Agriculture has always had a data problem. After the invention of writing around 3500BCE, Nisaba, the Sumerian goddess of grain, became the goddess of grain, writing, accounting, and surveying. Like farmers of today, even a goddess of grain had to tackle the problem of on-farm data. The oldest examples of ledgers from around the same period record the inventories and distribution of wheat, barley, and other crops on clay tablets. The invention of writing and accounting was a technological solution to an agricultural problem, one of the first examples of AgTech that has drastically changed the world. Today AgTech has the potential to change our world once again.
Throughout history, most of the food produced was consumed on farm or processed and sold locally in limited quantities. Until the 1930s, the average farmer produced enough food to provide for ten people. In the last century, however, yield per acre has increased exponentially. Today, the average farmer produces enough food to feed over 150 people and is doing so more and more efficiently. Mechanization, advances in agronomy and understanding of genetics have bore fruit (pardon the pun) and much of the progress has come from robust research and development by universities, agribusinesses, and farmers. This massive increase has been known as the green revolution. Ultimately, this progress has been achieved through the harvesting of raw data around crop yield, quality, and economics to inform best practices on the farm.
Economically, this increase in production has not translated to an increase in value for raw food. The main increase in value from agriculture production from the Green Revolution has been by the value-added supply system. Most food enters a complicated global supply chain. Raw foods are gathered, cleaned, stored, sorted, shipped, blended, processed, combined with other ingredients to produce a bevy of products that are transported to waiting consumers adding magnitudes more commercial value than the raw food had in its local market. Wheat left to spoil in a field has no value compared to raw wheat stored in a silo, but bread is ten to one hundred times more valuable than siloed wheat. Furthermore, wheat left uncleaned in bins will inevitably loose value over time or it may spoil and become useless. We are seeing similar trends with on farm data.
Over the last several decades we have entered the next agriculture revolution, Agriculture 4.0. Farmers have increased the amount of data being harvested from the fields along with their crops and many understand that this data has value. The average farmer generates 500,000 data points every day but not all of this is valuable. Data collected ranges from satellite data to equipment sensors readings to handwritten notes. By 2036, the amount of data collected daily is expected to increase by 800 percent, a growth driven largely by the proliferation of sensors and other connected technologies. Just as there are different qualities of crops harvested, there are different qualities of data collected and data quality determines value. Often, the process of analyzing this information is too cumbersome for the average farm, meaning most data is either not collected, goes unused sitting in data silos losing value, ultimately spoiling or is simply wasted. Similar to wheat unharvested in a field, data that is not recorded has no value whereas siloed data will only depreciate in value compared to data connected to a supply network. Dissimilar to wheat, raw data coming from the farm does not have a robust market to enter, but this is beginning to change.
Traditionally, information gathered on farm was either used to improve processes leading to greater yield or to bolster certification claims (e.g. Certified Organic), adding value to the physical product itself. As more information is associated with the physical product, the value of those products increases, allowing farmers to distinguish their product and target premium markets. For those higher up the value-added chain, more data can allow processors to match variability in crop quality caused by genetics and growing conditions to their facilities processes, thereby optimizing their returns. We can see this process continuing the length of the value chain, with AgTech firms collecting data and passing it from the farm gate to the end consumer. This allows retailers to back marketing claims (helping to avoid or defend against lawsuits), matching products to customers needs (or values), and building consumer loyalty. More vertically integrated industries such as pigs and poultry are realizing that circular sharing of this information can rapidly increase efficiency, productivity, and value. Information collected throughout the production system in pigs can help products enter specialty markets, reduce the size of recalls, match feeding practices to quality outcomes. At an extreme information collected at the retail level around customer preference can be used to inform genetic selection.
Increasing data collection and data sharing will benefit every stage of the supply chain. It will increase efficiency, lower costs, and reduce waste. In less vertically integrated supply chains, the challenge with data is to incentivise the primary producer to take the effort to gather the information in the first place. Promise of premiums has been the customary incentive in programs such as organics markets but this has had limited success and by their very nature premiums are not scalable. To increase data collection at scale, data must be shown to have intrinsic, real world, economic value. For data to have value it must be shared, processed, packaged, and have a market. To have a robust market an industry ecosystem approach is key.
The carbon offset market may be a tipping point for data in agriculture. While there is much debate around what data should be collected, how it should be collected and even if carbon offsets should exist, this market is building a framework which decouples farm data from crops and gives it intrinsic value. While much of this market is still in flux, the basics of harvesting and processing data, regulating its quality, validating, and marketing are being set in place. Farmers who can bring this data to market are directly rewarded and often find themselves able to use this data for other financial incentives including clean water or biodiversity incentives. Partners with carbon offset programs find themselves able to make money from adding a service to both farmers and carbon offset hungry clients. Furthermore, several of these industry partners can themselves use these programs to market climate friendly products to farmers or increase their social license in an increasingly value oriented consumer market. As more primary producers realize the economic benefits of collecting and sharing data those industry partners that understand the potential of data will be the next winners in the agriculture 4.0 revolution.
