controllers moves away from the site. However, whether site related savings can be realized might depend on the site specific contractual details.
Mobile / Fixed Telco view!
Blue & Green bubbles is pretty basic BI carried out today in various forms of sophistication. Not always correlated between the various areas.
Orange bubbles are analyzed as well but less frequently correlated with other data and more limited to special areas (i.e., engineering, marketing, etc..)
Red bubbles rarely figures on operators analysis, i..e, basically this is all the (so-called) unstructured data stuff that is difficult (or not possible) to tackle with existing classical CRM and data warehouses.
It should be noted that while the unstructured stuff might be important the load from such events are a lot less than the transactional data coming from the mobile users interactions unless the mobile operators start tracking the same data as google, FB etc..
MIGHT BE TOO TECHNICAL (possible skip) … In all effect when we talk about Big Data scenarios and architectures/systems we really mean systems that can handle BIG DATA PROBLEMS in terms of Volume, Variety & Velocity of data that CANNOT be well (computationally efficient and/or economically efficient) handled by a classical systems/data-warehouses (optimized for acquiring, analyzing and storing structured data) with near-RT requirements. Note Hadoop can also improve the modernization of classical data warehouses by bridging Big Data with classical data acquisition, analysis and store.