In February 2014, I was sitting at Palm Spring International Airport, returning home after a conference I attended. I was invited to give a presentation titled “Pros and Cons of Leasing vs. Buying Equipment.” While in the airport terminal, I overheard a conversation orbiting around commodity prices and the recent erosion from $7.00 plus to somewhere in the $6.00 range. I remember one of the participants saying, “I’m still making money, just not as much.” The beginning of 2014 was the start of the rapid slide off into the abyss that lasted the next 7 years.

What would have been the difference had you known this was coming? What would you have done differently?

“What does your crystal ball say?” Anyone in the business of guessing the future value of anything gets asked this question regularly. The standard answer is, “Mine is too cloudy to see,” or “mine is cracked,” something along this line. 

I am a big fan of the Magic 8 Ball answers as well. There is a crystal ball, and it can predict the future in very vague Nostradamus-like quatrains. The information is there, but it is open to interpretation. The more information available, the better chance of pinpointing who, what, when, where, why and how the market will move.

I have found over the years of looking at buying behavior that it’s not the physical price of commodities that turns up or turns down buying relatively. The physical price of commodities sustains buying habits, positive or negative. The movements in commodities is what turned on or turned off buying. The promise of, or lack thereof, profit drives producers to make equipment updates and other inputs on the farm.

On April 28, 2020, corn closed at $3.03. This was the lowest corn had closed in decades. Not much was happening, but there was a slow trickle of sales activity in most places. The price of corn slowly started to rise, and the same slow persistent trickle continued until corn hit $3.50, $3.75 and $4.00. 

When corn was selling at $4.00, the flood gates were wide open, and new and used machinery was selling as fast as producers could get their hands on it. Since then, buyer demand has not increased; instead, demand is as strong now as it was in fall 2020. So, what is the driving factor? The $3.75 corn had as much demand as $4.00 corn. Why is demand the same now at $7.50 corn as $4.00?

“Predictive analytics has to become a part of the ag equipment business, not only for the dealer but also for the producer…”

The argument is the physical price of commodities only matters regarding sustained buying patterns. The movement of price, up or down, is what turns on or shuts off buying, like the conversation in the airport terminal. The price has slid enough, even though it was at a reasonable and profitable level, to leave enough doubt in the producers’ minds that their buying decisions were in question. The $6.00 corn is $2.00 higher grossing than $4.00 corn.

I am no commodity expert. If I were, I wouldn’t be writing this article. Instead, I would be on my private island drinking something with an umbrella. So instead, we try to understand the movements in the commodity market, up or down, and what effect the move will have on the buying patterns of the North American farmer. 

The better I can judge the upswings and down swings in the market, the better I can position profitability. So how can I do this?

More data is available today by a simple Google search than ever before. Historical information is plentiful and, in many cases, free. Looking at auction data and what was happening in commodities historically paints an excellent picture of what to expect the next time the same scenario happens. 

The absolute best source of information is your business system. Think of the power of taking 10, 15 or 20-plus years of sales data and splashing it against a corn, wheat, soybean or cattle chart to see how the movements in the commodity market affected the overall outcome of new and used equipment sales. When armed with this data, recognizing an uptick or a downturn in the commodity market will trigger proactive instead of reactive decision-making. 

Be the first to auction equipment or slash prices, not the last. Start buying as much of the available used inventory at the bottom and sell at the top. Predictive analytics has to become a part of the ag equipment business, not only for the dealer but also for the producer.