Telecom is closer to FMCG (Fast Moving Consumer Goods) Newer methods of measuring performance are needed E.g. retail surveys to measure toothpaste market share; focus groups, customer surveys for satisfaction, etc. Yet telecom sector still relies on supplier provided data that is outdated by the time it’s reported Different approach is needed: demand side surveys Only way to make nuanced polices; nuanced business decisions But costly: so research organizations like us can’t do it always. Regulators/NSOs need to get involved

1. Measuring sector performance: Instruments and impact
Ayesha Zainudeen, Senior Research Manager
Helani Galpaya, COO
DIRSI@5, 20 November 2010
Lima
This work was carried out with the aid of a grant from the International Development Research Centre, Canada and UKaid from the Department for International Development, UK.

2. Measuring sector performance to gauge how
successful sector reforms have been
• Good sector performance means
– Connectivity (access)
– Choice
– Quality (of services)
– Prices (affordability)

3. Measuring sector outputs
Some of LIRNEasia’s tools and impacts

4. Connectivity: Usual suspects are flawed and/or
absent
• Connectivity (# of fixed/mobile/Internet subscriptions; # of
subscriptions/100; etc)
– Don’t account for multiple SIM ownership
– Don’t account for non-owning phone and Internet users (device
sharing)
– Can’t tell us who these users are (rich/poor; urban/rural;
male/female…); etc
– Can’t tell us which are actually fixed and which are actually mobile (LK
“fixed” wireless)

5. Quality: Usual suspects are flawed and/or
absent
• Only traditional measures: waiting lists; call success
rates; call drops; upload/download speeds, etc.
• Few regulator publish internet quality data, and if
they do, it’s using invasive cumbersome methods
that produce outdated data
• LIRNEasia measures QoSE, from user’s perspects
• Trade-offs across differing approaches

6. Price: Flawed methods (previously used) are
being correct with the use of baskets
• Prices (cost of a 3 minute call; cost of 1MB data, etc)
– Don’t reflect different usage levels
– Don’t distinguish between pre/postpaid
– Don’t account for sunk costs (handset, connection,
installation charges, etc), taxes and deals (buckets, etc)
– Different definitions of broadband (256kbps; 1Mbps; etc)
– Can’t tell us about affordability

7. What LIRNEasia uses to measure SP
and how we make use of the results

8. Connectivity

9. Demand side surveys are very useful for overall
numbers as well as nuances of use
• How many own? How many use?
• Teleuse@BOP3 (2008) 10,000+ survey of BOP (SEC D & E; 15-
60 yrs) telecom users in 6 countries
– Representative of BOP (15-60)
95 90
59 52
76 74
41 37 34 32
50
69
1 2 1 3
16 18
0 3 1 4 1
12
Bangladesh Pakistan India Sri Lanka Philippines Thailand
ICT use and ownership (% of BOP)
Use a mobile Own a mobile Use the Internet Own a computer
*
*
Among BOP
* Excludes CDMA fixed wireless phones in Sri Lanka

10. 10
Among BOP mobile owners
• How many own more than one active SIMs?
Bangladesh Pakistan India Sri Lanka Philippines Thailand
2008 2006 2008 2006 2008 2006 2008 2006 2008 2006 2008
More than 1 SIM 10% 12% 23% 5% 9% 9% 16% 9% 19% 1% 13%

11. • Urban-rural divide?
Urban Rural
BOP teleusers

12. • Gender divide?
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Male Female Male Female Male Female Male Female Male Female Male Female
Bangladesh Pakistan India Sri Lanka Philippines Thailand
Most frequently used phone (% of BOP teleusers)
Public acces phone
Friend/relative/workplace phone
Neighbor's phone
Other household member's phone
Household fixed phone
My own mobile
Among BOP teleusers
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Male Female Male Female Male Female Male Female Male Female Male Female
Bangladesh Pakistan India Sri Lanka Philippines Thailand
Most frequently used phone (% of BOP teleusers)
Public acces phone
Friend/relative/workplace phone
Neighbor's phone
Other household member's phone
Household fixed phone
My own mobile
1.6 : 1 3.5 : 1 2.0 : 1 1.8 : 1 1 : 11 : 1
Ratio of male to female
use of ‘my own mobile’

13. 43% 41% 36%
74%
70%
57%
56% 57% 63%
23%
10%
20%
Bangladesh Pakistan India SriLanka Philippines Thailand
Internet use (% of BOP teleusers)
I haven't heard about the Internet
I have heard about the Internet but I haven't used it
Less thanonce a month
Once a month
2-3 times a month
Once a week
2-3 times per week
Daily
Among BOP teleusers
• Do people even know about these ICTs?

14. Data successfully used to combat of regressive
element of proposed mobile tax in Sri Lanka (2007)
• Proposed tax
– 7.5% mobile subscriber levy (increase from 2.5%) + LKR50 flat rate
• Data used to show poor are dependent on mobiles, with low
monthly expenditure
• Regressive
effect illustrated
to policymakers,
media, etc
Result: Flat rate
eliminated; MSL
increased to 10%

15. • What do the poor do with their mobiles? Among BOP mobile owners

16. More recent application of demand-side data
to accurately estimate Internet "users"
• ITU-reported numbers
– Estimated Internet users = Total Internet subscriptions * X
– What is X? How is it determined?
• Afghanistan: 500
• Burundi: 13
• New methodology
– Use existing demand-side data to calculate X for subset of
countries; , according to GNI

17. Result: individual country multipliers (X)
determined objectively
• Maybe not perfect, but better than arbitrary Xs
Source: Samarajiva & Lucas, 2010

18. Choice

19. Not easy to measure, but demand-side data
can help
0
20
40
60
80
social status
fashion
value added services
privacy
mobility
easy to use
easy to access
can use at any time
save on travel time and cost
clear connection
no other choice
To control costs
economical to receive calls
economical to make calls
Fixed
Mobile
Public access
Base:
Fixed: 15800
Mobile: 616
Public access: 2106
Source: Teleuse@BOP1 (2005)
Primary reason for using fixed/mobile/public phone (% of users surveyed)

20. Quality

21. LIRNEasia uses broadband quality of service
experience (QoSE) benchmarks
• Measures 5 parameters (Upload, download, RTT, Jitter, packet loss)
– In relation to 3 servers (ISP, National, International)
• Tests conducted
– For mobile and fixed broadband (wireless coming soon)
– At different times of the day (0800, 1100, 1500, 1800, 2000, 2300)
– On weekdays and weekends
– From multiple locations (even in buses)
– By users (software downloadable; background app; data automatically
uploaded to publicly accessible website)
• Tests for long intervals to minimize effects of short term variations (e.g.
100 pings, 100 sec download)
• Variations studied and outliers removed

22. Value for money compared (kbps/USD)
October 2010 Fixed broadband QoSE benchmarks

23. Delivered vs stated speeds
October 2010 Fixed broadband QoSE benchmarks

24. Allows to derive other important measures: Advertised vs
delivered speeds; value for money (kbps/USD), etc
• Publication of benchmarks contributed towards
ethical advertising of BB packages in Sri Lanka (2009)
– Dialog Broadband changed advertised speeds from 7.2
Mbps  1 Mbps
– Mobitel, stopped advertising speeds of 14.4 Mbps 3.6
Mbps

25. Pressure for ethical advertising

26. Similar approaches being adopted by
regulators
• FCC promoting BB QoS monitoring via “crowd
sourcing”
• TRAI (India) and BTRC (Bangladesh) both partially
adopted LIRNEasia recommendations on monitoring
and publication of QoSE information

27. Prices

28. Broadband benchmarking: South Asia Broadband
Conference, Sep ‘07. Research picked up by AFP

29. AFP story picked up in multiple media
outlets, including some in PK
“...according to
Colombo-based
LIRNEasia, a regional
telecom think-tank”
AFP Dawn
“...according to
Colombo-based
LIRNEasia, a regional
telecom think-tank”
AFP Dawn
“ PAKISTANIS PAY MOST IN
SOUTH ASIA TO ACCESS
IINTERNET”
“ PAKISTANIS PAY MOST IN
SOUTH ASIA TO ACCESS
IINTERNET”

30. Gets regulator’s attention AND response
..and so on. Multiple
emails/conversations back and forth
about methodology, prices
..and so on. Multiple
emails/conversations back and forth
about methodology, prices

31. 6 months later…
Price Drop: 64%Price Drop: 64%

32. Benchmarking used to monitor price levels for
voice and data
• Mobile baskets (based on adapted OECD
methodology)
– Least cost frontier
• Broadband (retail and wholesale [though less
regularly due to resource intensiveness])
• Also collected: international voice; international
roaming

33. Adapted OECD mobile baskets used to guage
price/affordability levels
• Average voice minutes used per month (including voice
mail, free minutes given)
• SMS & MMS per month
• Connection and rental charges
• All above separated by
– On-net vs. off-net
– Peak vs. off-peak
• Calculated for low, medium and high users
• Prepaid/postpaid
• USD (price) & PPP (affordability)
• LIRNEasia since 2006; ITU since 2009

34. Calculated for low, medium and high users;
pre/postpaid seperately
SAARC countries medium user prepaid mobile price basket (USD)
October 2010
5.77
4.58
4.08
4.98
6.80
7.69
10.39
17.19
0
2
4
6
8
10
12
14
16
18
20
Afghanistan Nepal Bangladesh Pakistan India Bhutan Sri Lanka Maldives
USD
SMS
Usage
Rental
Connection
February 2010
ITU has also started reporting baskets since 2009 in place
of price of a 3 minute call

35. • Minimum level of expenditure (calculated using
basket approach) at all usage levels
0
50
100
150
200
0
80
160
240
320
400
480
560
640
720
780
860
920
1000
1080
1160
1240
1320
1400
1480
1560
1640
1720
1800
1880
1960
T-mobile ATT/Verizon/SprintNextel
Another approach based on baskets: Lowest
Cost Frontier (Bauer & Kim of Michigan State)
Assumes no switching costs and consumer has full informationAssumes no switching costs and consumer has full information
Comparisons between
Packages
Operators
Countries
Comparisons between
Packages
Operators
Countries

36. In sum

37. Telecom is closer to FMCG (Fast Moving
Consumer Goods)
• High competition; increasing commoditization
• Newer methods of measuring performance are needed
– E.g. retail surveys to measure toothpaste market share; focus
groups, customer surveys for satisfaction, etc.
– Yet telecom sector still relies on supplier provided data that is
outdated by the time it’s reported
– Different approach is needed: demand side surveys
– Only way to make nuanced polices; nuanced business decisions
– But costly: so research organizations like us can’t do it always.
Regulators/NSOs need to get involved

38. http://lirneasia.net/projects/2010-12-idrc-main-
project/indicators-continued/
ayesha@lirneasia.net
helani@lirneasia.net