Although change happens all the time, in some areas human nature demonstrates great constancy. One of these areas is how Pavlovian we react to market fluctuations. Agriculture knows many cycles, most of which are as much the result of human nature as the mechanics of economics.

In the time of high commodity prices that preceded and followed the Great Recession of 2008, one of the main questions I was asked about the future of agriculture was to give predictions about prices and profitability of agriculture. This is a tricky exercise if there is any. So many factors can influence both supply and demand that it is unrealistic to believe someone could predict with certainty future prices. Price predictions would only be meaningful by predicting costs at the same time. Despite the difficulty, many economists venture in the exercise. The levels of accuracy are disappointing. Past research on economists’ and gurus’ predictions has shown accuracy levels of 47% on average. In other words, tossing a coin would statistically be more accurate by a margin of 3%.

When “predicting” the future, it is more useful to focus on patterns than trying to miraculously try to pull the right numbers. Human nature is rather predictable. When prices and profitability are good, suppliers want to produce more, because they expect the result to be even higher profits. It is intuitive, and it would work fine only if the competitors did not follow the same thinking. Unfortunately, they do and the result is an increase in supplies. As it takes two to have a supplier-customer relationship, the flip coin of the high price medal is that buyers are less warm to buy more of what increase their costs. I like to compare value chains to an accordion. There is only so much money that flows between the two ends of the entire chain, and all the links must share that money. One end is the consumer market and depending on prices, consumers switch foods when prices reach a pain threshold. Since the amount of money entering value chains actually come from the consumer end, consumer resistance limits the elasticity of the entire chain. Thus, depending on the relative supply and demand between the individual links of the chain, some see their profitability expand while others see it shrink. The FAO knows the conundrum. High food prices put the economically vulnerable into food insecurity, while low food prices put many small farmers in economic difficulties, and into food insecurity. There is nothing like a food shortage causing high prices to encourage farmers to produce more. Following high price years, they have done exactly that, and that is why prices have fallen, sometimes to the point that entire sectors suffer dramatic losses. Low prices will give an incentive to those who will survive to boost their production, and the cycle will continue.

The counter intuitive approach is to be a contrarian and to supply tomorrow products that have low price and low profitability today and reduce exposure to today’s attractive products. It is easier said than done, because natural conditions limit the choice of products a farm can produce and heavy investments for one kind of production can limit flexibility. Nonetheless, the contrarian approach is a good one from a planning and forecast perspective. Market swings happen because forecasts tend to be made with today’s prices in mind and assume that the system is static. It is not. Forecasts must take into account the big picture and project what all actors of the value chain will do, as well as in what shape other value chains are and will be. The tools have been here for a while. The exercise then comes down to technical analysis, which is a very common method used by traders. It uses historical data and the predictability of human behaviour to give an indication of which direction prices are most likely to go in the future. Unfortunately, too many actors in value chains do not use that tool for their forecasting and miss on the most likely picture of the future. Some help might be coming, though. The development of software, robotics and artificial intelligence will come to the rescue by eliminating the intuitive and preference of the present of human nature by more rational analysis and forecasting than is the case today. Price setting and negotiations will increasingly be automated and carried out by machines, squeezing out the human factor, especially for undifferentiated commodities. Wall Street is already working on this. Earlier this year, Goldman Sachs indicated that they were going to replace traders by software engineers to achieve this very change, and also to reduce their costs, as a software engineers cost them four times less than a trader.

Copyright 2017 – Christophe Pelletier – The Happy Future Group Consulting Ltd.