GASTAT Releases Updated National GSBPM To Standardize Statistical Processes

The General Authority for Statistics (GASTAT) has released an updated national version of the Generic Statistical Business Process Model (GSBPM). This model serves as a methodological framework for statistical work in Saudi Arabia and is a primary reference for issuing statistics in both government and private institutions.

The updated GSBPM aims to improve the quality of statistical processes at all stages. It aligns with the latest international version issued by the United Nations Economic Commission for Europe. This alignment helps standardise work processes used in producing statistics, enhancing their quality and effectiveness to meet the targets of Vision 2030.

The new version includes terminology, definitions, and details about the stages of statistical production. These stages range from identifying needs to design, data collection, processing, analysis, publication, and evaluation. This harmonisation brings Saudi statistical work in line with methodologies applied by many international statistical agencies.

GASTAT has made the model available on its official website in both Arabic and English. Statisticians, researchers, government and private institutions, and other interested parties can download it for use. Customers can also contact GASTAT for further information and explanations about the model.

This updated model facilitates coordination among various sectors involved in statistics. By providing a unified framework, it ensures that different entities can collaborate more effectively on statistical projects.

Commitment to Excellence

GASTAT is committed to offering comprehensive and credible statistical products and services. The authority aims to align with the best international standards and practices. Their goal is to become the most distinguished and innovative statistical reference supporting social and economic development in Saudi Arabia.

The release of this updated GSBPM reflects GASTAT's dedication to improving statistical methodologies within the Kingdom. By adopting internationally recognised standards, they aim to enhance the reliability and utility of their statistical outputs.

This initiative is part of broader efforts to support Vision 2030 by providing high-quality data that can inform policy decisions. The availability of this model in multiple languages ensures that it is accessible to a wide audience, promoting transparency and inclusivity in statistical work.

With inputs from SPA