From time to time I ask experts in certain fields to provide us with their thoughts and insight. I recently asked Dominique Depaz, an analytics consultant to the agricultural industry, to share his process and insight on risk analysis and crop selection. I found it intriguing and have provided his words below.
FARMING BY THE NUMBERS
It is my observation that farmers are by far the greatest gamblers on earth, willing to put their entire assets on the auction block season after season; and yet they are highly risk adverse when it comes to changes in cultural practices. Most grow the same way over and over, (expecting different results); or follow a few mavericks willing to share their success stories.
Why is that?
I think part of the reason is that many farmers do not keep good data. And that is understandable. When harvest season hits, there is no time for anything else but to get the grains or vegetables off the fields. Who has time to track yield from field to field? But image the strategic value of data going back twenty two or more years? I am talking about weather information such as rain, wind, solar index on the farm, yield by fields, seed varieties, fertilizer applications and chemicals applied and pricing for the commodity. This information can be extremely valuable on two fronts: first for planning purposes and secondly for changing cultural practices.
Data mining can be extremely useful in developing risk probabilities and as a result it can guide a farmer’s planting schedule, type of crop to rotate and changes in farming practices. If you have thirty or more years of data from your farm, in a spread sheet you can analyze your yields relative to prices, weather and changes in growing practices. Even a few years can be very helpful. For example, you would discover that at the bottom of every eleven year solar cycle a La Nina event is likely to occur. This may cause droughts or excessive rains depending on your location. An El Nino event would have the opposite effect. You could then compare your yields during those periods and see how you fared in terms or production and in terms of market prices. Did the climatic change cause prices to move and by how much? You may find that droughts may have a huge impact in your region, but because the commodity you produce is also grown in other regions of the country, there is no significant change in price. Conclusion: you would loose money growing this crop with no chance to make up the losses at a later date. The strategic question then is: Can I grow an alternative crop which would fare better under the probable circumstances?
I have found that a simple probably matrix can be very useful. Here is how to develop it:
Based on your yield data, price and weather, you assign probabilities across a spectrum. After reviewing your data you may find that if you get more than six inches of rain within a week, you will loose 50% of your crops, whereas if you get three inches, you will loose less than 20%. Likewise the price of your commodity goes up 10% in the first case and only 2% in the second. Now, based on where you are in the solar cycle, you can go back several cycles and see how well wind and rain data correlated and you can make a projection that, for example, there is a 30% chance of getting six or more inches of rain within a week during the season, a 60% chance of three inches and a 10% of no rain. Of course you can break these probabilities further to obtain a smoother curve.
The final probability will look like this.
(0.50 (crop damage) X 0.30 (chance of 6” of rain) x 0.10 (price change) + (0.20 (crop damage) x 0.60 (chance of 3” of rain) x 0.02) + (0.10 (crop damage from drought) x 0.10 (no rain) x -0.05 (drop in price)* = 0.0169 or 1.69% financially better.
Note: * to mean that even though the farm had a drought the commodity price went down 5% because other areas of the country or other regions of the world over produced.
You may argue that this is a meaningless exercise, but it is not and I have used it many times to determine if it makes financial sense to replant after a frost, or a devastating rain, or early season drought.
Changing Cultural Practices
I have found that one of the reasons many farmers are slow to embrace yield enhancement products or to even trial them aside from not keeping good data is the belief that there are too many factors at play and the factors can not be differentiated.
One of the statistical tools used by researchers to overcome this issue is multiple regression analysis, which is available in an Excel spread sheet. For example, this analysis allows you to compare yield, against many variables such as rain fall, seed variety, wind, day light hours, growth enhancement products, disease etc.; and to factor the contribution of each variable to yield. As a result, a farmer can very precisely determine how effective a new product is in spite of changes in weather and other factors.
Most extension agents are familiar with this statistical tool and can help farmers set up trials and interpret the data for them. From experience, I have used this approach and have trialed and altered cultural practices each year based on this analysis. Multiple regression analysis is a very powerful tool which allows a farmer to determine what works with a high degree of confidence.
Farming by the numbers may not alter the risk of farming. Weather, disease, market prices and other factors beyond the farmer’s control drive the outcome. However, analyzing the risks and formulated alternative plans can have a very positive impact on the farmer’s bottom line.
Originally from Martinique, Dominique Depaz comes from a family of banana, pineapple and sugar cane growers. Right out of college he was among the first designers of drip irrigation systems in the western hemisphere. He then joined the Navy and flew jets aboard carrier for many years. Dominique has owned numerous businesses in and out of agriculture and has written many risk analysis software and a very complex, task driven farm management software. He is currently an analytics consultant to the agricultural industry. Dominique can be reached at: Dominique (at) SmartFarmingSolutions (dot) com