Empowering farmers with digital agriculture.
Smallholder farms support more than two billion people worldwide, but many rely on inefficient and environmentally unsustainable agricultural practices. Small changes in agricultural practices can substantially improve productivity and profitability. However, offering farmers standardized agricultural advice has limited effectiveness due to variation in local conditions and farmer characteristics. Traditional extension systems have been unable to incorporate and disseminate this information to farmers, in part due to the high costs of operating in rural areas.
We work to provide farmers with technological innovations
In developed countries, precision agriculture technologies are transforming agricultural production by allowing farmers to better target inputs and management decisions to local conditions. In developing countries, most precision agriculture technologies are beyond the reach of most farmers. However, several technological innovations have created new opportunities to provide customized information to farmers:
- Mobile soil analysis labs with spectroscopy improve access to high quality soil data
- Satellite and drone photographs enable data collection and validation from above
- New weather prediction models generate real-time estimates useful to farmers
- Widespread mobile phone use facilitates information delivery and collection
These technologies can be combined with the best available research to improve information content and messaging effectiveness:
- Behavioral economics can improve messaging and encourage adoption
- Social learning theory can facilitate the diffusion of relevant information
- Big data and machine learning allow for personalized advice
- A/B tests allow near instantaneous upgrades
- Randomized controlled trials (RCTs) make for more rigorous evaluation
PAD harnesses these innovations in technology and research to improve the lives of smallholder farmers. We are taking ideas from precision agriculture in developed countries and adapting them to the needs and constraints of farmers in developing countries. Because individual farmers are often not able to invest in data collection and experimentation themselves, PAD brings this customized information to farmers’ fingertips.
We work with a model
PAD is a non-profit organization with a mission to support smallholder farmers in developing countries by providing customized information and services that increase productivity, profitability, and environmental sustainability.
We are working on a new model for agricultural extension: reaching farmers with personalized agricultural advice through their mobile phones. We implement this model in collaboration with partner organizations and governments and gather evidence on its impact. We aim to improve the lives of 100 million farmers in developing countries with our services and support to existing systems.
Using two-way communication and information aggregation, we offer farmers useful information customized by geography, market, and farmer characteristics. As farmers realize the benefits of this service, they have incentives to contribute accurate information into the system that will improve our recommendations over time. We incorporate insights from behavioral economics and social learning theory and make use of A/B testing and machine learning techniques designed to identify what types of information and delivery mechanisms work best for farmers.
Our model is to impact the lives of farmers through two channels:
- The PAD Lab is where we design and operate a service for farmers, either as part of a research pilot or an on-going operation. These spaces serve as a “sandbox” for us to rigorously test ideas while at the same time providing a valuable service to the farmers we serve. We currently have labs in both India and Kenya.
- The PAD Partnership model is how we scale the ideas that work. Here we partner with governments and organizations with a shared vision of building, operating, and evaluating a service to farmers. We lend our expertise to co-develop these systems, to perform data analysis, to design pilots and experiments, and to offer advice on system improvements. We currently work with partners in India, Kenya, Pakistan, Rwanda, and Ethiopia.
- Africa | East
- Africa | Middle
- Asia | Central
- Asia | South
India, Kenya, Pakistan, Rwanda, Ethiopia.