Paving the Way for Data-driven Agriculture: Who's Your Farmer?
Posted on 09/27/2018
Posted on 09/27/2018
Who’s your farmer? This sounds like a simple question for any agricultural intervention, but it is fraught with complexity, especially for those of us who are trying to support women through agricultural programs. Why is that and why does it matter?
Recently, I visited the Ghana-based research team for our Sat4Farming project, which is a collaborative effort of Grameen Foundation, Rainforest Alliance/UTZ, Touton, Satelligence, Waterwatch Cooperative, and the University of Ghana. Sat4Farming uses a digital farm development plan to provide cocoa farmers with detailed information on their farms, such a profit and loss statement, and helps guide their investment decisions. Starting next year, satellite capabilities will enable us to monitor productivity and provide remote-sensing data from the farms.
As with any research project, we must define our sample. Who should we interview? Using the project-level Women’s Empowerment in Agriculture Index (pro-WEAI) requires us to interview a man and woman from the same farming household. The pro-WEAI measures how empowered the interviewed women are as a group and as individuals compared to the men in their households. (Here is an example of where pro-WEAI has been used.)
This sounds simple, but for starters, how do we define “farmer”?
Earlier this year, I led a research project on behalf of Digital Development for Feed the Future (D2FTF) to develop a landscape assessment on the future of farmer profile data. The assessment aims to describe how technology is changing how we capture data (from farmer, satellite, other data sources), how we analyze and use that data, who owns the data, and how new business models are based on data as a core asset.
One immediate challenge outlined in the landscape assessment was establishing a shared definition of “smallholder farmer.” Despite a general perception that smallholders had very little land (less than 2 hectares, for example) we found there was no real shared definition. It depends on the context, and thus, the size of land can vary. Some base the definition on the land’s profit potential, while others define a farmer based on their methods of targeting, such as through farmers’ associations or other groups.
But one interview revealed a new concept that stood out to us: In the process to digitize farming data, the farmer is no longer the centralized anchor for our data. It’s the farm. The farm—or the plot—is the unit of analysis that aggregates data on the people who work on the farm (i.e. the farm owner, his family, caretakers, day laborers, etc.). You can link weather and satellite data to the plot. You can link profit potential to the plot (How much land is there to plant? Where is it located? What are the soil conditions? How can we sustainably intensify agriculture on that plot?).
This was tested on my recent trip to Ghana when we evaluated potential interviewees for the research. Our partner, Touton, bases a lot of its agricultural extension support on who owns the land because ultimately, this person is likely making important decisions about how that land is used. So, the digital farmer development plan is targeted at farm owners. But this farm owner may live in the capital city, Accra—a mere six-hour drive from the farm—and he may have a caretaker (likely a man) who lives on the land and does most of the labor along with other members of his family, such as his wife and children. Our challenge is then who should we interview and base our decision on for the digital farm development plan? The landowner? Or perhaps the day-to-day caretaker that receives the one-on-one agricultural extension support and likely has been given the authority by the landowner to make routine decisions?
When you introduce the role of women in cocoa farming households, it becomes even more complicated. Our preliminary research found that while very few women are considered the “primary farmer,” they play important roles in activities that are most critical to the quality of the product: drying and fermenting the cocoa beans. Sometimes women attend community-level trainings provided by Touton. Sometimes they are at home when the Touton agronomist comes to monitor progress on the cocoa farm; the agronomist may also include them in the direct services provided to the farm, but this is more likely to be by chance. Sometimes the woman owns the land and may be considered the “primary farmer” but her husband is still the one who meets the cocoa buyer when the beans are purchased and receives the income. So, who is your farmer now?
There is something simple about the idea that digitization can cut through this complexity by anchoring data to a plot (and not to the farmer). The plot is the stage upon which different actors meet. Some days their roles are clear, some days it’s more like improvisational theatre. We need simplicity, so we can get distinct measures, and capture the actual roles of people on the farm. But there is also something very risky about trying to oversimplify our definitions of a smallholder farmer. Maybe we should rid ourselves of the idea that there is an idyllic picture of the husband farmer and his wife, and recognize that multiple people are connected to what happens on a farm. Each person on the plot has a role. They have similar and also separate needs. Viewing one farmer as the efficient representative of the plot and providing support to that farmer only dismisses the many actors that contribute to agricultural productivity. We can no longer afford to do that. A key place to start is by finding a way to collect data from other voices on the farm.
On October 2, at the SEEP conference, please join us to continue this dialogue around collection and management of farmer data at the session, Data-driven Agriculture: The Future of Smallholder Farmer Data Management and Use. I’ll be joined by colleagues from Grameen Foundation, aWhere and IFPRI to talk about how different types of service providers see both opportunity and challenges in how we collect data from or on the farmers we’re serving.