Farm data is a powerful tool that can drive crop management decisions, boost performance, and lead to a better return on investment (ROI). However, with so many databases and programs at our fingertips, it is often overwhelming to process all the information.  

With the right digital strategy, you can harness the power of datasets on your farm. This winter, folks from across the agricultural industry gathered for an open-floor, roundtable session to discuss ways to counteract digital challenges.  

The session was moderated by Ed Barnes, director of agricultural and environmental research at Cotton Incorporated. Barnes said, “Digital strategy is a broad term. It is about managing data, getting value from data, protecting data, sharing data, and owning data. There is a lot packed into it. 

“When we first started this roundtable years ago, everyone had data but did not know what to do with it,” he said, noting the transformation of the discussion over time.  

“Now, a key question we hear today is, ‘How do we use that data to identify parts of a field or fields in general that are losing money?’ That, I think, is the best use of this type of data and it starts during the preseason.” 

Use consistent naming conventions

A good digital strategy begins with uniform naming conventions across all platforms for each field, piece of equipment, and even irrigation infrastructure. This simple, front-end step allows for a consistent flow of data and provides for easier communication, especially during the summer months when real-time decision making is most critical.  

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Start by making sure each field is entered into every program under the exact same name and spelling.  

One farm manager noted how misspelling can cause disorder. “Standardize field names,” he recommended. “In looking at all kinds of maps over the years, you would be surprised at how many different ways a field name can be misspelled." 

Do the same thing for each tractor, implement, and irrigation well on the farm. Then, train your workers to follow the strategy consistently. That way, when tractors roll into a field, all operators know what to select – from the field name and piece of equipment down to the correct year and crop variety. 

Turn maps into decision making tools

The best decisions are based on years of high-quality data, compiled to pinpoint production trends over time. This requires looking for correlations in ground-truth data from field maps and datasets. The question is, how do we take those maps beyond just having a collection of pretty pictures? 

Related:Planter monitor data comes to your phone

Barnes said opportunity lies in normalizing the information to identify zones of the field where you are losing ROI. This may be corners of a field or sections where the cost of seed, fertilizer, and sprays exceed what that part of the field can produce. 

Barnes gave the example of sand blows in a cotton field and said after about three years, you can see areas of the field that are not making money. Look at all the data and set goals for your operation. 

He said, “If you can identify the problem, there may be some remediation steps, but you have to know the cost of everything, and you have to know how much yield you are losing.” 

Solutions may include target fertility treatments, addressing field elevation, or focusing on drainage issues. It could also mean taking those areas out of production and enrolling them into a conservation program, like that offered through the Quail Forever precision conservation program. 

Garrison Hardke, U.S. marketing manager at RiceTec, joined the conversation and reported the success of top rice producers and land managers who utilize past data to write prescriptions for the upcoming season.  

Hardke gave the example of row rice and the yield difference between the top and bottom of the field. “We have been working on nitrogen strategies to address more uniform yield,” he said. “We have farmers who are devising tests and different strategies to try this year, and they are already setting themselves up to collect that data.” 

Appoint a data analyst or consider outsourcing the job

Precision farm data is pulled from multiple sources through a divergent array of file types, mapping systems, drone images, and scale factors. This can complicate matters when it comes to consolidation, and having a single person dedicated to data management is one strategy for success. 

One participant suggested, “If you are a large operation that works with precision ag data pulled from multiple sources, you really need a data analyst or data engineer. Customizing the data is a tradeoff. The more you customize, the harder it is and the more you need someone dedicated to that job.” 

Another farmer who runs a smaller operation said he is basically the only employee on the farm. He said, “The most important thing that I have done with my data was to outsource it to someone else. It has enabled me to do a lot of things I could not have done on my own.” 

He outsources the work to a company who pulls soil samples and sets up zones based on absolute yield, which allows him to carve out problem acres and strategize accordingly. The farmer added, “It is a cost, but I feel it has been a positive ROI for what we have been able to accomplish.” 

Barnes affirmed that normalization gives you valuable information on concrete zones in the field, but the process takes effort.  

“Normalizing a yield map may not be in everybody’s wheelhouse. You might have to contract that out, but once you get that information, you can better understand the yield potential in each zone.” 

Share data as a valuable communication tool

There are many reasons a farmer may need to share or receive data on the farm, whether it is from a landlord or custom applicator. It is good to balance both sides of the equation, and it is worthy of including a data sharing statement in lease agreements. 

One farmer explained how she shares data as an open line of communication to demonstrate to her landlords the reality of farming their acres.  

“With three to five years of data sets, you can show the added value over time to their farm,” she said. “You can also bridge the gap for landowners who might not understand farming.” 

Barns noted the importance of getting down to the numbers. He said, “With data, you can take the emotion out of the equation. That can be a selling point to landowners, especially with things farmers are competing against like increased land values, subdivisions going in, and solar panels going up.”