Critical control points for profitability in the cow-calf enterprise

Professional Animal Scientist, Dec 2001 by Miller, A J, Faulkner, D B, Knipe, R K, Strohbehn, D R, Et al

Cull BW was correlated with cull price and weaning percentage (P

Reproductive Efficiency. The average producer had a weaning percentage of 83%. This was similar to data reported in Colorado [84%; (9)] and Texas [82.9%; (14)]. A SD of 8% indicated that 68% of the herds had a weaning percentage between 75 and 91%. Thus, there was less variation in the reproductive performance of these herds than in the cost data. McGrann (13) reported only a two percentage point (84% vs. 82%) difference for weaning percentage between producers in the high net income quartile and those in the low net income quartile of the Texas SPA database.

Weaning percentage was correlated (P

McGrann (13) reported that calf BW weaned per exposed female accounted for 7% of net income differences between herds. Combining weaning percentage and calf BW values from this study resulted in a similar outcome.

An evaluation of calving distribution was made by summarizing data for the percentage of calves born in the first 42 d of the calving season. The average for all observations was 81% with an SD of 14% (Table 1). Calving distribution was positively correlated (P

Investment. Investment measured on a market basis ($2,350) and on a cost basis ($1,560) was somewhat lower than investment figures reported in Texas [$3,355 and $2,276; (14)]. This was because of the enterprise analysis approach taken by this program. Producers often utilize equipment and structures in other farming enterprises. Allocating a percentage of equipment to other enterprises effectively lowers the investment for the cow-calf enterprise and may illustrate the complementary economic relationship of multiple enterprises.

Investment measured on a cost basis remained constant across years. Investment measured on a market-- value basis tended to increase from 1996 to 1999, as would be expected because commercial cow values increased. Investment was not a significant variable in either regression model. However, it was highly correlated with a number of the significant cost variables. Depreciation was highly correlated (P

Herd Size. Economies of scale have often been reported to exist in the cow-calf enterprise (10). Investment was negatively (P

Herd size was negatively correlated with family labor (P

The negative coefficients in the prediction equations for herd size (-0.17 financial; -0.32 economic) suggested advantages for a smaller producer (Tables 5 and 6), if they are able to manage the first factors. This might be difficult given the negative correlations observed among herd size and feed cost, operating cost, depreciation cost, and capital charge, as well as the positive correlation observed between calf price and herd size. It does indicate that small producers who manage these factors may have an advantage over large producers in matching their operations to their resources. These data indicated that economies of scale exist primarily in the form of reduced feed and operating costs.

Implications

The average cow-calf producer operating in Illinois or Iowa from 1996 through 1999 had a negative RLM. Cost factors were far more influential in driving RLM than production, reproduction, or producer-controlled marketing factors. Of these cost factors, feed cost had the largest impact. Smaller producers were not competitive in feed, operating, or investment costs and should hire custom machine operators rather than own leveraged equipment. Larger producers also received higher prices for their calves. The large herd-- to-herd variation seen for many cost factors indicates that many producers can dramatically improve their profitability by finding ways to lower production costs. As producers focus attention on factors that affect the profitability of the operation, feed cost was the most critical control point because it was responsible for over 50% of the herd-to-herd variation in profit.