“What can my Data do for Me?” is the Wrong Question
Make Your Data Make Sense
It’s easy to look at the mountains of data you’ve brought in on flash drives since GPS enabled your combines to be outfitted with yield monitors—and ask, “What can this data do for me?” You’ve spent a lot of time collecting it and bringing it into the back office—so now what can you expect to gain from all your hard work?
But “I have this in front of me; what can it do?” is asking the wrong question.
We’ve all had a wiring problem with a vehicle, and we know that a Chilton’s manual has the answer inside. But if you were to sit down and read the entire manual, you’d wind up with a lot of “useless” information—because it doesn’t answer your specific question—and more importantly, you’d be frustrated long before you made it to the right page. Instead, you’ll say, “There’s an issue with the wiring on the fuel injector.” You’ll turn to the page with the fuel injector wiring diagram, and you’ll learn how it works, and you’ll know how to repair the issue. Your problem is solved in a better way because you thought about it intentionally.
It’s similar with agronomic data. A wise person told us, “You’re going to use this someday, so start saving it now.” But we weren’t told what our data would be used for. And now that we’re up to our necks in bits and bytes, we’re waiting for information to jump out in front of us, congratulating us for our hard work collecting. Unfortunately, having a Chilton’s manual on the shelf doesn’t mean you’re instantly an expert on your vehicle, and the collection of data alone is not enough to produce wisdom.
In order to learn something new, we have to ask a question. When you have identified what you want to learn, then you are ready to throw out the outliers, tease the data into order, run your analysis, arrive at an answer, and make your operation better.
So what would you like to learn? Are you planting the right varieties in the right soil? Are you putting on more fertilizer than you need to? Is the fertilizer paying for itself in yield? Should you apply fungicide where you had an outbreak last year, across all low spots, or nowhere? What kind of lease should you negotiate for this ground? Should you bid on this one at all? How much of an effect is planting date having on your yield? Does that warrant adding a planter next spring? Is one of your operators more effective than the other, and would better training help?
There is data enough to answer these questions. And once you identify what you want to learn, analysis is the easy part.
Some of these questions you’ve already thought of; some others seed companies are investigating. Others might be questions you’re asking elsewhere in your operation—and you didn’t notice that your production data can answer them. When you start with a question and then look to your data for your answer, you can ignore the parts you don’t need, focus on what you care about, test an idea, learn from history, and improve your operation. “What can my data do for me?” is the wrong question. When you want to move forward, ask “What do I want to know?”
by GIS Technician Allison Jonjak