Countries by Statistical performance indicators (SPI): Pillar 2 data services score (scale 0-100)

Malaysia leads 190 countries in the World Bank's Statistical Performance Indicators (SPI) Pillar 2 data services score with a value of 99.67, while Turkmenistan ranks last at 5.30. The gap of more than 94 points between first and last reflects profound differences in the quality, accessibility, and richness of national statistical data services worldwide.

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Ranking 2024

Countries by Statistical performance indicators (SPI): Pillar 2 data services score (scale 0-100)
Rank	Country	Value
1	Malaysia	99.67
2	Poland	99
3	Norway	98.57
4	Slovenia	98.53
5	Singapore	98.4
6	Finland	98.2
7	Denmark	97.83
8	Portugal	97.63
9	Netherlands	97.23
10	Ireland	97.13
11	Latvia	96.8
12	Mongolia	96.33
13	Estonia	96.3
14	South Korea	96.1
15	Senegal	96.03
16	Moldova	96
17	Morocco	95.8
18	Hungary	95.53
19	Sweden	95.4
20	Germany	95.33
21	Australia	95.17
22	Slovakia	95.1
23	United States	95
24	New Zealand	94.9
25	Romania	94.7
26	Israel	94.2
27	Georgia	93.77
28	Jordan	93.57
29	Canada	93.3
30	Mexico	93.23
31	Saudi Arabia	93.2
32	Philippines	92.97
33	Italy	92.7
34	United Kingdom	92.6
35	Bulgaria	92.53
36	Austria	92.43
37	Spain	92.33
37	Palestine	92.33
39	Lithuania	92
40	Indonesia	91.87
41	Japan	91.83
42	Luxembourg	91.53
43	France	90.17
44	Kazakhstan	90.13
45	Tunisia	89.97
46	Malta	89.3
47	Czechia	89
47	Ecuador	89
49	Brazil	88.97
49	Costa Rica	88.97
51	Colombia	88.37
52	Chile	88.23
52	North Macedonia	88.23
54	Russia	87.97
55	Thailand	87.93
56	Switzerland	87.9
57	Croatia	87.53
58	Mauritius	87.3
59	Peru	87.17
60	Cyprus	86.57
61	Türkiye	86.4
62	Armenia	86.2
63	Argentina	85.67
64	Uruguay	85.3
65	India	85.13
66	Greece	85.03
67	Belgium	85
68	South Africa	84.63
69	United Arab Emirates	81.6
70	Sri Lanka	81.53
71	Egypt	80.8
72	Uzbekistan	79.13
73	Burkina Faso	78.4
74	El Salvador	77.23
75	Serbia	76.57
76	Niger	76.37
77	Côte d'Ivoire	76.3
78	Central African Republic	75.73
79	Cameroon	75
80	Paraguay	74.03
81	Jamaica	73.6
82	Suriname	72.63
83	Brunei	72.23
84	Rwanda	72.13
85	Panama	71.67
86	Benin	71.37
87	Montenegro	71.33
88	Tanzania	71.23
88	Uganda	71.23
90	Nigeria	70.97
91	Mali	70.67
92	Kenya	70.6
93	Myanmar	70.47
94	Kosovo	70.2
95	Dominican Republic	69.67
96	Albania	69
97	Tajikistan	68.97
98	Kuwait	68.87
99	Botswana	68.67
100	Saint Lucia	68.13
101	Guatemala	68.1
101	Trinidad and Tobago	68.1
103	Togo	68.03
104	Bolivia	67.9
105	Belize	67.73
106	Vietnam	67.67
107	Laos	67.4
108	Guyana	66.83
109	Qatar	66.8
110	Chad	66.73
110	Ghana	66.73
112	Mozambique	66.67
112	Zimbabwe	66.67
114	Namibia	66.63
115	Gambia	66.57
115	Maldives	66.57
117	Bhutan	66.33
118	Saint Vincent and the Grenadines	66.3
119	Iraq	66.27
120	Nepal	66.23
121	Honduras	66
122	Sao Tome and Principe	65.67
123	Bosnia and Herzegovina	65.6
124	Afghanistan	65.1
125	Ethiopia	64.43
126	Sierra Leone	64.37
127	Cambodia	64.27
128	Mauritania	63.9
129	Samoa	63.7
130	Bangladesh	63.47
131	Malawi	63.27
132	Nicaragua	63.2
133	Fiji	63.13
134	Angola	63.07
134	Kiribati	63.07
136	Antigua and Barbuda	62.9
137	Iceland	62.83
138	DR Congo	62.8
138	Iran	62.8
138	Lebanon	62.8
141	Solomon Islands	62.77
142	Barbados	62.57
143	Eswatini	62.53
143	Zambia	62.53
145	Marshall Islands	62.33
146	Papua New Guinea	62.23
147	Tonga	62.17
148	Pakistan	61.97
149	Madagascar	61.77
149	Timor-Leste	61.77
151	Vanuatu	61.67
152	Palau	61.57
153	Tuvalu	61.07
154	San Marino	60.73
155	Liberia	59.93
156	Libya	59.33
157	Algeria	58.9
158	Micronesia	58.57
159	Sudan	57.93
160	Ukraine	55.13
161	Andorra	55.03
162	Belarus	53.8
163	Kyrgyzstan	50.87
164	Oman	48.83
165	Somalia	48.73
166	Seychelles	48
167	China	43.93
168	Burundi	42.47
169	Nauru	40.7
170	Bahrain	39.53
171	Azerbaijan	36.9
172	Comoros	33.6
173	Cabo Verde	31.8
174	Lesotho	31.47
175	Guinea	30.6
176	Saint Kitts and Nevis	30.5
177	Gabon	30.23
178	Dominica	29.93
179	Equatorial Guinea	29.63
180	Guinea-Bissau	29.5
181	Republic of Congo	29.17
182	Grenada	28.83
183	Yemen	28.3
184	Djibouti	28.27
185	Bahamas	27.3
186	Syria	26.43
187	Haiti	24.97
188	Venezuela	24.4
189	South Sudan	8.33
190	Turkmenistan	5.3

Analysis

This metric measures how well countries deliver statistical data services to users. According to the source definition, the data services pillar overall score is a composite indicator based on four dimensions: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Scores are expressed on a scale of 0 to 100, where higher values indicate better performance. The dataset covers 190 countries with data from 2024, with 100% of datapoints classified as official and no extreme outliers detected at the 3-standard-deviation threshold. The full range runs from 5.30 to 99.67, a spread of 1,780.5%.

The top of the ranking is dominated by a mix of European nations, high-income Asian economies, and a few notable exceptions. Malaysia (rank 1, 99.67) leads ahead of Poland (rank 2, 99.00) and Norway (rank 3, 98.57). Slovenia (rank 4, 98.53) and Singapore (rank 5, 98.40) round out the top five. The top 20 includes Finland (rank 6, 98.20), Denmark (rank 7, 97.83), Portugal (rank 8, 97.63), Netherlands (rank 9, 97.23), and Ireland (rank 10, 97.13). Mongolia (rank 12, 96.33) and Senegal (rank 15, 96.03) appear in the top 15, placing ahead of several high-income Western nations, which is notable. Morocco (rank 17, 95.80) and Moldova (rank 16, 96.00) also score in the top 20.

In the middle of the ranking, scores range broadly through the 60s and 70s. Serbia sits at rank 75 with a score of 76.57, while Viet Nam ranks 106 at 67.67 and Bangladesh ranks 130 at 63.47. Iceland, a high-income Nordic country, ranks 137 with a score of only 62.83, placing it below countries such as Kiribati (rank 134, 63.07) and Samoa (rank 129, 63.70). At the lower end, China ranks 167 with a score of 43.93, and Bahrain ranks 170 at 39.53. The bottom five include Dominica (rank 178, 29.93), Equatorial Guinea (rank 179, 29.63), Guinea-Bissau (rank 180, 29.50), Congo, Rep. (rank 181, 29.17), and Grenada (rank 182, 28.83), with South Sudan (rank 189, 8.33) and Turkmenistan (rank 190, 5.30) at the very bottom.

Several limitations apply to this metric. The composite structure means that weaknesses in any one of the four sub-dimensions can significantly depress a country's overall score, without indicating which specific area is deficient. The source note itself is truncated, noting that advisory and analytical services may not be fully captured in the definition as published. Countries with limited statistical infrastructure may also underreport the very data used to score them, creating a potential downward bias at the lower end. Scores reflect a single reference year (2024) and annual volatility averaged 24.7% year-over-year, suggesting that rankings can shift materially between periods. Comparisons between countries at similar score levels should be made with caution given the composite nature of the indicator.

Methodology

The metric is drawn from the World Bank World Development Indicators, indicator code IQ.SPI.PIL2, with data for the reference year 2024. As defined in the source note, the data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might not be fully captured in the definition as published. Scores are expressed on a scale of 0 to 100; higher scores indicate better performance. The ranking covers 190 countries, all with data from within the last 7 years (100% recency). All 190 datapoints are classified as official quality. No extreme outliers were identified at the 3-standard-deviation threshold. The data range spans 5.30 to 99.67, a spread of 1,780.5%. Average year-over-year change across the dataset is 24.7%, indicating moderate but meaningful volatility. The composite construction of the indicator means that individual sub-dimension scores are not directly visible in the aggregate ranking.

Sources

World Bank