Benchmarking herd productivity is not only commonplace in today’s global pork industry; it has become a critical tool. Whether it’s used to compare how units are performing within an operation, between operations – or between countries – benchmarking is one more way to determine competitive positions.
University of Min-nesota Swine Group researchers, John Deen and Sukumaran Anil, have been looking at benchmarking from a global swine perspective.
“Benchmarking productivity can take a number of approaches and levels,” says Deen.
The first, is to provide internal benchmarking to compare and monitor improvements in an individual herd.
The second, is to compare with herds of similar management and resources, and identify differences between those herds that can signal individual deficiencies.
The third, is to compare herds or systems of unlike resources. This lets producers and their consultants identify strategic opportunities and deficiencies, enabling long-term changes in production methods or expansion plans.
The last level, is to compare industries in different regions or countries. This allows some analysis of strategic opportunities or responses to the resources available in different areas.
“Such analyses are rare, often subjective, and difficult to perform,” says Deen. That’s because pork production data, especially in the grow/finish area, are susceptible to consumer demands, as well as the choice and availability of animal feedstuffs.
The researchers used PigChamp reproductive data in its data-share program for their comparisons. About 45 percent of the herds that are licensed to use this program voluntarily submit their records annually.
Deen and Anil also collected annual average values for production variables involving breeding, farrowing, weaning and the population as a whole from each farm. Herds from Brazil, Canada, Mexico, Thailand, Colombia and the United States were represented.
Farms providing data updates on or after October 2001 were included in the analysis. Herds that showed more than a 40 percent fluctuation in breeding herd inventory were excluded. In the end, the study included 119 operations from Brazil, 36 from Canada, 78 from Mexico, 15 from Colombia, 23 from Thailand and 105 from the United States.
“When comparing such data, a few caveats must be made,” notes Deen. “The first, is that there’s little reason to suggest that the herds participating in PigChamp are representative of all herds in a country. In reality, this database tends to represent the larger and more technologically adept producers.” He points to average lactation length as an example. (See table.) There also may be some variation in the recording methods and inclusion biases by region.
Still, this is the best method of gaining farm-level estimates of productivity over a long period, contends Deen. He offers several observations about the results:
As is typical, there’s a great deal of variation within each group. The standard deviations reported represent a wide variation in reproductive performance. As in most cases, as the mean performance improves so does the standard deviation. This represents opportunities, but also emphasizes that regional differences don’t make up a large part of the causal bases for differentiation.
Statistically, there are many differences between the countries. There are detectable differences in all of the variables that Deen and Anil looked at except for mummies per litter, which ranged from 0.20 to 0.27 piglets.
What’s most distinct is the fact that the United States lags behind other countries in many reproductive areas. Nonproductive-sow days are higher, farrowing rate is lower and sow longevity is lower compared with other countries.
“Most benchmarking is typically done within a country as the expected competition and opportunities should be seen in farm-to-farm comparisons,” says Deen. “The opportunity in international comparisons is to drop out distinctive differences that may result from differences in priorities, resources or simple emphasis due to a lack of expectation within the country.”
Take for example, the fact that high temperatures often are blamed for many reproductive problems. However, that does not explain the United States’ high mortality and culling rates. In fact, some of the lower rates are found in countries with hot climates.
More likely, the higher mortality rate is due to stricter regulations for transporting those animals to slaughter, or a lower value for such animals, says Deen.
The combination of high cull rates – often related to reproductive performance – and the high nonproductive-sow days suggests that labor may be a restrictive resource, he adds. However, the United States needs to look at other methodological differences as well.
“The higher stillbirth rates in the United States are more difficult to justify,” says Deen. “The average herd parity is lower and the temperatures again are lower than in many countries.”
Historically, the United States has promoted itself as having a superior pork production sector – especially when it comes to reproduction. However, according to Deen’s and Anil’s recent analysis, that perception is questionable. Or, perhaps the United States’ exported production techniques and skills are simply employed more effectively elsewhere than they are at home.