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What Makes the Adoption of Agricultural Software Difficult for Farmers

Adoption of agricultural software.

Today, farmers have access to software that has the power to reshape the entire industry. With a few taps, they can grow more food with fewer resources and reduce input costs.

While software adoption rates are continuously increasing, the progress is still slow in comparison to other industries that leverage similar solutions. 

So, what’s the hold-up?

In my role at Growers, I travel the US speaking with agronomists, equipment dealers, and ag retailers – and I spend a lot of time with farmers.  

I had a prospective customer tell me once, “Steven, you’re trying to sell me a product that I don’t want. I’m not concerned about getting the right amount of seed and fertilizer on every acre. I’m concerned with GETTING seed and fertilizer on every acre.” 

The look on my face was of complete bewilderment, maybe even sheer horror. 

He’s the “progressive farmer” with tens of thousands of acres, and the best technology money can buy. And chooses, despite market volatility, weather pressure, margin erosion, and price sensitivity, not to use it.

Instead, he applies the same rate of seed, fertilizer, and chemicals on every single acre.  

If that’s a new concept or revelation to you – this isn’t a problem for large farmers, it isn’t a problem for small farmers, it’s a problem for agriculture.  

And, it’s a technology problem.

By that I mean, there are three critical concerns farmers have that inhibit adoption:

  1. Data is inaccurate, biased, and difficult to collect
  2. Most ag software solutions don’t support the entire production process
  3. Farmers don’t know how to leverage data for financial and competitive advantage

For farmers to adopt new ag software, companies need to go the extra mile and create tailor-made products that meet the farmer’s needs and make adoption worth it. 

In this 3-part series, I’ll break down each barrier: how it happens, why, and what we can do to change the trajectory of slow agtech adoption. 

Let’s start with data. 

Farmers understand how difficult it is to collect accurate data, so they’re often skeptical of how this information can be used to support them in more informed decision making.

When I say accuracy, I’m referring to the accuracy of whatever data the farmer is collecting (soil, planting, application, harvest, imagery, financial, etc.)  

I know you’re thinking, “Of course we need accurate data!”, but for those who have earnestly tried to collect unbiased, accurate data, you know how challenging that can be.  

Here’s how it happens and why it’s a problem:

Data of questionable quality comes in. 

Then, we use that data to define a process, so the quality wavers even more. 

When we start making decisions on that data, you can see how the quality of our decisions can get out of control. 

Each of these data points gets further and further from the truth (what’s actually happening in the field). And the number one reason why most data is inaccurate?  Human error. 

So, how can we get accurate data? 

First, when you evaluate a precision ag solution for your operation, err towards the solution that focuses on automated data entry.

For example, does the software allow you to set up your monitor with a configuration file that has the correct naming convention already included? Or do you need to type the name of your seed varieties into your monitor?

If you don’t have to rely as much on the “human component” to record the information where human error can be significant, the better off you’ll be. 

Second, prioritize learning, training, and teaching for those who are involved in your operation.  Learn what parts of the process you should automate to remove the risk of human error.  

For example, the “auto-field boundary detection” is common on most precision ag monitors today. Using the equipment GPS location, and a previously recorded or uploaded boundary, the equipment monitor can detect what field it is located in. And it can automatically populate the correct Grower/Farm/Field hierarchy, which is important for those that are streaming data to the cloud.  

When you can save the data to the right field AND not rely on your operators to do that correctly, it’s worth the time, and it’ll pay off in spades as you start to understand how to extract value from your data and use it in the future.

Lastly, and to my point above – be the professional that can act as a guide to your farmer. I’ll argue till I’m blue in the face, every farmer needs a precision ag service that utilizes a technology – not the other way around. 

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