How Digital Technologies Can Drive Food System Transformation

New technologies like remote sensing, digital advisory services, and digital financial tools have the potential to dramatically transform agricultural value chains in low- and middle-income countries (LMICs). But are these countries able to truly take advantage of this potential? Not without further investment, says a chapter in the recent book titled Science and Innovations for Food System Transformation.

Chapter 22, “Food system innovations and digital technologies to foster productivity growth and rural transformation”, highlights the opportunities posed by digital technologies. These powerful tools can help better connect farmers to markets and financial services, enhance agricultural knowledge and expertise, and provide more robust, up-to-date data to better drive everything from private sector investments to government and NGO development programs. When digital technologies are used effectively, the result is often a more productive, inclusive, and sustainable food system.

Unfortunately, the chapter goes on to emphasize, LMICs often lack the proper enabling environment, as well as the needed capacities, to fully realize these opportunities. While larger middle-income countries like Brazil, China, and India have ramped up their public sector investments in agricultural research and development (R&D) and capacity (both human and institutional), similar investments in LMICs continue to lag behind, and what investments are made in these countries tend to be smaller and less effective than those made in higher income countries.

The chapter separates countries into three groups: those with poor research systems (“lagging”), those with average research systems (“average”), and those with advanced research systems (“advanced”). LMICs overall fall within the “lagging” and “average” groups.

Lagging LMICs spend only around USD 0.7 per person in total government spending 2011, compared to USD 1.95 in countries in the advanced group; of that, only 3-6 percent went toward agriculture. This translates into extremely low investments in agricultural R&D, such as new digital technologies.

In terms of human capital capacity, only around 17 percent of agricultural researchers in countries in the lagging group hold PhD degrees, compared to 27 percent in countries with advanced research systems. In countries in the average group, a large proportion of qualified researchers are nearing retirement age, which will lead to a further lack of human capital, particularly in Africa south of Sahara.  

Finally, LMICs’ ability to take advantage of the opportunities presented by digital technologies is hampered by a lack of high-quality research institutions. In both lagging and average countries, this institutional capacity gap is driven by a combination of policymaking structures, small economies and/or agricultural sectors, and limited human capital.  

To address all of these constraints, the chapter’s authors recommend a combination of global, regional, and national actions.

Globally, IP companies and other key digital players will need to engage more strongly with agricultural research institutions in LMICs to enable more cost-effective access to IP agreements, data, and apps and digital platforms. In addition, high- and middle-income countries with more advanced research systems will need to strengthen their cooperation with LMICs in order to promote learning and capacity-strengthening. This includes the growth of North-South and South-South collaboration.

At the regional and national levels, one of the most basic actions to be taken is to increase investment in digital infrastructure, particularly in rural areas. Farmers and other agricultural value chain actors can only take advantage of the power of digital technologies if those technologies are accessible and affordable.

In addition, national and regional policymakers will need to invest in adapting digital technologies to their local contexts to make these powerful tools more accessible to poor farmers and small businesses. Local contexts also need to be considered when addressing regulatory constraints in order to create more equitable and functional enabling environments. Such an enabling environment should also include an emphasis on cooperation among agricultural R&D actors to close LMICs’ institutional capacity gap.

Emphasis on and investment in education geared toward research, management, and business development should be prioritized by national and regional policymakers to help LMICs develop the skilled workforce needed to take advantage of digital transformation. In addition, policymakers, NGOs, private sector companies, and other stakeholders should also invest in improving the capacity of farmers, processors, and others along agricultural value chains to use digital technologies effectively.