This is the 80th monthly column written for National Hog Farmer’s Weekly Preview. This monthly exercise has forced us to look at production data in new ways and to dig deeper into our database. We have learned a great deal in this process.
As a result, we have written a new Swine Management Services (SMS) benchmarking program that incorporates some of the knowledge we have gained over the last four years. This new program will retain everything that is in the current farm benchmarking program, plus new parity benchmarking reports and charts. This will help us analyze all 800 farms in the database by parity vs. the 130 farms in the SMS production analysis database used previously. This new program will be rolled out at World Pork Expo (Thursday, June 6 at 1:00 and 2:30 p.m.) in the Walnut Center on the Iowa State Fairgrounds.
For this article, we will focus on four of the new parity benchmarking charts:
· Chart 1 – Parity Structure: Compares a farm's parity structure to the SMS database.
· Chart 2 – Culling Percent: Compares farm’s culling rate to the SMS database.
· Chart 3 – Death Loss Percent: Compares farm’s death loss to the SMS database.
· Chart 4 – Retention Percent: Provides retention rate to the next parity.
Farm parities will be listed as P0 (unbred), P0 (bred), P1, P2, P3, P3, P4, P5, P6 and P7+ (Chart 1), with corresponding inventory for a farm vs. the composite of the farms in the database. Whether this will be the ideal parity structure for improving performance we do not know. We’re still learning.
Chart 2 compares the culling rate of a farm to culling percentage of the database, by parity. If culling rates for younger parity females are hurting farm performance, this chart will help producers address that issue. Total culling rate is not a good comparison between farms because it is totally dependent on when the gilts are entered into the database. Farms entering the gilts 120 days before the first service will have a higher culling rate for gilts and push the farm’s culling rate higher. That is why it is important to begin looking at culling rate by parity.
In Chart 3, the farm’s female death loss percentage is broken down by parity. This farm’s P1 death loss is 1.3% vs. the SMS database at 1.8%. Again, total female death loss is not a good indicator for comparisons between farms. Farms entering the gilts 120 days before the first service will have a higher death loss percentage for gilts and a higher overall death loss. That is why it is important to look at death loss by parity.
Finally, Chart 4 was developed to examine female retention rate, by parity. Retention rate is the percentage of females that make it to the next parity.
Currently, we look at P0 through P 7+, but we may remove gilt culling and death loss rates going forward to eliminate the variation caused by entering gilts into the record program at different times.
Genetic costs are the third-highest cash expense on a sow farm, behind feed cost and labor. As an industry, we need to keep working on increasing lifetime performance of females to help lower the genetic costs. We are excited about the capabilities of the new SMS benchmarking program because it will allow us to analyze more farms, therefore gain new knowledge.
Past “Production Preview” columns can be found at www.nationalhogfarmer.com. Click on “newsletters,” then the respective date of the Weekly Preview issue you are interested in.
Key Performance Indicators
Tables 2 and 3 provide 52-week and 13-week rolling averages for key performance indicators (KPI) of breeding herd performance. These tables reflect the most current quarterly data available and are presented with each column. The KPI’s can be used as general guidelines to measure the productivity of your herd compared to the top 10% and top 25% of farms, the average performance for all farms, and the bottom 25% of farms in the SMS database.
If you have questions or comments about these columns, or if you have a specific performance measurement that you would like to see benchmarked in our database, please address them to: email@example.com firstname.lastname@example.org.
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