⇓ More from ICTworks

New USAID Insights: Digital Profiles of Smallholder Farmer Data Management

By Wayan Vota on December 17, 2018

smallholder farmer profiles

More than 500 million smallholder farms worldwide play a significant role in food production and the genetic diversity of the food supply. Until now, it has been difficult to get information to or from smallholder farmers, compounding basic infrastructural problems such as access to inputs, markets, financing, and training.

The spread of mobile technology, remote-sensing data, and distributed computing and storage capabilities are opening new opportunities to integrate smallholder farmers into the broader agri-food system. The scale of these changes holds out the potential for another agricultural revolution.

As mobile technology use increases and improves in rural areas, the paradigm is also shifting for how smallholder farmers are profiled, how their needs are understood and met, how the impact of agricultural services is measured, how farmer data is shared, and how a global body of knowledge can be built by drawing on typically siloed expertise and data.

Smallholder Farmer Landscape Assessment

To help describe this shift in farmer profile data management, Grameen Foundation conducted a landscape assessment that:

  • Documents experiences in managing digital farmer data by describing how smallholder farmers are defined, the types of service providers that collect farmer profile data, how data is collected, analyzed, and used to support smallholders with products and services, and how this data is shared and managed.
  • Highlights innovative models of smallholder farmer data management and sharing to inspire new thinking among actors in this space.
  • Outlines key considerations when assessing existing or investing in new efforts to develop and leverage farmer profile data.

Over a three-month period, Grameen Foundation conducted a desk review of the existing literature, including peer-reviewed journal articles, project and program reports and presentations, blogs, and information provided on websites.

Grameen Foundation also conducted approximately 50 key informant interviews with service providers, including mobile network operators (MNOs), agribusinesses, government, research firms, technical assistance providers, donors, and other actors. These service providers were assumed to provide a valid representation of current farmer data management practice.

Grameen Foundation also participated in the ICTforAG 2018 and Data Driven Agriculture: The Future of Smallholder Farmer Data Management and Use workshop in summer 2018, the latter organized by USAID funded and FHI 360 lead mSTAR project, to gather additional input from technical specialists in the area.

This landscape assessment was meant to capture different contexts and stakeholders but not to be exhaustive. The insights collected are meant to guide development organizations, USAID, and other donors in using these models in their everyday operations or in project design.

Smallholder Farmer Assessment Findings

farmer data collection phases

Understanding smallholder farmer data management requires defining from whom data is captured and how it is captured, analyzed, used, and shared. The findings from the assessment revealed:

  • Defining a smallholder farmer is not easy; farmers are not homogeneous.The definition of a smallholder farmer must be flexible to include particularly vulnerable people.
  • Given there can be several farmers per plot of land, when aggregating data for either open data efforts or for sophisticated analytics, it is the farm itself that “pulls” data together. The farm is the common denominator, not the farmer, for aggregating data.
  • Service providers who capture data from, about, and for farmers are a diverse group.The type of service provider involved does not necessarily determine what data is collected or how it is used, but it is an important starting point.
  • New ways of collecting and aggregating data and applying analytics—such as predictive, prescriptive, and cognitive analytics—can reduce the amount of direct input needed from the farmer. Data analytics is a game-changer and is being used to create “new data” from existing data.
  • Digital technology is now facilitating the sharing and management of farmer profile data in real time.
  • Marrying plant science data with real-time farmer data is a new frontier for improving farm productivity.
  • Service providers win or lose depending on how they use their data. Service providers and farmers should not treat data as just a resource but as an asset and should consider opportunities to monetize data. Smallholder farmer data is giving rise to new configurations within service provider business models.
  • There is no single pathway to sophisticated use of farmer profile data. How service providers use and manage data in combination with the data capture methods and data analytics determines how innovative their model may be.
  • When service providers consider new farmer profile approaches, they should start small and take manageable steps.

This assessment has also revealed that most of the data and the technology (hardware and software) already exist to solve many constraints that farmers face, but the solutions are fragmented and not all service providers—or farmers—have equal opportunities to access them.

The Future of Smallholder Farmer Digital Solutions

farmer digital solutiuon hype curve

Big data promises to bring fragmented data, resources, and service providers together to support the farmer ecosystem. There is no better time than now to strengthen farmer ecosystems with advancements in technology that can facilitate the sector’s ability to:

1. We can clarify farmer data we have and we need.

How many of the same farmers are asked the same questions over and over by different service providers and how many are left out? How many women or other vulnerable groups are left out? It is hard to design for and service the needs of people if you have no information about them.

Blockchain and mobile phone ownership may give visibility to people who need to be included. Practical data management barriers prevent true open data sharing. Until these are solved at both the macro and micro level, disjointed data collection efforts resulting in stovepipe repositories and farmer fatigue will unfortunately remain the norm.

2. We can marry plant/animal science with human science.

Plant and animal science research is crucial to increase yields and improve animal health. Organizations such as CGIAR have abundant scientific insights relevant to smallholder farmers.

In addition, the aggregation of information from a farmer’s profile, remote-sensing data, satellite data and weather data makes it possible for farmers to make decisions at critical moments. Data analytics that pull data from multiple services can be used to provide timely, individualized information based on the farmer’s and the environment’s current and predicted conditions.

3. We can link the farmer with the full agricultural ecosystem.

Markets themselves are underdeveloped.Access to agricultural financing has been historically limited.While lack of data is not the only reason for poor markets or limited access to financing, it is an important one.

Buyers do not have information on smallholder farmers and neither do many financial institutions. Data on farmers’ harvests and productivity creates this visibility for other stakeholders in the value chain; data analytics can also directly link people to markets and financial services.

4. We can be precise.

Many service providers and projects that have begun to integrate technology writ large have been able to show cost-efficiencies in their service delivery and demonstrate impact. If a farmer had a better market, an agricultural loan, and an agriculture extension agent that showed up every day, would that improve his/ her yield? Likely so, but would this be sufficient in the face of environmental, physical changes?

Precision has been missing. More is required than information about the farmer and about predictable behaviors; “smart information” is needed to help inform choices during unpredictable circumstances. Farmers need to understand the tradeoffs of different financial decisions such as “If I use this amount of fer tilizer that costs me this much, what will my yield be? Which market has the best price today?”

Farm development plans and other tools that model these circumstances help farmers make more informed decisions based on their own financial situations. Such precision may better support a smallholder farmer who has no room for financial error; he or she may find it worth the money to pay for such services.

All the pieces are there for supporting data-driven agriculture.The challenge is to bring the pieces together for the benefit of the farmer and the world he or she is expected to feed.

Filed Under: Agriculture
More About: , , , , , ,

Written by
Wayan Vota co-founded ICTworks and is the Digital Health Director at IntraHealth International. He also co-founded Technology Salon, MERL Tech, ICTforAg, ICT4Djobs, ICT4Drinks, JadedAid, Kurante, OLPC News and a few other things. Opinions expressed here are his own and do not reflect the position of IntraHealth International or other ICTWorks sponsors.
Stay Current with ICTworksGet Regular Updates via Email

2 Comments to “New USAID Insights: Digital Profiles of Smallholder Farmer Data Management”

  1. Ehud Gelb says:

    Dear Mr Vota
    I found this paper very interesting.
    How can I communicate with you?
    ehud.gelb@mail.huji.ac.il
    Thanks