Learning from innovative farmers: spotting agricultural development options that work locally

Jonathan Steinke
Jonathan is a research fellow with Bioversity International, working on digital innovation for agricultural advisory services. He is currently pursuing a PhD at Humboldt-University in Berlin, Germany.

Around the world, agricultural development organizations often struggle with surprisingly weak adoption of innovations that had previously been successful at other places. If all goes well, the smallholder farmers addressed by a development program readily adopt and adapt newly introduced practices, such as improved management of crops and livestock. Not so rarely, however, promising innovations do not fit with local culture, cause extra labor at times when the farmers are already extremely busy, or show other unexpected downsides in the new context.
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Avoiding locally unsuitable interventions and designing better agricultural development programs by working closely with the local community is possible, of course. But participatory research can take a long time, and results are sometimes biased towards the local opinion-leaders, who are not always the most successful farmers. Could there not be a simpler way to find out “what works” under specific local conditions?

A few years ago, I visited smallholder farmers engaged in “agricultural research committees” in Honduras. These individuals were certainly not average farmers. I still remember how impressed I was about their ingenuity and energy in pursuing small-scale farm experiments, constantly improving their production, and consequently, their livelihoods. There was no doubt these local experts held vast knowledge about agricultural development practices that are proven to work in their specific context, and which could be highly interesting options for other farmers in their communities.

This idea – that in every rural community, there are some creative and innovative individuals that can serve as models of development – is called “Positive Deviance”. Originally developed to identify good child care practices in Asia, the concept is quite simple: the grass isn’t always greener on the other side. And yet, somebody in the village has the greenest grass, despite facing the same challenges as others. So what can be learnt from that high performer? The idea is to first spot farmers with superior livelihood outcomes – household performance that “sticks out from the crowd”. And then, invite them to share their knowledge.

A positive deviant farmer from the Mtwara region, Tanzania

But how can we find such outstanding households? Enter RHoMIS. Sitting over a cup of coffee in Ethiopia in 2017, Mark van Wijk of ILRI told me about the astonishing diversity of smallholder households that is often found in RHoMIS datasets. Together with Jacob van Etten (Bioversity International), we speculated this diversity might help to identify specific farmers that were already engaged in innovative agricultural and livelihood practice.

We looked at a sample of over 500 farming households from southern Tanzania to find the strongest performers. But what is “performance” anyway? After all, farming is a whole way of life, requiring complex decisions about scarce household resources and competing goals. Farmers need to produce food, generate some income, and preserve natural resources, all at the same time. If our definition of “Positive Deviance” focused exclusively on the most productive households, that might lead us to practices with adverse implications, for example, for household income or the environment. To avoid identifying such unsustainable practices, we defined Positive Deviance by exceptionally strong “overall” performance in five key dimensions: food security, income, nutrition, environmental sustainability, and social equity. RHoMIS provides household-level indicators for each of these.

But does this approach not risk simply identifying the wealthiest farmers, with largest farms or best market access? By accounting for individual household resources, we put performance into perspective: our selection criterion was achieving better outcomes than other households with equivalent resource endowments. That is, Positive Deviance meant performing “better than expected”.

It turned out these households really had interesting practices to show. All in all, in ten days of fieldwork with 15 households, our interviews and farm visits revealed a list of 14 practices that plausibly contributed to their superior performance. The positive deviant farmers engaged in a large diversity of practices: from agronomic improvements, such as cereal-pulse intercropping, to on-farm businesses, such as a tree nursery, to off-farm enterprises, such as a private transport business or classic wage labour. Most importantly, all of these options clearly worked under local conditions. We believe that the results from this kind of research – a focus on Positive Deviance – can help to plan development interventions that are well-grounded in local smallholder context.
In our recent peer-reviewed study, published in PLoS One (open access), we draw three main conclusions:

• Positive deviant farmers were diverse with respect to resource endowments and livelihood activities. Thus, exploring their behaviours generated a wide range of locally viable household-level practices that can support agricultural development efforts in diverse contexts, addressing different needs.
  
• Identifying such locally viable practices does not require complex econometric modelling or extensive qualitative fieldwork. Rather, an efficient combination of quantitative and qualitative research methods makes the Positive Deviance approach scalable and accessible for local development agencies, such as NGOs.
  
• The performance differences between positive deviants and other households also indicated most-promising domains for development interventions. In the case of southern Tanzania, for example, our results suggest highest potential for improvements in food security and income. In contrast, improvements in nutrition and social equity seem harder to achieve without repercussions for other dimensions.
  

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