Cuba vs Sudan: Statistical performance indicators (SPI): Pillar 1 data use score

Cuba
40 scale 0-100
in 2024
Sudan
46.6 scale 0-100
in 2024
Cuba rank
186th
Sudan rank
183rd

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

  • Cuba
  • Sudan
20406080200420142024

How they compare

Sudan currently reports 46.6 scale 0-100 against 40 scale 0-100 in Cuba, a difference of 6.6 scale 0-100.

That makes Sudan's figure about 1.2 times Cuba's.

The two have swapped places 4 times across 21 shared years of data; in 2004 it was Sudan ahead.

Globally, Cuba ranks 186th and Sudan ranks 183rd of 217 countries.

Individual pages

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.