FINBIN database: Creating an informational advantage
FINBIN is a great resource for dairy farmers in the Upper Midwest. It lets the user explore the detailed statistics of roughly 400 dairy enterprises from 2008 to 2015. Consistent, reliable and comparable information on farm finances are scarce because it requires farmers’ trust and integrity for handling sensitive data, as well as sustained collaboration networks. The Center for Farm Financial Management (CFFM) at the University of Minnesota has long been a leading provider of farm enterprise statistics service, thanks to its alliances with farmers and farm management instructors in Minnesota and neighboring states.
The rich FINBIN data can shed light on the opportunities overlooked by the mainstream experts and academics. The annual dairy operation data collected by the FINBIN is very detailed. This network of intensive data collection has potential to create informational advantages to dairy farms in the Upper Midwest. Studying data on farmers’ choices and their economic well-being helps create knowledge for others. These data also provide essential insights for research and Extension.
How can we utilize the FINBIN data to learn about successful dairies? First, one can find farms that have competitive incomes in the entire range of operational scales. Table 1 shows the average net income per hundredweight of milk among the top 20% farms in profitability by herd size groups (up to 50 cows, 50 to 100, 100 to 200, 200 to 500, and 500 or more) from 2008 to 2015. While the profit margin varied with fluctuating milk prices and feed costs across years, every year in every herd size category these farms managed to keep the margins well above zero. The regional competitiveness of the Upper Midwest partly rests on how well we learn from these leaders and replicate their success.
Second, one can find successful dairies across various systems. Table 2 shows the farm characteristics and 2015 profitability measures of selected dairy systems among the top 40% or top 60% farms in each group, depending on the availability of data. These producers did well in 2015 in spite of it being a difficult year. I selected comparisons between tie-stall and freestall dairies for the 50 to 200 head category, non-BST and BST dairies for the 200 to 500 category, and non-3X and 3X milking dairies for the over 500 category, as well as highly specialized systems like robotic milking systems and organic dairies. Across systems, successful farms all have a competitive feed cost of around $8.20 ± 0.50 per hundredweight of milk production (with an exception of $13.33 for organic dairies). The labor cost, which includes the hired labor expense and FINBIN’s estimate of the value of management labor, tends to vary with the labor intensity and milking intensity of the system. For example, tie-stall farms are more labor intensive and less capital intensive than freestall farms. Nonetheless, well-managed tie-stall dairies achieve fairly similar levels of milk production (about 23,000 pounds per cow) and farm income ($43,000 per operator) as their freestall counterparts. The medium-scale dairies using BST tend to be larger and produce more milk per cow than their non-BST counterparts (350 vs. 280 cows; 26,500 vs. 24,500 pounds per cow), albeit the profitability per hundredweight seems to vary substantially from farm to farm among these mid-scale farms. Successful large-scale dairies, regardless of whether practicing 3X milking or not, appear similar in their production (25,500 to 26,500 pounds per cow) and profit margin ($1.80 to 1.90 per hundredweight). Successful robotic dairies show relatively high production (25,500 pounds per cow). Successful organic farms excel at managing feed and labor costs and maintaining a relatively high production level (15,500 pounds per cow), compared to their less successful counterparts. The total farm asset varies with the scale of operation, while debt-to-asset ratio is on average maintained at around 35 to 45%, showing the importance of taking appropriate financial risks.
The business intelligence provided by the CFFM creates a strategic advantage for Upper-Midwestern dairy farmers. If you find the FINBIN data to be useful, invite your fellow farmers to join this strategic network. Contributing your data to the FINBIN database helps develop regional advantages through access to precise statistics for research, customized benchmarks for your business, and opportunities to gain new insights from successful peers. The more dairies that decide to participate in the network of data collection, the more powerful the database becomes. In the age of computers and ever larger datasets, there is strength in numbers.
|Year||Up to 50||50 to 100||100 to 200||200 to 500||Over 500||All Farms|
|2015||4.24 (9)||4.04 (37)||4.35 (27)||3.66 (11)||3.16 (7)||3.61 (91)|
|2014||-||7.65 (37)||7.13 (32)||6.37 (16)||7.43 (12)||7.17 (101)|
|2013||4.32 (5)||3.17 (30)||3.16 (32)||3.39 (22)||2.59 (11)||2.96 (100)|
|2012||2.91 (14)||3.34 (37)||3.58 (36)||3.06 (14)||2.75 (5)||3.15 (106)|
|2011||5.77 (18)||4.80 (44)||3.96 (23)||5.39 (17)||5.29 (13)||5.07 (115)|
|2010||3.18 (21)||3.50 (49)||3.68 (32)||4.09 (10)||6.10 (7)||4.52 (119)|
|2009||-||2.26 (29)||1.88 (49)||2.40 (26)||-||3.88 (110)|
|2008||5.51 (26)||4.54 (47)||4.73 (25)||4.66 (8)||-||4.88 (109)|
Source: FINBIN 2008-2015. Calculated year by year. Number of farms in parenthesis. A minimum of 5 farms required per column for the statistic to be shown.