On 24 November 2025, the World Bank released 2025 update of the Statistical Performance Indicators (SPI), adding results for the 2024 calendar year and revising earlier years. The SPI provides an open-source framework for assessing the performance of statistical systems and the efforts to improve them. The SPI breaks down national statistical performance into five pillars and 22 dimensions, each backed by open data and code. Dive into the SPI data here or learn more about the framework on our SPI webpage.
This year’s release is purely an update to the data and does not introduce any methodological changes. The scoring framework, sources, and construction of the SPI remain fully comparable with earlier vintages; all changes in an economy’s scores come from new or updated underlying data (see the What’s New note for details). Most revisions to prior estimates reflect fresh information on the use of data in international databases (Pillar 1) and on the availability of key censuses and surveys (Pillar 4), together with updates to selected data infrastructure indicators (Pillar 5).
The new data confirms that the stagnation in statistical performance seen since COVID-19 has continued. From 2016 to 2021, global SPI scores rose steadily, primarily due to large improvements in data services and infrastructure, but this momentum stalled with the onset of COVID-19: by 2023, global averages had largely flattened. The new data shows that this plateau has persisted in 2024. Progress is especially weak in the data sources pillar, where censuses, surveys, and other data core sources are lagging behind.
The SPI Overall Score is now available for 188 economies, representing more than 99 percent of the world population.1 There has been an increase in the number of economies with an SPI overall score since 2016, with a rise from 167 economies to 188.
1 The countries without an SPI Overall Score can be seen in the What’s New.
Statistical performance: a global snapshot
There is substantial variance in statistical performance across economies. High-income regions, mainly Europe, North America, and Australia, still lead the way in terms of statistical performance. Conversely, Sub-Saharan Africa and Small Island Developing States are still areas in need of improvement. From 2016 to 2024, the average SPI scores in low-income nations increased by 10 percentage points — compared with 12 percentage points for high-income nations.
Why does income tend to generate higher SPI scores? High-income countries typically have more resources to spend on improving National Statistical Systems (NSS) by upgrading data infrastructure — for instance, hiring more national statistical office (NSO) staff and improving data collection.
Figure 1: Map of Overall SPI Scores
Trends over time: 2016-2024
SPI scores have improved worldwide by an average of 12% since 2016, largely driven by gains in data services and infrastructure. North America and Europe & Central Asia rank highest, with East Asia & the Pacific, and Latin America & the Caribbean following. While richer economies have the highest level of statistical performance, they have actually seen a decline in 2024. On the other hand, we see some improvements from lower income economies who are busy closing the gap.
Figure 2: SPI trends by World Bank Income Group
It is substantially easier to make gains from a low starting point, where incremental effort yields much larger marginal improvements in performance. Consequently, lower- to upper-middle countries in Latin & Central American Africa, Eastern European and South Asia have realised most SPI gains. Figure 3 shows the global distributions of improvements in SPI. Sub-Saharan Africa has seen mixed results, and is home to some of the economies with the biggest improvements — such as Benin, Burkina Faso, The Gambia, Senegal, and Zimbabwe — as well as some that have taken a step backward since 2016 — such as Burundi, the Republic of Congo, and South Sudan. Other countries that have decreased statistical performance since 2016 are Venezuela and Yemen. The economies with high statistical performance, such as those in North America and Europe, predictably find it more difficult to improve rapidly.
Figure 3: Map showing global changes in SPI since 2016
What pillars are driving most of these gains?
The SPI framework assesses the maturity and performance of national statistical systems in five key areas, called pillars. The five pillars are: The SPI is broken down into five separate pillars: i) Data Use, ii) Data Services iii) Data Products iv) Data Sources v) Data Infrastructure.
What pillars of the SPI score are driving most of these gains? Since 2016, the Data Services score has increased by an average of 25 percent, disproportionately driven by countries with mid to low SPI scores. For example, Data Openness — as proxied by the ODIN openness score — has risen by approximately 66% from 2016. This is somewhat promising; it suggests that lower-scoring countries are catching up and converging to their higher-income counterparts.
Figure 4: Global SPI trends for all pillars
However, not all pillars have seen improvement. Improvements in producing adequate data sources have stalled, growing only 3% since 2016. Data shows only a handful of countries have increased their data sources' figures by more than 10 points, and most countries have grown 0-10 points or declined.
Statistical performance and resourcing
As mentioned above, income is a key predictor of statistical capacity. However, income is not destiny when it comes to statistical performance. A number of countries have managed to punch far above their GDP per capita. The chart below highlights five countries — Burkina Faso, Senegal, Uzbekistan, Philippines, and Mexico — as the countries who have outperformed relative to what would be predicted by their GDP per capita. On the other hand, Equatorial Guinea, Libya, Dominica, Turkmenistan, and St. Kitts and Nevis are highlighted as underperformers.
Figure 5: SPI overperformers and underperformers
What enables a country to overperform? We can look at Burkina Faso as an example. The NSO, the National Institute of Statistics and Demography, has used the platform of their National Strategy for the Development of Statistics (NSDS) to focus on building strong and modern fundamentals. This has included a drive to improve the data infrastructure and standards, as well as enhancing the services that allow users to access data. An example like Burkina Faso shows that substantial improvements are possible if efforts are well coordinated and supported.
Figure 6: Burkina Faso's SPI growth
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