Mongolia's story is one of those featured in the GovMesh Digest special report. You can find the individual stories on the other participating governments at GovMesh 4.0 here.

Evidence-based policymaking was a priority for governments worldwide. But fragmented data across different agencies remained a persistent challenge in many countries. 

Rather than functioning as a shared asset, data often developed within institutional silos, limiting its strategic value and preventing optimal use. 

The cost of decision-making became high if individual agencies manage their own systems and data, said Director General of the National Statistics Office of Mongolia, Ariunbold Shagdar. 

One of Mongolia’s key efforts to address this challenge has been to pursue data integration through a series of pilot projects that have since evolved into a more systemic approach. 

The National Statistics Office played a central role in this effort, managing two core registration systems: population and housing, and business registration.  

The former is individual-based, while the latter is based on legal entities. 

By connecting these two systems, the government has begun to build a more comprehensive picture of the country’s conditions.  

“If we connect these systems, we can see a better picture of the country. Every policy and programme could be more productive and efficient,” he added. 

Shagdar was speaking at GovMesh 4.0, held by GovInsider and interweave.gov on March 2 in Singapore, where representatives from six countries gathered to discuss data-driven governance.  

From face-to-face to register-based census 

One of the most visible impacts of data integration pilots was how it has transformed census operations.

While census collection was previously conducted entirely through face-to-face, the approach has now shifted significantly. 

Mongolia's National Statistics Office Director General, Ariunbold Shagdar, presenting at GovMesh

He shared that by adopting a mixed-method approach for the 2020 Population and Housing Census, the National Statistics Office of Mongolia achieved significant cost efficiencies.  

“By utilising administrative registers for 90 per cent of the data and face-to-face interviews for only 10 per cent, the project budget was reduced from 15.2 billion MNT ($5.4 millon) to 4.7 billion MNT ($1.7 million) - a total saving of 10.5 billion MNT ($3.7 million).  

“Furthermore, by moving to a fully register-based system, the 2025 census cost less than one billion MNT ($282,064).”  

Supported by automation tools such as ETL (extract, transform, load), Mongolia is also exploring the possibility of conducting annual census updates to provide more timely data for policymakers. 

Addressing inter-agency resistance 

The journey towards integration has not been without challenges, particularly resistance from government agencies and lack of compliance with data standardisation.

This is why the Mongolian government has rolled out several policies to mandate data sharing, supported by legal frameworks on statistics, transparency and data protection. 

For Shagdar, success depended not only on regulation, but also on leadership and the presence of a trusted institution to drive the initiative. 

“There should be leadership. Some organisation should lead this initiative,” he noted. 

He also highlighted the importance of an incremental approach, rather than waiting for perfect conditions. 

Instead of waiting for everything to be ready, Mongolia has adopted a “learning by doing” approach by building systems while continuously refining them. 

Building the foundations of a data ecosystem  

The Mongolian government was also developing a broader data ecosystem, including a national database with multiple layers including aggregated data, customised datasets and data visualisation tools.

Metadata standardisation has become a priority to ensure interoperability across systems. 

“If we want to integrate all government databases, we should standardise metadata,” he explained. 

In addition, Mongolia is establishing data laboratories, expanding access to statistical data, and revising legal frameworks to support greater data openness. 

Shagdar emphasised that lasting change depends on demonstrating tangible results.  

“We should demonstrate some very good flagship work. Over time, it will work,” he said. 

Published Date:2026-04-22