Executive Summary

In 2016, OECD Agriculture Ministers issued a Declaration on Better Policies to Achieve a Productive, Sustainable and Resilient Global Food System, which placed “a high priority on developing policies to underpin competitive, sustainable, productive and resilient farm and food businesses” (OECD, 2016[1]). Recent and ongoing developments in digital technologies can help deliver such “better policies”. Advances in data collection technologies, particularly in situ and remote sensors, have markedly increased the spatial and temporal data resolution of agricultural data, and reduced the cost of gathering such information. Adoption of precision agriculture machinery in the agriculture sector provides a new source of data that is relevant for policy. Advances in data processing, “artificial intelligence” and computing power allow vast amounts of data from many and varied sources to be analysed and deliver new insight relevant for policy makers and administrators, as well as for producers and other actors in agriculture and food. Advances in encryption and data protection technologies, together with advances in institutions for data sharing, offer the opportunity to broaden access and reduce the transaction costs of accessing agricultural micro data while preserving confidentiality where necessary. These developments provide opportunities to improve policies by helping to overcome information gaps and asymmetries, lowering policy-related transaction costs and enabling people with different preferences and incentives to work better together.

Evidence from an OECD questionnaire highlights that policy administrators are already using digital technologies and data to improve the way they deliver agri-environmental policies. Use of some technologies and related data is developing faster than others, albeit often on an ad hoc basis even within government organisations. Currently, the digital technologies and data sources most commonly used by policy administrators are data from remote-sensing, GIS-based analytical tools, and digital communications tools. Almost all organisations responding to the questionnaire considered that digital technologies could provide benefits in terms of improving communications with other government organisations and with farmers, facilitating new programmes and services, and decreasing organisational costs. Further, only a minority of organisations considered that understanding the benefits, or communicating these benefits to stakeholders, were a challenge hampering the use of digital technologies or “Big Data” for policy purposes.

Yet, further opportunities are evident. Administrators can make use of digital technologies to improve current policies or enable new ones, for example policies that are more results-based or less compliance-driven. In particular, the paper identifies three key opportunities. First, governments have the opportunity to design and implement more “data-driven” policies and to evaluate policy performance more robustly. Second, governments can use digital technologies to re-think monitoring and compliance, reducing compliance burden for producers and public costs of administering monitoring and compliance programmes. Digital technologies can also enable new approaches which reward (financially or reputationally) going “beyond compliance”, rather than relying on heavy penalties to incentivise compliance. Finally, governments can make use of algorithms to improve administrative functions, reducing costs, freeing up staff time and reducing the likelihood of human error. Algorithms can also enable governments and researchers to undertake more complex and detailed analyses, to help produce new knowledge, faster.

However, available evidence shows that institutional and regulatory constraints can hamper the use of digital technologies by policy administrators in some cases. Perceived practical challenges include a lack of financial resources, and the substantial change to current workflows, policies or programmes that would be required to make more use of digital technologies and ‘Big Data’. Privacy or confidentiality regulations can also be a constraint in some cases. A lack of standardisation and differing regulatory regimes obstructs efforts to achieve representativeness or comparability in policy-relevant indicators.

Beyond existing constraints, there are a number of new issues that need to be addressed. Governments need to address the challenge of how to integrate data of varying quality, temporal and spatial scales, and sensitivity to produce useful knowledge. Governments can do more to encourage good data management practices and ensure sensor technologies are validated and calibrated for use in policy or regulatory contexts. Devolution of decision-making to computers within the policy cycle also raises several important questions about transparency, oversight and responsibility. An important issue is the need to be explicit about the limitations of data, models and algorithms, which is becoming ever more prominent as governments and industry increase their reliance upon them. Finally, adoption of new digital tools to deliver better policies risks creation of new information asymmetries or a “digital divide” between those who can access or use digital tools and those who cannot. Potential pitfalls await if these questions are not addressed satisfactorily.

More broadly, the capacity to make use of digital technologies in agriculture depends on more than access to basic connectivity infrastructure (broadband, telecommunication services, etc.). It also depends on development of a range of data collection and analysis services and on the regulatory environment (which encompasses interoperability rules, data quality standards, norms or regulations on data ownership and data privacy, skills, shared modelling frameworks, digital platforms, cloud-based storage and processing, etc.). These elements collectively shape the creation of effective systems of digitalisation in agriculture, and together provide an enabling data infrastructure.

Governments can play an active role in building data infrastructures for agriculture. In doing so, it is important that all uses of digital technologies, including for better agricultural and agri-environmental policies, are part of a coherent approach to digitalisation of the sector as a whole.

More specifically, governments can first make existing data relevant to agriculture more available to other actors to enable the development of new services supporting decision-making both by governments and farmers. Governments can also take an “online first” approach to delivery of government services and interactions with producers. This can reduce administrative costs for both governments and producers, and enable new kinds of services. Second, governments might have a role in supporting connectivity and the development of a data collection infrastructure (sensors network, remote sensing, etc.), including by directly investing in data collection technologies where there is a public good or public interest rationale to do so.

Executive Summary