7105.0.55.004 - National Agricultural Statistics Review

7105.0.55.004 - National Agricultural Statistics Review - Final Report, 2015

ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 29/07/2015 First Issue

Page tools: Print Page Print All
Foreword Executive Summary + Chapter 1 - Introduction + Chapter 2 - The current Australian agricultural statistical system + Chapter 3 - Stakeholder feedback on the current Australian statistics system + Chapter 4 - Principles of best practice agricultural statistical systems + Chapter 5 - Assessment of the Australian system against the best practice principles 1. Strong governance and coordination 2. A clearly articulated strategy to guide future investment 3. Use of best practice methods and sources to maximise data quality and minimise respondent burden 4. Investment in, and use of, innovative technologies, methods and processes across the statistical cycle 5. A culture of open data Chapter 6 - Towards a best practice agricultural system About this Release	4. INVESTMENT IN, AND USE OF, INNOVATIVE TECHNOLOGIES, METHODS AND PROCESSES ACROSS THE STATISTICAL CYCLE While there has been investment in new technologies and innovations in the agricultural statistical system by various stakeholders, including government, this investment could be better coordinated and targeted at those technologies and innovations that will best support the overarching strategy. The issues raised through the NASR indicate there are likely to be benefits from investing in technologies and innovations that reduce respondent burden and improve data quality, and that exploit the potential to provide new statistics relevant to current and emerging issues and decisions. The potential for technologies to improve data dissemination and output should also be explored to improve data accessibility and discoverability. The NASR consultation identified a number of potential innovations and technologies for further consideration. These ranged across the full statistical cycle, including data collection, data processing, analysis, and dissemination. For example, greater use of e-forms and smart phone apps in the data collection phase has potential to improve the respondent experience and the timeliness and quality of responses. The USDA has been using Electronic Data Reporting forms for the US Agricultural Census since 2007 and reported reductions in processing time and increased cost-effectiveness as a result of this shift⁶⁶. Other ways of collecting data should also be investigated, including ‘big data’, remote sensing and sensor technologies embedded in production systems and supply chains that could offer potential efficiencies through automated collection of data, and lead to improved data quality, particularly timeliness. Similarly, improved use of data integration in the data processing, analysis and dissemination phases could enable the production of new, value-added statistical products from existing sources. The integration of frameworks such as accounting frameworks would improve the coherence of data sources by enabling them to be organised according to common standards, definitions and classifications. To explore the potential of these and other options, coordinated research and development should be encouraged and guided by the overarching objectives of reducing burden, improving data quality and delivering efficiencies to the agricultural statistical system. Ideally, this would involve government and industry, and involve exploration of partnerships with the private sector to develop and implement new technologies. FOOTNOTES ⁶⁶ Surveying America's Farmers Online - An Innovation in Collecting Ag Stats Document Selection These documents will be presented in a new window.