Start with the Soil
“It starts with good soil”, was what I heard from a farmer standing in intense heat, deep in the dry zone of northern Myanmar. He crumbled a fistful of it and smiled, “sheepshit, water, and crop rotation”. I thought back to the time and place where my obsession with food, farming, and development more generally became serious. Darina Allen, owner of the Ballymaloe Cookery School in Ireland where I worked briefly, would say something similar to her students on their first day. Holding a fistful of good earth she would implore them to let the soil fall through their fingers, to feel the condition of it. “It all starts with good soil”, she would say. “The food we eat, the pleasure it gives you, your ability as a cook, all of it starts with this good earth”. A million miles from east Cork, in a place that could not be more different, those words rang true once again.
Good soil is the start of good agriculture and without good agriculture everything else goes away. For the past month, the Future Sense at IDEO.org team has spent time with farmers, traders, experts, and academics in Myanmar, Tanzania, Malawi, and Kenya, and we have, variously, been able to draw upon our own experiences from years of work done in agriculture around the world. From our work, a central question has begun to emerge. What are the decisions that a farmer can take to ensure maximum productivity over the long term? That is, can we optimize for yield, while ensuring the future productivity of soil?
We are becoming obsessed with the decisions that can be taken to optimize yields over the long term. Optimization is often a dirty word. We associate it with maximized short-term gains or the perverse concept of maximizing shareholder value. In agriculture, maximized short-term gains are often disastrous. For sure, they deliver an income boost in the immediate term but often that boost comes at the expense of the health of the soil and local ecosystem, and ultimately, cost farmers money in the long-term. We have only to look at green revolution farming practices or the agricultural appropriation that came with modern industrial farming techniques to understand that there are both objective and culturally subjective nuances to farming that must exist within the idea of universal yield maximization.
There are myriad reasons for farmers to take suboptimal decisions and, lots of the time, a perverse supporting ecosystem renders those decisions rational. There could be a political environment that prioritizes short-term thinking — farmers might be incentivized to help a political party achieve its election promises. There may be limited access to the appropriate inputs — farmers may have no choice but to purchase intensive seed and fertilizer types. There may be a lack of extension support to best advise farmers on new techniques and keep them updated on real time conditions. Some farmers don’t want to optimize yields, they just want to farm and that is just fine. And on, and on, and on.
With those systemic issues in mind, there do still exist a set of decisions that when taken at the appropriate moment during a crop cycle should ensure for optimal yield and soil health. While we are not yet at a point of mapping fully the knowledge space within which those decisions exists, we do know that this knowledge space is conditioned by a series of variables, each of which can be measured using low cost sensor technology. Location, rainfall, soil makeup, wind speeds, temperature, historical yields, ambient humidity, crop and input types, time, distance to market, are all things that have a real data set. This data set, when looked at objectively, shows us what optimal yield and soil outcomes could look like. When compared to the real time decisions of a farmer then, we can see the distance between what could happen and what is happening now.
Though this may sound like a data play, that could not be further from the truth. In order to understand why some decisions are made, time must be spent in the field with farmers, developing a deep understanding of their needs base. The optimal response to a series of data in Myanmar will be vastly different to the optimal response in Tanzania. That is what we are beginning to design for. The grunt work of the Future Sense project has been understanding what we should measure, the hard part, the part that will require us to go deep while remaining culturally appropriate in our design work, is understanding how we should support and facilitate the optimal response to those measurements. How can we use low cost, emerging sensor tech to improve the outcomes of farmers in emerging markets? It is not simple. First we have found what to measure and where, now we must design a response to those measurements which allows farmers to benefit from them.
Darina was right when she said that it all starts with good soil. That is where it starts, but there is more to it. Without good decision making, good soil doesn’t matter and without good soil, good decision making can only get us so far. Where the rubber meets the road for us on the Future Sense team, is thinking about real agricultural ecosystems and the decisions being taken within them and understanding how best to design an intervention that supports farmers in navigating towards their own optimal outcomes.
