Ethiopia vs Sri Lanka: Statistical performance indicators (SPI): Pillar 1 data use score

Ethiopia
90 scale 0-100
in 2024
Sri Lanka
90 scale 0-100
in 2024
Ethiopia rank
61st
Sri Lanka rank
61st

Statistical performance indicators (SPI): Pillar 1 data use score over time

  • Ethiopia
  • Sri Lanka
20406080100200420142024

How they compare

Ethiopia currently reports 90 scale 0-100 against 90 scale 0-100 in Sri Lanka, a difference of 0 scale 0-100.

The two have swapped places 3 times across 21 shared years of data; in 2004 it was Ethiopia ahead.

Ethiopia ranks 61st and Sri Lanka ranks 61st of 217 countries.

Sri Lanka has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Ethiopia Sri Lanka Difference Ahead
2000s 31.67 scale 0-100 31.67 scale 0-100 0 scale 0-100
2010s 63 scale 0-100 76 scale 0-100 13 scale 0-100 Sri Lanka
2020s 86 scale 0-100 94 scale 0-100 8 scale 0-100 Sri Lanka

Averages of every year both report within each decade.

Frequently asked questions

Which has higher statistical performance indicators (spi): pillar 1 data use score, Ethiopia or Sri Lanka?
Ethiopia, at 90 scale 0-100 against 90 scale 0-100 in Sri Lanka as of 2024.
What is the difference in statistical performance indicators (spi): pillar 1 data use score between Ethiopia and Sri Lanka?
0 scale 0-100, with Ethiopia ahead.
How many years of comparable data are there for Ethiopia and Sri Lanka?
21 years are reported by both, from 2004 to 2024.
How do Ethiopia and Sri Lanka rank globally for statistical performance indicators (spi): pillar 1 data use score?
Ethiopia ranks 61st and Sri Lanka ranks 61st of 217 countries.
Where does this data come from?
Statistical Performance Indicators, World Bank (WB), published as Statistical performance indicators (SPI): Pillar 1 data use score (scale 0-100). Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Ethiopia vs Sri Lanka: Statistical performance indicators (SPI): Pillar 1 data use score. Statizoid, drawing on Statistical Performance Indicators, World Bank (WB). Retrieved 17 August 2026, from https://public-sector.statizoid.com/compare/statistical-performance-indicators-spi-pillar-1-data-use-score-scale-0-100/ethiopia/sri-lanka/

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Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY 4.0 (World Bank Open Data); please keep the attribution.

<a href="https://public-sector.statizoid.com/compare/statistical-performance-indicators-spi-pillar-1-data-use-score-scale-0-100/ethiopia/sri-lanka/">Ethiopia vs Sri Lanka: Statistical performance indicators (SPI): Pillar 1 data use score</a> — Statizoid

About this data

Indicator
Statistical performance indicators (SPI): Pillar 1 data use score (scale 0-100)
Unit
scale 0-100
Source
Statistical Performance Indicators, World Bank (WB)
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
221 places, 4,593 data points, 2004–2024
Last refreshed

The data use overall score is a composite score measuring the demand side of the statistical system. The data use pillar is segmented by five types of users: (i) the legislature, (ii) the executive branch, (iii) civil society (including sub-national actors), (iv) academia and (v) international bodies. Each dimension would have associated indicators to measure performance. A mature system would score well across all dimensions whereas a less mature one would have weaker scores along certain dimensions. The gaps would give insights into prioritization among user groups and help answer questions as to why the existing services are not resulting in higher use of national statistics in a particular segment. Currently, the SPI only features indicators for one of the five dimensions of data use, which is data use by international organizations. Indicators on whether statistical systems are providing useful data to their national governments (legislature and executive branches), to civil society, and to academia are absent. Thus the dashboard does not yet assess if national statistical systems are meeting the data needs of a large swathe of users.