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    Open Ag Technology Group at Purdue University
    aaron@openag.io

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How Do I Get Value From My Data?

How Do I Get Value From My Data?

We’ve seen an example previously in this series (see below) of one way to gain value from your data which provides insight into why you are having so much trouble turning your data into dollars today. The real economic value in Ag Data is the extent it can be used to:

  1. improve our daily operational logistics,
  2. evaluate the revenue implications of our daily decisions,
  3. and better learn the mysteries of the physical world that cause our crops to behave as they do.

We’ll take a look at  some examples of #1 in the next installment of this series: improving our daily operational logistics.  I list it as number one because it is the single most likely way to start making data profitable on your farm.  It is about answering questions like where is everything and everyone, what are our plans, how close are we to “complete”, where should we put new tile next year, what was the oil filter number on that tractor, etc.

Now let’s look at item #2: evaluating the revenue implications of our daily decisions.  If we spray a new fungicide this year, data can help us figure out how many bushels more or less we got as a result.  If we want to compare no-till, minimum till, and conventional tillage, data can help us get there.  Cover crops, refuge-in-a-bag, overlap control, auto-steer, fertilizer timings and placement, and literally hundreds of other practices are just begging us to try them out in the search for higher yields.   But can we afford the fee for each?  Data is the only way of truly figuring out what works best.

The trouble is, it turns out to be really, really hard to get definitive answers to these questions.  Tell me if this scenario sounds familiar:

OADA Conversation

The sad truth is that most of the time, we farmers buy things because they are new, use them for a few years without disastrous results, and then switch to the next new thing.  Most of the “trials” we run on our farm generally end with inconclusive, non-disastrous results.  There is always some convincing reason to distrust the final yield numbers: it was an “unusual” year for weather, we didn’t really compare apples-to-apples, the nitrogen applicator was on the fritz, the genetics compensated for our changes, etc.

This Part 1 of 2 blog posts on  How Do I Get Value From My Data?

This is part of a series of articles on Ag Data by Aaron Ault

Aaron Ault is the OADA Project Lead and a Senior Research Engineer at the Open Ag Technology Group at Purdue University.