Global Strategy to Improve Agricultural and Rural Statistics

Advanced Training on CAPI in Mali Enhances Agricultural Data Collection Skills

31/01/2024

The Global Strategy to Improve Agricultural and Rural Statistics Phase 2 (GSARS-II), in its commitment to enhancing agricultural and rural statistics, has successfully concluded an advanced training workshop in Mali. The workshop, held from November 19th to December 2nd, 2023, focused on the Computer Assisted Personal Interview (CAPI) methodology using statistical software. This innovative approach to data collection, which involves digital devices for recording survey responses, enhances efficiency and accuracy, especially in agricultural statistics. 

Led by Nagbégna DIABATE, a Data Analyst from the ESS Division of the Food and Agriculture Organization (FAO), the workshop's main goal was to empower participants with the skills to design CAPI applications for the Agricultural Conjuncture Survey (EAC). Participants included members of the Cellule de Planification et de Statistique du Secteur du Développement Rural (CPS/SDR).  

The training covered various aspects of statistical softwares, including data collection methodology, designing data entry masks, deploying applications on Android tablets, and data synchronization. By the end of the workshop, participants were able to create functional CAPI applications tested on tablets, demonstrating significant skill development. 

This initiative aligns with GSARS's mission to strengthen the statistical capacities of countries, particularly in the collection and exploitation of agricultural data. The successful workshop marks a crucial step in enhancing Mali's agricultural data systems and contributes to the broader goals of sustainable agricultural development and policy formulation. 

The success of this workshop and similar initiatives in Mali owes much to the support of the FAO Country Office and the generosity of donors such as the European Union and the Bill & Melinda Gates Foundation. Their commitment to agricultural development and data-driven decision-making continues to greatly impact the global agricultural sector.