Is My Ag Data Valuable?
Value is a tricky creature. It always seems to mean different things to different people. For example, I think bacon is very valuable due to its high level of deliciousness, but my vegetarian sister doesn’t necessarily agree with me. I think the corn I harvested this year has value of around $7.00 per bushel, but I can’t seem to find anybody who thinks it’s worth much more than about $3.80 per bushel. I guess all the people really can be wrong all the time. What gives?
The primary lesson about value is that, at its core, it is a feeling assigned to things by people. Therefore, the question of “value” for you is different from the question of “value” for other people. Commerce is about finding common ground about those conflicting ideas of value. The price at which things are voluntarily bought and sold tells us that what the economic value is. Economic value is only an estimate of true value, and it represents a win-win situation where the seller values the money received more than the product produced, and the buyer values the product more than the money they paid. After each transaction, there is, therefore, more net value (i.e. wealth) in the world than before.
In agriculture, we have the luxury (or curse, depending on the day) of having a “perfect market” for our products: your sale price per bushel (economic value) does not depend on the amount of bushels that your particular farm produces. In other words, statistically, nobody really cares what you think your crops should be worth. A lot of people, therefore, devote a lot of time to guessing what the generally accepted economic value of our products are going to be when we sell them. Because of this, the more bushels your farm produces, the more revenue you receive: double the bushels means double the gross dollars.
This means the one most likely to derive the highest real economic value from data about your particular farm is you. You are actually planting, caring for, and harvesting the crop on those acres. Let’s, therefore, start with the question of assessing the economic value of your data to you, and we can then reasonably assume that the economic value to others is less than or equal to that. A great way to do this is to look at particular pieces of data you currently have and ask “what would be different if it didn’t exist?”
If next year there was a major solar flare that took out the GPS satellites during harvest, and you therefore had no yield maps, would any decisions on your farm be made differently? If the answer is no, then the economic value you should assign to your yield maps is zero. If the answer is yes, then you should assign the value of that data as the net change in revenue due to the decisions you make with it. If you make worse decisions because of your data (entirely possible), then its value is negative. If you make better ones (also entirely possible), it’s positive.
If at the end of your planting season, you accidentally left the door of your tractor open overnight and a squirrel snuck in and ate the notebook where you wrote down your planting records, would decisions be different? One excellent data-driven decision could, of course, be to avoid walnut-flavored paper in the future. However, if that planter notebook stayed in the tractor cab all year and was never opened again, it’s likely the squirrels made better use of it than you did.
Sometimes it seems like this squirrel is making better use of my data than I am.
Mentally perform this exercise for everything you think of as “important” data. What I suspect most of us will find is that the value we place on our data today has more to do with emotion than it does with revenue. This is fine, but we should all have the humility to admit that if we aren’t deriving all that much revenue-based value from our data, odds are nobody else is going to get much value out of that data either. For one thing, who knows how accurate our data really is if it has never been used for anything? That’s not to say there isn’t tremendous value that can be derived from your data, but the bank doesn’t care much about the value you could be getting out of your data.
 Blended images from http://upload.wikimedia.org/wikipedia/commons/2/2c/Squirrel_eating_peanut_12u07.JPG
Aaron Ault is the OADA Project Lead and a Senior Research Engineer at the Open Ag Technology Group at Purdue University.