Aaron Snodgrass0:00
Credible now to get us started today. I'm going to take you back months ago. One of the things I do for my company, Agra Bowl, is produce a lot of weather content that goes out to our clients, talking about the weather, letting people know what regional, national, and international stresses are, and whether that primarily focuses on how it might impact production and then of course the markets. But I'm not a market expert, so don't ask me to be. Anyway, I was up pretty late one night, and I was on YouTube getting ready to upload my videos. YouTube will suggest videos for you to watch; it gives you a list, 'Oh, you should watch this next.' At the very top of the list, and I have no idea why this was the number one video that it wanted me to watch, well, it was this one. And I watched it at about 2:30 in the morning, and I'm like, 'This has to go into my talk.' So here it is. Site title says 'Data Analysis: Know Your Discipline.' You can see the subtitle 'The Price is Right.' This is what YouTube desperately wanted me to watch, and I'm so glad they did. How are you? Ready? Here we go.
A motor scooter from Honda, the Elite 80, with its 80cc 4-cycle engine, has plenty of power and is easy to handle for a super fun ride. And you get to bid on this first, Barbara. $1,700. Michael, exactly 21:48. And his bid is 21:48. That's an interesting bit. How did you settle on 21:48? Out on your last weekend, that was exact. You were laughing and you didn't hear what else he said. He says he watches every day. Now if he wins this, you'll see that loyalty to this show. Hey dog, what do you bid, Scott? Why did it all? He has the exact price. Well, what are the bids so far? The bids so far: $1,700, $2,148, $1,800. $1,800, Noel. $1,500. $1,500 for her. The manager. But Michael is already leaping around down there. He says he's got it. Now we'll just find out whether you got it or not. We have a lot of scooters, you know. First numbers to 2,000, 148. It gets better. Believe it. And watch a couple more seconds here. 31 years for this moment. It's an honor, sir. Well, it's an honor to have you on the show, and thank you for your loyalty, and I am delighted that you got that price exactly right. $500. All right. I'll pause the video there. Michael goes on. You need to watch this when you get home. Michael goes on to play a game, of course, where you're guessing the prices of things, and he basically just names the prices right away and cleans up, the highest winning ever on that particular game. And what I like about this is Bob Barker said, 'Oh, loyalty to my show is what made Michael successful in this particular event.' And that's not it. What I think it is, is that Michael, probably not doing this on paper or doing this on a computer, is actually performing an outstanding data analysis problem. And now he's remembering things, he's watching, he's paying attention. And why I'm telling you this is very simple. I work in ag tech. I'm also a professor at a university. When I look at the future of where agriculture is going, there is no doubt, and you'll hear Dave and I talk about this, that you in this industry have one of the largest big data problems there is. And I look at who the top performers are in farming. They are the people that are doing a lot of trial and error. They're looking at the data that they collect, they're analyzing it, they're making their decisions so that each year they are more successful. They are using the experience of their relatives, the family, dad, grandpa, whoever owned the farm before that, but they're transforming the farming experience by making really, really good use of the data you collect. Because this, in my opinion, is probably the riskiest industry that there is: farming. Think about all of the different sources of risk you have. What do we do, Dave? We are people that talk about risk in your lives. And when I think about the weather aspect of this, there is so much we can learn from great historical data. In fact, I would make an argument that you should not only be paying attention to short-term weather forecasts, but you should be paying way, way, way more attention to historical weather information on your operation. Because if you know what's happened in the past, you have the insight to make better decisions about the future.
