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U.S. 2007 – 2012 Pork Industry Productivity Analysis

U.S. 2007 – 2012 Pork Industry Productivity Analysis. C. E. Abell 1 , C. Hostetler 2 , and K. J. Stalder 1 1 Iowa State University, Ames, IA 50011-3150 and National Pork Board, Des Moines, IA 50325. 2013 Pork Academy Des Moines, IA June 5 & 6 , 2013 . Data Description.

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U.S. 2007 – 2012 Pork Industry Productivity Analysis

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  1. U.S. 2007 – 2012 Pork Industry Productivity Analysis C. E. Abell1, C. Hostetler2, and K. J. Stalder1 1Iowa State University, Ames, IA 50011-3150 and National Pork Board, Des Moines, IA 50325 2013 Pork Academy Des Moines, IA June 5 & 6 , 2013

  2. Data Description • Production data obtained from a large U.S. data record keeping organization • Agreement with the National Pork Board to share limited information. • Uses: • Quantify the annual production levels and variation associated for several key productivity indicators • Establish industry benchmarks for all swine production phases • Breeding herd • Nursery • Wean – to – finish • Conventional finishing

  3. Data Description • Production data obtained from a large U.S. data record keeping organization • Agreement with the National Pork Board to share limited information. • Uses: • Quantify seasonal affects associated with the key productivity indicators • Identify research opportunities that would improve the U.S. pork industry production efficiency

  4. Data description • Statistical process • Industry Trends • Raw means and standard deviations were used • Seasonality evaluation • Linear model was used • Fixed effects • Company • Month • Year • Covariates – for nursery, grow-finish, and wean-to-finish • Start age • Start days • Days in facility • Covariates – Sow farm • Weaning age

  5. Data description cont’ • Data (records) reported monthly for each production phase • Nursery and finishing data – • Monthly averages are based on animals exiting the facility that month • Sow farm data – • Monthly averages are based on litters weaned in that month

  6. Company / farm summary • Increase in the number of companies and farms represented • Tremendous increase in the data volume evaluated • Results in improved information and interpretations that can be made • Companies becoming much more data driven in their decision making process

  7. Company / farm summary • Grow-finish and wean-to-finish becoming farms becoming more like their sow farm counterparts • Farm level decisions much more data driven • Continue greater use of data when guiding company decision process regarding: • Employee • Financial • Health • Nutritional • Genetic • Some combination

  8. Benchmarking - What is it? • Definition of benchmark: a standard of excellence, achievement, etc., against which similar things must be measured or judged (Dictionary.com) • Definition of benchmarking: the process of using benchmarks to identify areas for improvement, strategies to achieve improvement and implementation of those processes (Common Industry)

  9. Why do we do it? • Compare with other businesses • Within species • Across species • Compare herd performance • Within company • Within country • Etc. • Set goals for improving herd • For a specific trait or several traits

  10. Overall Averages

  11. Key productivity indicators • Sow farm KPIs • Pigs/mated sow/ year • Litters/mated sow/year • Total born • Still born and mummies • Number born alive • Number weaned • Pre-weaning mortality % • Weaning weight • Weaning age

  12. Key productivity indicators cont’ • Nursery KPIs • Nursery mortality % • Nursery out weight • Days in nursery • Nursery feed conversion

  13. Key productivity indicators cont’ • Conventional finishers and wean-to-finish facilities KPIs • Finisher (wean-to-finish) mortality % • Finishing weight • Days in finisher (wean-to-finish) • Finisher feed conversion (wean-to-finish)

  14. Key Productivity Indicator Averages • Means and standard deviations across all farms and operations. • Sow, nursery, wean-to-finish, and conventional grow-finish data • Developed to examine yearly trends across the U.S. Swine industry. • Operations can compare one or a number of KPIs to see if they are above or below average

  15. Overall data summary • Finishing mortality has declined over time while market weight has continued to increase • Improving mortality by 2% for a 1000 hd. finishing facility would be equivalent to adding $3,240 each barn turn assuming 270 lb. market hog and $60/cwt. • Days in the finisher have remained relatively constant over time • Average daily gain has increased slightly over time • Feed conversion has improved slightly across both finishing facility types

  16. Overall data summary cont’ • Nursery performance has change little across the reporting time period • Pigs/mated sow/ year has increased by almost 2 pigs from 2007 to 2012. • Litters/mated sow/year has changed little during the time period • Most of the improvement in PSY is a result of improved litter size • Some of the PSY increase is greater stillborns and mummies • Number weaned has increased by 0.8 pigs

  17. Overall data summary cont’ • Percent pre-weaning mortality has increased. • Represents lost opportunity • Easy to improve?? • Weaning age has increased by 2 days from 2007 to 2012. • Weaning weight has increased by 1 lb.

  18. Plots of Averages

  19. Description of figures • Figures 1 -24 graphically depict the change for the top 25%, overall, and bottom 25% for each KPI for the 2007 to 2012 time period. • Top 25% represented by red lines • Overall average represented by black lines • Bottom 25% represented by blue lines • More easily view the rate of change for each KPI across the 2007 to 2012 time period

  20. Figure summary • KPIs are changing at the same direction for all three groups • Each group slope or rate of change may slightly differ • Examples: • Litter size averages have increased at almost the same rate across the top 25%, overall average, and bottom 25%. • Litter size limit not reached yet for any group

  21. Figure summary cont’ • Examples: • Percent finisher mortality variation among the 3 groups has changed substantially across the 2007 to 2012 time period for the three groups. • Result from increased importance or focus placed on reducing mortality by owners, barn managers, and barn workers • New vaccines • Better herd health status

  22. Seasonality Estimates

  23. Seasonality graph description • Least squares means were used to obtain the month estimates using the model previously described.

  24. Seasonality graph • Graphs clearly show the months when decreased performance occurs for each KPI • Decreased performance represents substantial productivity and economic losses for the US swine industry • Identifying causes and methods to mitigate seasonality effects on the KPIs would have a large economic impact on the entire swine industry.

  25. Seasonality graph cont’ • In general lowest finishing performance was seen during the summer months • Sow farms had the lowest production during winter months (sows experience hot weather and then express the effects during the winter months). • Except for nursery mortality, seasonality has less impact on nursery performance relative to other production phases.

  26. Summary • The US swine industry has been successful at improving production efficiency • Some traits (mortality) still represent future opportunities • Increasing the pounds of pork produced in a given period of time and reduced finishing mortality has improved finishing throughput. • Combining improved litter size and pounds of pork produced, the throughput of the US swine industry has increased as a whole.

  27. Summary • Key productivity indicator trait improvements may be the result of – • Better genetics • Improved health • Superior management • Other • The results from this analysis can be used to determine when management practices need to be improved and/or maintained to ensure optimal performance level for each swine production phase.

  28. Thank you for your time and attention ! Do you have any questions or comments?

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