Data analytics is a growing trend across all industries, making it an essential part of improving business operations and decision-making. A multitude of forms of data enable companies to understand and anticipate customer needs, gain insights into new geographies and customer segments, optimize resources, and make better decisions.
The agricultural sector is no different when it comes to the use of data analytics. The sector has seen an increasing use of digital solutions such as precision agriculture, blockchain technology and IoT to capture, facilitate, analyze and enable decision making on various activities along the supply chain. These solutions drive a shift towards improving crop yields, mitigating the effects of climate change, increasing efficiency in resource use, and aligning with consumer demand in agriculture.
The current state of data ownership and governance in agriculture
There are more than 500 million smallholder farmers worldwide, who play an important role in food production and supply. These smallholder farmers generate and can collect data on soil health, seed and fertilizer use, time taken to complete field operations, production practices and irrigation data. Data generators or service providers such as research institutes, governments/NGOs and commercial/corporate service providers are also increasingly capturing this data, either through direct interaction with farmers or using mobile phones and/or remote sensing technologies to develop digital farmer profiles.
Some of these profiles contain comprehensive data, which is made accessible – sometimes on a commercial basis – to several service providers, such as input suppliers, financial institutions, agro-processors, government agencies and agricultural cooperatives. . Service providers can also develop products and services by conducting data analysis to provide farmers with better inputs, fast and low-cost access to finance, and effective price discovery. However, this increase in data collection, storage and use has raised concerns about the ownership and governance of farmer and farm data. Questions remain about who decides how this data is used and shared, who benefits financially from this data, and what rights farmers have to access, delete and control data about them and their farmers that is held by some thirds.
Challenges Smallholder Farmers Face in Data Governance and Ownership
Many smallholder farmers face capacity constraints to fully utilize the data collected from their agricultural activities. There are many reasons for this, but some of the main ones include insufficient regulatory guidelines on data privacy and security, lower level of literacy, insufficient knowledge and awareness on how their data is stored and used by service providers, and a lack of farmer-centric guidance. data governance models. In addition to capacity challenges, smallholder farmers also face data ownership and control issues, which impact their willingness to adopt digital solutions. According to the GFAR study “Farmers’ rights to data, information and knowledge”, access to information is mainly limited to large farmers and service providers. Although most of the data is generated by smallholder farmers, it is usually collected by government agencies, research organizations, NGOs, financial institutions and development organizations. Since agricultural data is often sensitive and not something farmers are willing to share, they may be reluctant to share some data, particularly if that data will then be used and potentially owned by another party. This can put them in the position of having to give up access to useful digital services unless they are aware and willing to trade their data to access them.
Given these challenges, there is an immediate need to design data governance and ownership frameworks or processes that put the needs of farmers at the center. Putting policies in place around governance and inclusion will also drive the adoption of innovative, farmer-friendly data analytics solutions in the agricultural sector, thereby improving livelihoods and increasing incomes for smallholders. while also benefiting service providers and other actors in agriculture by creating a fair environment. and a competitive market for the provision of services.
Some ways stakeholders are addressing these issues
Overcoming issues related to data governance and ownership requires a multi-pronged approach from all relevant stakeholders, including research institutes, policy makers, donors and development organizations, businesses and organizations. data collection and analysis companies. Some well-known initiatives undertaken by organizations around the world include the National Farmers Federation Voluntary Code of Conduct, the Australian Agricultural Data Code, the EU Code of Conduct on Sharing Agricultural Data by Contractual Agreement and the US Privacy and Security Principles for Agricultural Data.
In addition to developing codes and principles, some regions are also forming agricultural data cooperatives. These farmer cooperatives pool and store member data and allow the organization to control the flow of data. Farmer data cooperatives include Ag Data Coalition, Grower Information Services Cooperative and the Farmers Business Network in the United States, and JoinData, a Dutch data cooperative.
Some non-profit development organizations and development agencies have also designed programs that allow farmers to interact with their data. For example, “FarmStack” from Digital Green is a free open source software for data exchange to share data directly and securely without any third party involvement. It also gives users full control over the data. Digital Green uses FarmStack to create a secure marketplace for selling agricultural products in India and Ethiopia. Feeding the Future Ghana Agricultural development and value chain improvement (ADVANCE II)which was implemented by ACDI/VOCA, used innovative and locally sourced farmer identification smart cards owned by the farmer, which were shared with the consent of the farmer.
Some private actors are also using technologies such as AI and blockchain to allow farmers to store their own data on a secure distributed database. For example, Farmobile, a US-based agricultural data collection and software provider, has developed an ownership framework that governs ownership of agricultural data and exercises control through a legal agreement that stipulates who can modify and access this data. The Farmobile DataEngine platform provides data ownership rights to farmers through which they can keep their data with themselves or share it with service providers or advisors and can also monetize it. Similarly, Conservis, a software-based farm management service provider, grants data ownership rights to farmers. The company can only share farmers’ data after they have given permission.
With the increasing pace of technological advancements in the agricultural sector, data at different stages of the supply chain will become even more critical for planning and decision-making. Therefore, there is a need to have a multi-stakeholder discussion on data governance where each stakeholder shares their concerns and suggestions in order to build a common vision for the consistent implementation of existing data practices and policies across areas. geographical.