Big Data, ICT, & The Future of Smallholder Farming

Transforming Data into Action

This year’s ICT4D Conference in Kampala, Uganda explored the ways in which information and communication technology (ICT) are enhancing program quality, improving decision-making, increasing impact, and accelerating progress toward the UN’s Sustainable Development Goals across many sectors. The discussions around digital agriculture showed that the true power of agricultural data comes when it is placed in the hands of people who can take action: Data becomes intelligence!

How can we bridge the gap between big data analytics and delivering context-specific information to farmers?

ICT solutions can help bridge this divide particularly as civil society and public sector entities increase their use of digital tools such as field tablets, smartphones, etc. The increased availability of modern technology for agricultural extension agents allows for greater delivery of localized, actionable data to farmers. Use cases of big data in agriculture include, but are not limited to: 

Advisory services at farm level

Market intelligence & Commodity pricing

Financial services (e.g. drought-based insurance)

Bundles of services that include weather and agronomic tips, financial services

Early warnings of pest and disease outbreaks

Early drought detection and warnings for food security

Each of these can build a farmer’s resilience to climate change and allow for more effective, informed decision-making by governments and policy-makers.

Challenges of ICT for Smallholder Agriculture

Data-informed farming requires sending quality information to smallholder farmers through agricultural data ecosystems, but currently, agriculture is operating in a data-impoverished environment. Critical datasets, such as aWhere’s weather data, are breaking this barrier down. We not only deliver premium, localized, real-time weather data and insights to farmers and decision makers, but also training for scientists, agronomists, and analysts on using analytical tools (R & QGIS) and interpreting ag-weather data so they can provide relevant and accurate information to the farmers in their area.

The adoption of digital services in agriculture has been slow largely due to the rural and remote nature of smallholder agriculture and the lack of ICT channels that reach these areas (e.g. tablets, smartphones). Additionally, many platforms need to be developed for offline use and while connectivity is becoming less of an issue, civil society and public sector actors must invest in and support robust data infrastructure & technology to promote sustained use. A more diverse set of actors in the digital agriculture space (private, public, and civil society actors) is needed to create symmetrical approaches in order to progress digital agriculture forward.


aWhere recognizes the need to integrate farmer-level data into all ICT solutions. Improving smallholder agriculture cannot happen without a deep understanding of the needs of the farmer.  We must focus on the farmer – without detailed farmer-level data, context-specific solutions cannot be implemented.

ICT solutions are weakened without the following:

Human-centered design of messaging services supported by baseline data at the farmer level to create accurate, targeted advisories and messages: Which type of information does the farmer want? What is their greatest challenge? What is their greatest success? Are they considered an early adopter, lagger, precommercial, commercial? Targeted information can be sent if farmers are categorized.

Inclusion of key intermediaries such as agriculture extension agents to reach the highest number of farmers

Local solutions such as positive deviants. For example, if everyone’s crops are failing but farmer A’s crops are growing, what is farmer A doing differently? How can we tap into that knowledge?

Understanding generational aspects of smallholder agriculture: For example, younger populations may be more interested in ICT solutions and may demand different types of data such as new techniques on pest management or global market price information

Digital literacy will vary and extension agents may be the key to breaking down the barrier to access to information

Ground-truthing agronomic messaging is also needed to improve content: Researchers are taking on this topic to better understand how climate information is used, particularly looking at how gender plays a role in how information is spread throughout a household

Opportunities for Big Data in Smallholder Farming

Technical advances in data storage and communications as well as computing power over the past few decades have allowed for the development of powerful tools that make the agri-food system more profitable and precise. But, how do we combat, and not create, inequalities within digital agriculture? Navigating digital illiteracy and avoiding unintentional consequences is a big challenge for digital development in all sectors. Data privacy and ownership protocols must be created to ensure farmers’ personal information is protected and aligns with national and international data management standards.

Big data and ICT4Ag can be powerful tools to help smallholder farmers confront, adapt, and build resilience to climate change by giving them access to data and information to improve on-farm decision-making. A recent study by GeoPoll of 18,000 farmers in Kenya showed that 50% of farmers surveyed say that climatic changes have impacted their yields. From sms messaging services to voice recordings, ICT channels can deliver powerful information to farmers, many of whom are impacted by climate change.

aWhere’s vision is to de-risk agriculture from increasingly volatile weather using data science to empower farmers and agriculture value chains to be more resilient, profitable, and efficient in providing nutritional security. The future of digital agriculture starts with better information to build economic resilience to climate change and aWhere is at the forefront of providing critical data inputs to be delivered via modern ICT channels.