The "target" is a tool commonly used by farms to establish objectives. Ideally, that target represents an attainable goal as opposed to some long-range aspiration. And while it is not uncommon to set our sites on a single number, we generally are willing to accept anything - plus or minus - within a range of that number.

When targets are set to represent a system's specifications, i.e., what it needs to achieve, then it is fair to assume that deviations from the target are at a loss to the system. For example, if the target market weight is 280 lb., then pigs marketed above or below that weight represent an additional cost to the system. Simply stated, it costs more to produce pigs that do not meet the target weight. The same efficiencies of space, feed and transportation will not be achieved. Similarly, packer premiums decrease as weights and carcass characteristics deviate from the desired target.

Likewise, for a system designed to handle a certain number of pigs, deviations from that number come at a cost (real or opportunity) to the system. If the system over-produces pigs, then growth performance will be compromised by overcrowding. Alternately, if the system under-produces pigs, then its facilities will not be efficiently utilized.

The approach of having an acceptable range around a target is sometimes referred to as the "goal-post" view. That is, as long as the production falls within the acceptable range around the target, there is no additional cost to the system. An alternative approach (developed by Genichi Taguchi) is to perceive deviations from the target with a loss function (see Figure 1). A loss function assumes that the cost of a deviation from target increases as the size of the deviation the increases.

To further explore this concept, we'll consider two finisher distributions. For this scenario, the objective is to market pigs at 280 lb. with an acceptable window of 20 lb. above or below (i.e., 260-300 lb.). Group 1 meets the objectives of marketing all pigs within the acceptable window. Group 2 pigs, however, range from 248-314 lb., with 1.3% falling outside the acceptable window (see Figure 2). However, when the two distributions are evaluated using a loss function, the cost of missing the target in Group 1 is more than three times that of Group 2 - even though all of Group 1 falls into the acceptable window.

Although it may be a more comfortable approach, assuming a "goal-post" view of targets comes with a price. When the target truly reflects the optimal scenario for an operation, efforts should be made to achieve the target.




Click to view graphs.

Stephanie Rutten, DVM
University of Minnesota
rutt0011@umn.edu
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