Farmers Have Trust Issues With Big Data — For The Same Reasons As All Of Us

Every 10 minutes, the farmers we work with get vital signs from every corner of their fields and gardens. Temperature. Humidity. Barometric pressure. Insect population. With incredible precision, a system of thousands of networked sensors reports back conditions with a level of detail unimaginable even a decade ago.

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But here’s my biggest fear: All this data — the backbone of the burgeoning agtech industry that has the potential to reshape the way we grow food — also has the potential to make farmers’ lives more difficult. And for all our technological sophistication, we can finally do little more than add noise to their busy lives, than help them grow more, better, and healthier crops.

We are on the brink of a big moment for agricultural technology, as it is poised to become a $22 billion industry by 2025. Precision agriculture (using data and AI to optimize agriculture) has a big role to play in that. But to get there, we first need to understand the basic difference between signal and noise for farmers in the field using our tools.

In short, as an agtech provider, how can we do a better job of giving farmers “the news they can use” … and filtering the rest?

Challenges for farmers

Data and analytics now play an important role in almost every industry. But the general theme remains.

In one study, 91% of executives said their data had not yet reached a “transformational level” in their business. Most cited complexity and lack of training as barriers.

Precision service providers should have the same thing — simple stepping stones to smart decisions, not mountains to climb

For farmers, this challenge is very acute. They now have access to more data than ever about their crops. However, using it is another story. In fact, a 2020 study showed 70% of farmers said they didn’t have the training needed to use more data in their operations, and 75% said they didn’t have the time to handle it.

Put yourself in their shoes. You have multiple systems reporting back some aspects of your operation. Often, these tools are not compatible with each other, so each one provides a different set of numbers on different platforms. Farmers are left to sift through this flood of information, when they really want actionable insights. Big data needs to be a trusted advisor, not a tricky foe.

What farmers really want in their data

There’s a line from Google’s philosophy that many companies can learn from: “We’re probably the only people in the world who can say that our goal is to get people to leave our website as quickly as possible.” Precision service providers should have the same thing — simple stepping stones to smart decisions, not mountains to climb. For me, it boils down to a few key considerations:

data vs. outlook

As a scientist working in this field, I know all about the vast amounts of data required to make predictions on these complex farms. But what is far more valuable to a grower are actionable insights. It’s like the difference between a diagnosis (knowing what went wrong) and a prognosis (knowing what to do). Contemporary sensor technology can provide farmers with line-by-line or even crop-by-plant details such as insect pressure or water absorption. But it’s one thing to absorb all that information, and another completely to know what to do about it.

Important timeframe

In many cases, “actionable” depends on the timeframe. Farmers in the field can take days, if not weeks, to structure a response to changing conditions. That’s why reporting real-time conditions is less helpful than anticipating what lies ahead. And this is where AI and machine learning come in handy. A big pest for the farmers we work with is the navel orangeworm. These moths can destroy gardens quickly. If farmers were only warned while an attack was in progress, they would be left defenseless. Instead, they need tools that can predict infestations ahead of time and suggest (or better yet, automatically trigger) the appropriate response.

Zoom out before zoom in

On any farm, you have different individuals who rely on data — from people in the field trying to make quick decisions with just a smartphone, to managers checking charts and tables on the desktop. That’s why agtech needs to take its cue from consumer technology and put user experience first. A successful product starts with a simple dashboard where anyone can view mission critical information such as weather, pest stress, water management and crop stress. A grower can dive as deep as they want into the platform for more information, but can take comfort in knowing they don’t have to.

Independence is everything

A 2018 study looked at farmers’ perspectives on Big Data, and found privacy and ownership to be among their biggest concerns. Who collects the data collected from my fields? Was it sold to someone else? Is the advice I get on everything from pest control to fertilizers unbiased and objective… or is there a hidden agenda? That’s why agtech providers need to offer clarity on what data is collected, why, and how it will be used in the end. Farmers have good sensitivity to conflicts of interest, and no one wants to see their information sold to third parties, or potentially used against them.

In the face of challenges ranging from changing weather patterns to supply chain disruptions, precision agriculture is a powerful way to help nature feed a growing population. The right data means the potential to do more with less: fewer inputs and lower costs for higher yields and greater ROI. However, for this potential to be realised, it is necessary to look beyond data collection, machine learning and cutting-edge technology, and come face-to-face with the one person who makes this all possible: the farmer.