Digital Opportunities for Better Agricultural Policies

Chapter 1.  Overview of findings and recommendations

Abstract

This overview draws together the findings from this report and provides recommendations for policy makers and agri-environmental programme administrators, both about how they can make use of digital technologies to improve policies, and how policies can appropriately support uptake of digital technologies in agriculture. Further, some recommendations are relevant for governments more broadly, as they touch on issues such as innovation and competition.

1.1. How can governments best use digital technologies to improve agri-environmental policies?

Digital technologies can help achieve policy goals by reducing the problems caused by information gaps, information asymmetries, and incentive misalignments, all of which can contribute to increased transaction costs and limit the feasible set of policy options. Opportunities to address these problems by using digital tools exist along the “policy cycle”. The conceptual framework in this report can be used to identify where potential exists to make (increased) use of digital technologies to improve agri-environmental policies throughout the cycle.

Adoption of digital technologies by agri-environmental policy makers offers substantial opportunities to reassess and redesign existing policies. Recent technological developments have dramatically improved the cost-effectiveness of both in situ and remote sensors and changed the calculus of which policy type within the broad spectrum of policy options are the most effective and efficient. Increased spatial and temporal data resolution is allowing governments to act on their commitments to adopt “data-driven policy”, in particular by enabling:

• policy makers to better understand environmental impacts of agriculture and formulate policy objectives which more holistically capture these impacts;

• design of highly differentiated and targeted policies;

• new data-driven monitoring and compliance systems; and

• improved ability to measure risk and manage uncertainty.

Further, new technological solutions to preserve privacy while increasing access to data can allow governments to become more open and to increase the availability of data for policy-relevant research, policy-making, implementation, monitoring and compliance, and evaluation. A combination of digital technologies can be used to underpin more inclusive policies promoting sustainable, productive agriculture.

However, digital technologies are not a panacea; they are a means to an end, and can create new challenges. The potential for these challenges to occur should be considered both up front, so that policy design can take them into account and mitigate them where possible, and during policy implementation, so that challenges can be addressed as they arise and digital tools can be refined. Key recommendations under thematic headings are below.

1.1.1. Making use of digital technologies in policy design and implementation

Digital tools can enable new information-rich policy approaches (see, for example, Case Study 1). Governments have the opportunity to reassess and potentially revise existing standards and regulations to ensure latest technologies can be included. Specific recommendations are:

• Governments should review environmental standards relevant for agriculture which refer to average concentrations or emissions over a particular period of time, to allow for point-in-time data and continuous monitoring as a supplement to or replacement for average parameters. Policies which address farming practices, often based on some form of technology standards, may be able to be reformed to use performance standards.

• Governments can potentially revise existing administrative service standards (e.g. commitments to process programme applications within a certain timeframe) in light of the ability to adopt time-saving and cost-reducing technologies (e.g. greater automation of administrative procedures, use of online platforms and e-services for payments)

High resolution earth observation data, as well as and improved data on a wide range of agricultural and environmental variables, paves the way for more nuanced, targeted agri-environmental policies, even over large spatial scales. However, knowledge gaps remain (and likely always will to some degree), and a combination of tools may be necessary. There is also still an ongoing need to improve scientific understanding of complex physical processes. In addition, economic considerations (e.g. costs and benefits of investments to improve understanding) also need to be taken into account. Specific recommendations for using digital technologies to implement more targeted policies are:

• Policy decisions still should be made based on a holistic consideration of benefits and costs, not simply on the basis that a policy option has, with digital technologies, now become technically feasible.

• Governments considering implementing spatially-targeted and result-based programmes should consider using digital tools, recognising that there is a role for both digital data collection (sensor technologies) to measure results directly and for digital analytical tools (particularly agri-environmental models).

• Pilots for testing targeted and results-based programmes should explicitly aim to evaluate the cost-effectiveness of using digital tools (including the data that digital tools generate).

Adoption of new digital tools for policy risks creation of a “digital divide” between those who can access or use the tool and those who cannot. Also, the production of new knowledge available to certain parties (e.g. service providers) but not to others (e.g. service users) can inadvertently create new information asymmetries. Adoption and design of policy tools should recognise these risks and mitigate them by taking the position that digital policy tools and related data should in principle be as open as possible, with restrictions on access being clearly justified.1 To maximise both the ability of users to use such digital tools correctly, and for digital tools to link together, the design of digital tools should include development of user guides, training and interoperability features.

Use of digital technologies for policy purposes is often approached on an ad hoc basis; for example, decisions about digital technologies are often made at the level of individual policies or programmes rather than at an organisational or whole-of-government level. Government agencies should evaluate opportunities systematically, even if actual use of given technologies remains only for specific purposes. The case for creating new digital tools also needs to consider whether existing tools can be improved, and also how digital tools work together with other tools. A coherent approach can help ensure that initiatives generate additional benefits by using a mix of old and new technologies and provide for multi-dimensional integration of digital tools (e.g. interoperability between digital tools, integration of digital tools with other tools) to ensure efficiency and effectiveness.

1.1.2. Using digital technologies can improve monitoring and compliance for agri-environmental and agricultural policies and programmes

Remote sensing and related technologies offer the potential to drastically reduce the cost of monitoring efforts to improve agricultural sustainability. Digital technologies can also be used to move toward more collaborative approaches which encourage proactive participation of farmers in the overall monitoring procedure.

In fact, the relative ease of monitoring certain kinds of actions or environmental impacts using digital technologies may motivate a shift towards them in policy design on these actions or impacts. However, such changes should be carefully considered: policies should generally not limit farmers’ actions to only those which can be easily monitored by digital technologies, as this may constitute a de facto technology standard which limits farmers’ options for becoming more sustainable. Rather, policies should continue to be evaluated based on their total costs (and benefits), not only transaction costs of monitoring.

In voluntary policy contexts (such as voluntary agri-environmental programmes), administrators may face a conflict between short-term goals (ensuring compliance with current programme requirements) and long-term goals (encouraging re-enrolment). Governments should explore options to circumvent this dilemma, which could include:

• more flexible, digitally-enabled compliance approaches which focus on monitoring and helping farmers learn how to comply, rather than an audit-and-sanction approach;

• making changes to policy design in order to foster improved compliance in future, which could include design elements such as:

  • a greater focus on long-term results;

  • making use of technology to design schemes which only pay once compliance is demonstrated (e.g. via geo-tagged beneficiary-provided photographs, remote sensing);

  • use of market-based instruments where famers are paid for ecosystem services and compliance is managed via market contracts;

  • designing flexible requirements which “follow nature” (e.g. mowing dates), which fosters alignment between short- and long-term objectives by not unnecessarily restricting farmers’ choices.

Data publication, reporting or transparency requirements can be an effective policy tool for incentivising compliance even if the result is that the data is never actually reported to or used by the government except in cases of non-compliance. Data transparency requirements can be an important component of self-auditing, self-reported-compliance, and collective compliance mechanisms.

1.2. Governments should champion efforts to improve access to agricultural data

Micro-level agricultural data (for example, farm level or field level data) is needed for evaluating the effectiveness and efficiency of agricultural and agri-environmental policies, as well as for developing new, tailored services for agricultural producers. Governments have a key role to play to improve access to agricultural data, including the ability to link datasets, while preserving confidentiality where needed. Specific recommendations are:

• Government statistical agencies, administrative agencies (e.g. paying agencies for voluntary programmes) and regulatory agencies (e.g. environmental regulators) should increase their interaction and explore ways to pool data. They should also work together with data providers and data users to establish a clear framework governing data access.

• Governments should investigate how administrative data can be re-used to support: 1) agricultural and agri-environmental policy implementation; 2) policy-relevant research; and 3) services to farmers. Governments should formulate clear policies for access and use of administrative data which take into account both the benefits and risks.

• Improving access to agricultural micro data held by governments requires a coherent, tiered data dissemination strategy. The recommended approach is as follows:

  • Take a risk-based approach to allowing access to agricultural data held by government: that is, consider and clearly articulate reasons why specific data or classes of data cannot be openly provided, including identifying the magnitude of potential harm and the likelihood of risks eventuating. This could be accompanied with commitments to periodically review pre-existing legislative requirements to protect confidentiality of agricultural data.2

  • Invest in data services such as providing linked datasets to increase the usefulness of government data collection. One important aspect of this is to link farm financial datasets with physical data such as soils, precipitation, and other climate variables. Governments should also consider how provision of government-held data interacts with datasets from other sources.

  • Increase use of secure remote access mechanisms allowing trusted researchers to access agricultural micro data.

  • Explore greater use of new technologies (such as “confidential computing” and other advances in encryption) that avoid the traditional confidentiality-accessibility dilemma.

• Data-collection agencies should explore how the burden of existing data collection by government organisations can be lessened while maintaining or strengthening data collection through the use of digital technologies, including considering how digital tools could be used to gather data via alternative pathways; they should also put in place data management frameworks which include methodologies for the evaluation of data quality for data from alternative sources and planning. Finally, government might have a role in ensuring the longevity and robustness of these data sources.

• Governments should explore ways to incentivise provision of private sector data for public use and for agricultural research. This should include consideration of providing incentives for farmers to allow their data to be shared for policy purposes; options include monetary incentives (i.e. payments for data provision) and non-monetary incentives such as provision of regulatory safe-harbours for data providers or provision of services which use data that has been provided (e.g. benchmarking services).

Issues related to the treatment of data are critical not just in the context of the use of government-held agricultural data to improve agri-environmental policy, but form part of the broader debate about how digitalisation can be used to create value in the food system. For this reason, the study also takes a broader look at the issue of data and data governance in agriculture. While a full consideration of all of the regulatory aspects conditioning the use of digital technologies in the agriculture sector is beyond the scope of this report, some key findings and recommended “first steps” are identified towards ensuring that the regulatory environment, notably in relation to data and data governance, provides protection where needed, while not stifling innovation.

1.3. Data infrastructures and data governance for agriculture: Potential roles for government

The capacity to create value in the food system using digital technologies depends on: 1) access to basic connectivity infrastructure (broadband, telecommunication services); 2) a range of data collection, storage and analysis services (sensors, modelling, digital platforms, cloud-based storage and processing, software systems for managing and processing data to yield actionable insights); and 3) the regulatory environment (the soft infrastructure representing the institutional environment defining interoperability rules, data quality standards, norms or regulations on data ownership and data privacy).

The options for governments partly depend on the state of these existing infrastructures. Within the same environment, governments might adopt different roles, from a central planner to an enabler, an investor or a regulator. Governments can potentially support the development of a data infrastructure in agriculture in the following ways:

• As a regulator, the government can create an environment enabling private sector investments and competition, for example by setting interoperability standards. More broadly, governments may need to consider issues in relation to the collection, use and sharing of data and other related regulations, as well as issues in relation to trust, whether in the use of data or in the technology.

• As an investor, the government can support connectivity and the development of a physical data collection infrastructure (sensor network, remote sensing, direct development of the data infrastructure and creation of markets for usage rights) and the development of innovative services.

1.3.1. Governments can play an active role in future development of digital tools for policy and for agriculture more broadly

Governments can actively support development of digital tools for agriculture and for better policies in a number of concrete ways. These include:

• Governments can undertake regular horizon-scanning exercises to ensure they remain up-to-date with new digital tools.

• Governments, in their role as users of technology, can make their user requirements clear to technology developers, and consider use of co-innovation models to ensure that technology developments both meet users’ needs and that users are challenged to re-assess their needs in light of technological developments.

• Governments, in their roles as (co-)providers and leaders of technology development, can invest in relationships with academia and technology developers working in emerging technology areas, particularly in the field of sensor development, and work together to ensure technologies are validated and calibrated for use in policy or regulatory contexts. Governments should also engage with researchers who work with agricultural data to conduct policy-relevant research, to maximise the use of such data for policy.

• Use of technology for policy purposes may incentivise adoption of technology on-farm. This can be beneficial; however, there is the potential for net increase in regulatory burden on farmers if government policies push farmers to adopt technologies by requiring them to satisfy mandatory regulatory requirements, when there is no net benefit to farmers. As in general, policy makers should carefully evaluate whether any expected net increase in regulatory burden is justified. Governments should endeavour to ensure technology adoption does not become a force for exclusion rather than inclusion.

Notes

← 1. Open data refers to the possibility of citizens to access data, however it does not mean that data is necessarily visible by all. Privacy and trade secrets still prevail and cryptographic keys are used to control access to such data. These are particularly popular in the public sector, with open government data, and with the scientific community as a solution to promote enhanced access to and use of data.

← 2.  Note that this recommendation does not presume that an open data approach will be appropriate in all cases. Rather, it is recommended that governments consider the possibility of opening datasets as a useful conceptual starting point so that the case for confidentiality requirements can be appropriately (re‑)evaluatced and transparently made.