Analysing ICT indicators, based on benchmarking provides a far more valid evidence-base for ICT policy and regulation than using the ranking of a country on one of the global ICT indices. Both ap- proaches use the same data but differ in how the data is analysed. The benchmarking approach is a starting point for further analysis, showing clearly the linkages between individual indicators. Global ICT indices, as they are currently formulated, disguise these linkages by providing a composite measure, and often only display normalised indicators that cannot be verified by the user. This encourages the perception that the index is the end result of the analysis, rather than the beginning.
2. A GOOD INDEX
• Most of us have used indices and many of us
have constructed some
• Good indices include:
• World Bank Ease of Doing Business Index
• Consumer Price Indices
• OECD price baskets
• Stock market indices
• Changes in the value or ranking of ICT sector
indices should help to identify best practice
and potential bottlenecks to improved ICT
sector performance
3. COMMON PROBLEMS
• Summing up indicators that explain the
same factor (muti-colinearity)
• Summing up indicators that are all highly
correlated to GDP per capita
• Measuring affordability as prices expressed
as % of GDP per capita, masking
information included in prices
• Using first world indicators such as fixed-
line penetration and wired broadband
5. COMPARING RANKINGS AGAINST
SELECTED ICT INDICATORS
Ranking ICT Indicators
ADI
(A4AI)
3i
(EIU)
IDI
(ITU)
NRI
(WEF)
MCI
(GSMA)
1 GB
prepaid
data in USD
Active
SIM cards
per 100
Fixed-line
per 100
Nigeria 13 45 137 119 98 3.20 83 0.10
Kenya 30 51 129 86 105 5.00 82 0.19
Ghana 26 49 112 102 96 2.46 128 1.01
Namibia 31 NA 120 99 NA 5.89 99 7.42
Brazil 10 18 63 72 56 8.48 124 21.01
Sources
A4AI
2017
EIU
2017
ITU
2016
WEF
2016
GSMA
2016
RIS / RIA
Q4 2016
ITU
2016
ITU
2016
Brazil scores best in this comparison, but has the highest mobile
broadband prices and the only 2nd highest mobile penetration
6. COMPARING RANKINGS AGAINST
SELECTED ICT INDICATORS
Ranking ICT Indicators
ADI
(A4AI)
3i
(EIU)
IDI
(ITU)
NRI
(WEF)
MCI
(GSMA)
1 GB
prepaid
data in USD
Active
SIM cards
per 100
Fixed-
line
per 100
Nigeria 13 45 137 119 98 3.20 83 0.10
Kenya 30 51 129 86 105 5.00 82 0.19
Ghana 26 49 112 102 96 2.46 128 1.01
Namibia 31 NA 120 99 NA 5.89 99 7.42
Brazil 10 18 63 72 56 8.48 124 21.01
Sources
A4AI
2017
EIU
2017
ITU
2016
WEF
2016
GSMA
2016
RIS / RIA
Q4 2016
ITU
2016
ITU
2016
Nigeria scores better the Ghana but Ghana is cheaper and has
higher penetration of SIM cards and fixed-lines
8. VARIATION IN THE EIU 3I (2017) EXPLAINED BY
GDP PER CAPITA CURRENT PRICES FOR 2016
GDPperCapitainUSD(currentprices)
0
15,000
30,000
45,000
60,000
0 25 50 75 100
R² = 0.8479
9. VARIATION IN THE GSMA MOBILE CONNECTIVITY
INDEX (2017) EXPLAINED BY GDP PER CAPITA
CURRENT PRICES FOR 2016
0
30,000
60,000
90,000
120,000
0 22.5 45 67.5 90
R² = 0.8673
18. DOMINANT OPERATORS, (BIGGEST
WITH 39% MARKETSHARE) ARE
NOT FUSSED BY LOW PRICES OF
SMALLER OPERATORS
• Smaller operators only offer services in the Kampala /
Entebbe
• Policy makers and regulators thus need to find ways
on how to increase competition on national level
• National roaming?
• Extend open access fibre network?
• Base -station level spectrum allocation instead of
national?
20. GDP PER CAPITA
Not in scope of policy makers
and regulators
SUMMATION
Value of indicators is lost in
aggregation
ANYTHING BUT PRICES
Indices are not linked to
prices, not even affordability
sub-indices
BENCHMARKING
Analytical power bears
responsibility
NOTALLANSWERED
M-Access starting point
rather then end result
AWAY FROM THE COFFEE TABLE
Global indices can be
improved to serve ICT policy
makers & regulators