Saint Vincent and the Grenadines vs Vanuatu: Statistical performance indicators (SPI): Pillar 1 data use score

Saint Vincent and the Grenadines
50 scale 0-100
in 2024
Vanuatu
56.6 scale 0-100
in 2024
Saint Vincent and the Grenadines rank
172nd
Vanuatu rank
171st

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

  • Saint Vincent and the Grenadines
  • Vanuatu
203040506070200420142024

How they compare

Vanuatu currently reports 56.6 scale 0-100 against 50 scale 0-100 in Saint Vincent and the Grenadines, a difference of 6.6 scale 0-100.

That makes Vanuatu's figure about 1.1 times Saint Vincent and the Grenadines's.

The two have swapped places 2 times across 21 shared years of data; in 2004 it was Vanuatu ahead.

Saint Vincent and the Grenadines ranks 172nd and Vanuatu ranks 171st of 216 countries.

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

Head to head by decade

Decade Saint Vincent and the Grenadines Vanuatu Difference Ahead
2000s 20 scale 0-100 20 scale 0-100 0 scale 0-100
2010s 34 scale 0-100 41.66 scale 0-100 7.66 scale 0-100 Vanuatu
2020s 34 scale 0-100 56.6 scale 0-100 22.6 scale 0-100 Vanuatu

Averages of every year both report within each decade.

Frequently asked questions

Which has higher statistical performance indicators (spi): pillar 1 data use score, Saint Vincent and the Grenadines or Vanuatu?
Vanuatu, at 56.6 scale 0-100 against 50 scale 0-100 in Saint Vincent and the Grenadines as of 2024.
What is the difference in statistical performance indicators (spi): pillar 1 data use score between Saint Vincent and the Grenadines and Vanuatu?
6.6 scale 0-100, with Vanuatu ahead.
How many years of comparable data are there for Saint Vincent and the Grenadines and Vanuatu?
21 years are reported by both, from 2004 to 2024.
How do Saint Vincent and the Grenadines and Vanuatu rank globally for statistical performance indicators (spi): pillar 1 data use score?
Saint Vincent and the Grenadines ranks 172nd and Vanuatu ranks 171st of 216 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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Saint Vincent and the Grenadines vs Vanuatu: Statistical performance indicators (SPI): Pillar 1 data use score. Statizoid, drawing on Statistical Performance Indicators, World Bank (WB). Retrieved 21 August 2026, from https://public-sector.statizoid.com/compare/statistical-performance-indicators-spi-pillar-1-data-use-score-scale-0-100/st-vincent-and-the-grenadines/vanuatu/

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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.