In the ever-changing world of agriculture, collecting accurate and reliable data is crucial to guide policy decisions towards sustainable development and meet the growing needs for policy monitoring. However, in many countries, such as Liberia, statistical data collection is hampered by various obstacles such as adverse weather conditions and limited accessibility to remote locations.
The Food and Agriculture Organization of the United Nations (FAO) is currently providing technical assistance to Liberia to fill data gaps, particularly in areas where data collection is difficult due to extreme weather events or limited accessibility. This initiative aims to overcome challenges encountered during agricultural surveys, including difficult access to farms due to poor roads and the distances that survey teams have to walk.
The use of new technologies has helped improve the data collection process. For example, the crop cutting methodology allows for objective estimates by accurately measuring the weight of crops. This helps provide reliable estimates based on objective data directly from the field where crops are grown.
FAO’s 50×2030 project is a major initiative to close the agricultural data gap in 50 countries in Africa, Asia, the Middle East and Latin America by 2030. This collaboration between FAO, the World Bank and the International Fund for Agricultural Development aims to promote data-driven agriculture to address food crises, climate vulnerabilities and improve rural livelihoods.
It is essential that policymakers, countries and society at large have reliable data to develop, implement and monitor the impact of policies. Without accurate data, interventions could be poorly targeted or ineffective. Moreover, quality data are essential to attract funding from international donors, which often require strong evidence to commit resources.
Ultimately, accurate data is not only for governments and international agencies, but also for local communities to empower them and address their specific development needs. Collecting high-quality agricultural data is therefore a key pillar to support food security, reduce poverty and build resilience in rural communities around the world.