Cost of Production 2009: The End of Points and the Beginning of Distributions

     For years, modern swine producers thought about cost of production as a point or single number.  For almost a decade, a cost of production of 38 cents a pound was consider standard, high efficiency cost control.  Those days are gone and I don't mean just that number.  There is no new number which is or will be the normal cost of production for all of us who love to live by rules of thumb.  The cost of production for meat animals is largely determined by the cost of the underlying feed ingredients which have entered a phase of volatilty that is not likely to abate.  The continued mandates for ethanol production which will absorb four billion bushels of US corn production will keep key feed ingredient prices on a perpetual "stocks-to-use" razor and provide another source of price volatility here-to-fore reserved for weather events alone.  The combined impact of weather and reduced stocks-to-use values will force the volatility of the grain sector into the cost of production for poultry, pigs and to some extent beef production.

     I have forecasted the cost of production for pigs in the US using a simulation technique which is based on the last three years corn and soybean meal price distributions to give you a new look at how you must conceive of your costs now and in the future.  The pattern of the distributions of corn and soybean meal bleed through to the shape of the distribution of the cost of production estimate.  In the graph which follows, the height of the histogram bars is the probability of a given average cost prevailing in 2009.  The average cost of production: $67.72/cwt is not the outcome with the highest probability due to the skewness of the distribution but you should learn to look at this as the pattern of likely outcomes rather than our nice, tidy, single cost rule of thumb.  Doing so will give you certain key understandings which will help protect you from big mistakes.  The graph follows:

The long tail to the right reflects the fact that crop price volatility push a greater danger of very high costs into your system than they do of dramatically lowering your cost.  This is based on the last three years but a similar pattern is observed in the last couple of decades since droughts and other crop killing disasters happen from time to time and mega-bumper crops (such as doubling the five year average) are non-existent.

By coming to visualize your cost of production in this way you will avoid some important traps of the single point mindset.  First, you will avoid the temptation to average price self-sufficiency.  By that I mean, you believe because you are a low cost producer, you can simply take the average price offered in the market for pigs and in the long run beat the competition.  That notion only works in price stable environments, in other words, "the old days".  The new days require risk management rather than the safe haven of "cost-control only" as a strategy. 

Second, you will be relieved of at least some of the fear, that when high prices come, they will last a long time or occur frequently.  Very, very high prices are rare (as illustrated in the graph), which is to say, they have a low probability.  Since "high prices cure high prices" through substitution and use conservation, you will be guided to make better decisions about locking long term current high prices in an environment when bubbles and other price drivers have everyone thinking prices could go even higher.  Such as when commentators where talking about $12 corn last summer.

Lastly, this new envisioning of prices and therefore costs, will give you guidance regarding locking margins, which is the only way to go at this stage of the game when meat prices and input costs are subject to wide and unpredictable swings.  By visualizing the patterns of corn and soybean meal prices coming into your cost of production and realizing the impact their distributions (rather than their levels) have on your distribution of costs will help you avoid liquidity disasters by choosing margin locking opportunities with better skill and ingenuity.