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Playing Chess, Not Checkers – 3 Moves to a Data-Driven Resource Management Strategy

1 Jun 2021  •  Erin Hightower

The business of farming is a lot like the game of chess. Strategy. Skill. Staying a step ahead of the opponent – although, unlike chess, growers have multiple opponents including weather, pests, and other factors out of their control.  

Different resources like equipment and people are like different game pieces, each with their own functional abilities and rightful place in the field (on the board). Just as a grandmaster does not move a bishop or knight without a thoughtful reason, growers must use a strategic plan, factoring in all resources, and based on more than gut instincts and experience. And every decision made is ultimately for one, big-picture goal: protect the king. Of course, on the farm, the crop is king.

Precision ag data is a useful tool to make good, informed decisions in playing the strategic game that is farming. Without good data, it is like only seeing half of the opponent’s pieces. It is important to see every piece of the board, not just the pawns and the rooks.

I think we can all agree one of the biggest challenges of implementing a data-driven precision farming strategy is overcoming feelings of overwhelm. In my years of working with growers, one of the ways I have learned to address this challenge is to focus on smaller, more manageable areas. I have identified three key resources growers need to manage on a daily basis: people, equipment, and inputs.

Related article: 6 steps to maximize agronomic data 6 steps to maximize agronomic data value

Here are a few examples to show how good precision data can be helpful in these three areas and used to play chess, not checkers – that is, make strategic management decisions.

People Resources
A company’s most valuable assets are its people. Each team member brings a unique blend of knowledge, skill, and personality. Like all assets, proper management of people is important to getting best results.

Operator Jane’s data may show she runs her sprayer at a speed two miles-per-hour faster than operator John, while operator Bruce’s data demonstrates he has a quicker adoption period with new precision technology than operator Betty. By having good data on every operator, growers can align the right operator to the right task, the right machine, even the right field position to best bring out their strengths.

Data can also be revealing about operators themselves, enabling adjustments to either behavior or the equipment. I recently worked with a grower who upgraded his older, slower sprayer to a faster ExactApply model. Upon reviewing initial operating data, it showed he was operating it at a faster speed than his previous sprayer and the nozzle size he thought he needed was no longer correct. Had he not collected and reviewed that data, he would not have changed his nozzles and may have continued to operate with the incorrect size, which was creating unstable droplets and not putting on enough chemistry.  

Interested in knowing more about choosing the right sprayer nozzle? Watch this sprayer nozzle selection guide video:



That brings us to the next key resource: equipment. There are more ways that data can help make the most out of equipment resources.

Machinery Resources
While a farm’s most valuable assets are people, the most expensive ones are equipment. There are so many ways that good data can optimize a farm’s equipment management strategy.

Regular preventative maintenance is the difference between a machine that operates without worry for hundreds of hours and one that is prone to breakdowns, often at the most inconvenient times. Technology offers a great way to track machine hours and maintenance intervals, removing any chance of human error using handwritten maintenance logs. Technology can also provide insight into a machine’s utilization that may be assumed otherwise.

One of my growers recently commented that he was excited about two new windrowers he added to the operation. His operators shared his enthusiasm for these new machines – maybe too much. He quickly realized these two new machines were being used at a rate nearly double what he anticipated. Why? Because operators were choosing the new machines every time and rarely using the perfectly good, yet older models. He expected all the machines to be used at an even rate and created a maintenance plan to reflect equal hours. Realizing the two new machines were logging more hours, he was able to adjust the maintenance plan to be sure the higher-utilized machines were getting appropriate TLC.

Another way to use data for machine optimization comes when pairing tractors with implements. Different implements demand different RPMs out of the tractor. Consider a piece of equipment that needs a higher RPM, like tillage, and one that needs less RPM, like a seeder. It is important to pair the tillage equipment with a tractor that has the horsepower to meet its needs, whereas a smaller tractor can be used to run the seeder.

That is obvious, right? But this data is more valuable than one might initially think. I recently worked with a hay grower who realized he was oversizing RPMs significantly. Once he had the data to show just how wasteful this was, he updated his fleet to less expensive, smaller tractors that still met his power needs.

Data can help take the optimization practice a step further. For example, consider the ability to track fuel and diesel exhaust fluid consumption. It is one thing to determine the least amount of horsepower an implement requires, then right-size the tractor in the most optimal way. Further optimize machine pairings by finding that sweet spot where the tractor meets the horsepower needs while using the lowest amount of fluid.  

That leads to the third resource to track and optimize: input resources.

Input Resources
Here is a question: which areas of your farm deliver the best return on investment. I will ask the question again, this time the answer cannot simply be, “The one with the highest yield.”

A field may deliver the highest yield, but what if that field also requires more than one pass to get rid of the palmer amaranth? What if it requires more fertilizer than another because of its unique terrain and characteristics? Essentially, that top producing field may also be the top consumer of costly time and inputs. Data can be the secret to exposing truths about some fields and unlocking hidden potential in others.  

One way I have seen growers adapt to unique field needs is using variable rate practices. Whether seeding, nutrients or other inputs, a variable rate strategy is one of the best ways to control input costs and eliminate waste. It is also great advice for those who are struggling with how to produce more in the same amount of space. After all, it is easier to variable rate than it is to find new ground to farm.

Need to know how to upload a variable rate prescription to a Gen 4 display? Watch this video:



One way I help growers understand variable rate strategy is looking at it through the lens of a livestock farmer. When managing a herd, a farmer is constantly evaluating the cows throughout the year, paying attention to which cows get sick, which ones lose weight, which seem to have an easier time gaining weight and so on. They address this by giving some more feed or medicine or, conversely, less.

This is not a magical strategy; it is simple common sense. You would not feed all cows the same amount of food if some were gaining weight and others were not. You would not give them medicine if they did not get sick or withhold from the ones that did. You do not treat them exactly the same because they are not the same; each is unique and all have individual needs.

The same is true of fields; every field has unique characteristics and needs, yet it always surprises me that it is not common practice to treat them differently. This is where a variable rate strategy comes into play and doing it well is dependent on good data.

Especially when it comes to in-field practices, I think it is common to do certain things or do them a certain way because that is the way it has been done. Data can help and encourage looking at situations more critically and determine what is necessary, what is right, and what can help get the best production with the lowest inputs.

Protecting the King
If you play chess using the same strategy, the same set of moves every time because, “That is how I have always done it,” I can almost guarantee you are not going to win. The opponent – weather, pests and all those factors out of your control – is not the same every time. They are going to throw out new moves, change it up, and, at times, be totally unpredictable.

Strive to be the grower who is playing chess, not checkers. If you are always thinking several steps ahead, doing your best to anticipate an opponent’s next move, and drawing on more than gut instincts to make the right decisions, you are more likely to avoid being caught in checkmate.

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Interested in more about precision agriculture? Check out the RDO Equipment Co. Agriculture Technology Agriculture Technology Podcast, browse past episodes, and find out more about everything from equipment to UAVs to specialty crop care. Watch the video series Precision Ag Precision Ag Answers – from RDO Equipment Co. on YouTube – from RDO Equipment Co. on YouTube for a mix of quick tips and deep dives into the biggest precision agriculture questions.



Erin Hightower

Erin Hightower has been working in farm planning and agronomy for 15 years. As an Agronomist at RDO Equipment Co., she works with team members and growers in the Northwest region, focused on education and training, and conducting field trials. She is a Certified Crop Advisor (CCA) and Certified USDA NRCS Nutrient Management Planner, Certified Conservation Planner, and Comprehensive Nutrient Management Planner.

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