Methodological innovation
FAO develops methods and standards for food and agriculture statistics to produce timely and high-quality data. In order to guarantee the quality and consistency of statistical activities, the Organization has developed corporate Statistical Quality Assurance Framework with a set of Statistical Standards.
FAO Statistics Division works to strengthen the statistical processes throughout the Organization by developing improved methods and their implementation in the corporate Statistical Working System.
FAO Statistical Working System
FAO Statistical Working System is a corporate platform used in FAO for the processing and storage of statistical datasets, providing the framework needed to use the same methods, standards, classifications and approaches within statistical processes. Within the FAO Statistical Working System, the methodological innovation work focuses on progressively integrates the corporate statistical processes with the aim to improve the quality of FAO statistical production, methods and outputs.
Data Lab on Statistical Innovation
FAO develops new methods using Big Data and based on Data Science to impute missing data. With this aim, FAO established the Data Lab on Statistical Innovation, a gate to the innovative statistical tools that provides timely and detailed data and analysis, drawing insights from diverse information to support decision making. Through the use of non-traditional sources, such as datasets, data catalogues on the web, documents, news and social media posts, the Data Lab contributes to filling in data gaps in domains and geographical areas in which there is little official data available. The Data Lab is also supporting FAO’s Hand-in-Hand Initiative with the objective of accelerating progress on Sustainable Development Goals in 43 focus countries with the highest poverty and hunger rates.
To promote consistency and comparability of information at the world level, FAO statistics provides national statistical offices with internationally recognized definitions, concepts and classifications.
