# **Appendix A: Pillars of the SPI**

A quick primer on names. We refer to the 5 rows in the framework in Figure 1 as pillars. We refer to the 22 cells in the framework in Figure 1 as dimensions. Finally, each dimension may be composed of multiple indicators. For instance, the dimension on censuses and surveys is made up of indicators on whether population censuses have been conducted, agriculture censuses, labor force surveys, etc.

# **3.1 Data use**

The data use pillar is segmented by user type. The tiles on the Dashboard provide an indicator of use of statistics respectively by the legislature, executive, civil society (including sub-national actors), academia and international bodies. A mature system would score well across the tiles. Areas for development would be highlighted by weaker scores in that domain enabling questions to be asked about prioritization among user groups and why existing services are not resulting in higher use of national statistics in that segment.

# **3.2 Data services**

The data services pillar is segmented by service type. The tiles on the Dashboard provide an indicator of the quality of data releases, the richness and openness of online access, the effectiveness of advisory and analytical services related to statistics and the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including ethical consideration of proposals and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.

# **3.3 Data products**

The data products pillar is segmented by topic and organized into social, economic, environmental and institutional domains using the typology of the Sustainable Development Goals. This approach enables comparisons across countries and anchors the system in the 2030 agenda so that a global view can be generated while enabling different emphasis to be applied in different countries to reflect the user needs of that country.

# **3.4 Data sources**

The data sources pillar is segmented between sources generated by the statistical office (censuses and surveys) and sources accessed from elsewhere (administrative data, geospatial data, private sector data and citizen generated data). The appropriate balance between these types of sources will vary depending on the institutional setting and maturity of the statistical system in each country. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics may reflect a lack of use of (and low score for) geospatial data. This linkage, which is inherent in the data cycle approach, should help highlight areas for investment if country needs are to be met. **3.5 Data infrastructure** The data infrastructure pillar is segmented into hard and soft infrastructure segments itemizing essential cross-cutting requirements for an effective statistical system. The segments are:

1. Legislation and governance covering the existence of laws and a functioning institutional framework for the statistical system

2. Standards and methods addressing compliance with recognized frameworks and concepts 3. Skills including level of skills within the statistical system and among users (statistical literacy) 4. Partnerships reflecting the need for the statistical system to be inclusive and coherent 5. Finance, both domestically and from donors 36