National Farm Survey
Digital sustainability auditing and benchmarking tool for Irish dairy farms
Description
The National Farm Survey (NFS) has been conducted by Teagasc on an annual basis since 1972. The survey is operated as part of the Farm Accountancy Data Network of the EU and fulfils Ireland’s statutory obligation to provide data on farm output, costs and income to the European Commission. A random, nationally representative sample, of between 1,000 and 1,200 farms depending on the year, is selected annually in conjunction with the Central Statistics Office (CSO). Each farm is assigned a weighting factor so that the results of the survey are representative of the national population of farms.
Technology
Reports published on the Teagasc website as well as an online dashboard provide insights into the National Farm Survey data.
Target
The main users of the NFS data include farmers and farm advisors, who use it to benchmark performance and plan farm businesses; researchers and academic institutions, who rely on it for financial, technical, and socio-economic farm-level analysis; economists and policy makers, particularly at national and EU level, who use it to design, monitor, and evaluate agricultural policies (including through FADN); Teagasc and the EU Farm Accountancy Data Network (FADN), to meet Ireland’s statutory reporting obligations; and the Central Statistics Office (CSO), which uses the data to compile national agricultural statistics and conduct surveys such as the Household Budget Survey for farming households. The reports and the dashboard are also publicly accessible for wider stakeholder use.
Business model
The survey is operated as part of the Farm Accountancy Data Network of the EU.
Impact
The National Farm Survey aims to improve the availability of consistent and comparable sustainability data for Irish agriculture.
Partners
Glanbia; Dairygold; SmartAgriHubs consortium; Department of Agriculture, Food and the Marine; Teagasc Agricultural Economics & Farm Surveys Department
Four Betters
Better environment
Better production
