Abstract

This paper presents the FAO Food Balance Sheet (FBS) Shiny Application, a browser-based platform designed to make FAO’s revised FBS methodology accessible to national statistical systems without requiring programming expertise. Food Balance Sheets are central to agricultural policy, food security analysis, and nutrition monitoring, but independent national compilation has remained difficult in many low- and middle-income countries because the methodology is technically complex and traditionally implemented in R. The application addresses this barrier by combining data entry, imputation, balancing, standardisation, and analysis in a single multilingual interface.

The platform supports structured compilation of supply-utilisation accounts through spreadsheet-like editing, Excel import-export, audit trails, and a comprehensive flags system that records data source and production method. Its imputation routines handle missing stock, loss, and consumption data using rules-based and demand-based approaches. A balancing algorithm then reconciles supply and utilisation using historical patterns and commodity-specific residual rules, while standardisation converts processed forms into primary equivalents through editable commodity processing trees and nutrient coefficients. Because the application is centrally hosted, users access the same up-to-date methodology through a standard web browser, with synchronised collaboration and country-specific access control.

Evidence from pilot implementations in Bhutan, Mauritius, Eswatini, Angola, and Guatemala shows that the application improves both usability and statistical relevance. In Bhutan, national compilers used detailed supply-chain intelligence, such as importer identity and business activity, to classify commodity use more accurately than global imputation would allow. In Guatemala, national compilation revealed that tortillas, a major staple food, are absent from the global commodity tree, demonstrating how local use of the tool can identify structural gaps in the international framework and support methodological improvement. Across pilots, the flags system also exposed previously unorganised information on data quality and production practices, helping target capacity building more precisely.

Beyond compilation, the application generates integrated policy dashboards on productivity, trade in primary equivalents, self-sufficiency, utilisation structure, and dietary indicators. The paper argues that this combination of national flexibility, methodological consistency, and automatic policy analysis turns the FBS from a technical statistical product into a practical decision-support system. More broadly, the platform offers a model for bottom-up strengthening of agricultural statistics: national compilation improves country estimates while simultaneously contributing to a more accurate global food data infrastructure.