Dan Frieberg

Premier Crop Systems

Dan Frieberg is CEO of Premier Crop Systems, LLC a crop data-analysis company based in West Des Moines, Iowa. For more information on Premier Crop Systems or data-driven decisions, visit www.premiercrop.com. Premier Crop Systems will push you to dig more deeply into your field data and find just how much power lies in the information layers that hide within your acres.

Learning blocks show variable rate application payback

Since 2005, we’ve been checking our work with our trademark Learning Blocks and we have proved, and continue to prove every year, that variable rate applications frequently pay. It’s not 100% but given the complexity of our modern crop production the results from millions of acres are amazing.

Data can show cost per bushel

Imagine the power of knowing your long-term average cost per bushel by dominant soil types. Maybe you’ve mastered being profitable on lighter soil types and that is one of your strategic advantages.

Dig deeper into data to analyze sidedress nitrogen applications

What do you do when data analysis doesn’t support your own theory? For me, the first answer is to keep digging in the data. I’m still a believer in split applying nitrogen – including sidedressing a portion, but living though those dry summers would lead me to get the work done early.

Variable-rate seeding success

For many, analyzing variable rate planting with strip trials has resulted in conclusions that aren’t positive for the practice. Our results and experiences have been the opposite. Using higher and lower Learning Blocks™ within management zones and analyzing yield results have led to even faster adoption.

Dig deep into data to get more yield

In what parts of your operation, are you looking for actionable data to help make a tough decision? Keep digging into your data. More than likely, the “first layer” is only a step in the right direction. Although it may take more time, digging into a second and third data layer may provide discoveries that are well worth the effort.

Mind the gap: Quality ag data analysis relies on quality ag data

Quality data analysis relies on quality data. And quality data requires hard work and attention to detail. Even though we can use technology to make the timing gap smaller, we all must still “mind the data quality gap.”

Who owns agriculture data and knowledge?

Recently there have been headlines about agreements between the industry and farm groups on data ownership and privacy. That’s positive. But it’s really not surprising that a company would agree that you own your data and that it will be returned or removed from their servers. Or that you will be allowed to direct whom it gets shared with or sent to.

Real agronomic complexity

I’m a believer that agronomic common sense and real world observations tell us that avoiding doubles and poor seed spacing is critical to higher yields. But they are only a few staves in a very complex agronomic rain barrel and the $ signs flashing on the monitor screen are only real if proper seed placement is your lowest stave.

Data may reduce rent

Can you use your data to rank each field by profitability? Obviously it’s not as easy as the highest to lowest yielding, as cost of input and operations, as well as land costs, are major pieces to be considered.

Don’t farm averages 2

None of us can control or even predict all the curves that Mother Nature can throw our way. But using data from your fields opens the door for you to manage the crop production variables that are manageable.

Compare real benchmarks

The best benchmarking services don’t just tell you where you rank – but they tell you why. What does the data say you need to change to perform better or to keep doing to stay on top?

Data decisions: Use technology to verify company data  1

As companies line up to offer you solutions based on their proprietary algorithms that you adopt the same position as President Reagan did in negotiating arms treaties with the Former Soviet Union – “trust, but verify”. If a company tells you that their proprietary algorithm says you need 50 lbs. of additional N, use your technology to verify.

Data Decisions: Meaningful data analysis involves agronomic common sense, local expertise 2

“But how do I know if what I am seeing in my data analysis is real?” That’s a question that is not only appropriate but also healthy. For the last 15 years, as I’ve presented agronomic decision data analytics to growers and their advisors, I’ve cautioned that “correlation doesn’t always equal cause and effect,” says Dan Frieberg.

Data Decisions: Find profit in agronomic data 2

Let’s assume you are motivated to get started using your agronomic data to make decisions. What do you do next? Spring planting is hopefully only days or weeks away; what is possible? A great place to start using data to make decisions for the future is to gather all GPS data in an electronic form.

Data Decisions: Share your farm data?

Reality is we all share “our” data with other companies, either intentionally in exchange for a benefit or inadvertently because we wanted a cool “app,” and sometimes the tradeoffs are worth it. For me, the difference between consumer data sharing and sharing your geo-referenced agronomic data is profound.

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