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Deciphering dairy data

Randall Greenfield Published on 06 November 2015

I grew up on my family’s dairy farm in southern Wisconsin. I remember when one of my older brothers started recording each cow’s calving information in a notebook.

We wrote down the dam’s ID (the number on her small, originally orange, metal eartag from her brucellosis vaccination). If that had been lost, we recorded some obvious physical characteristic, possibly combined with a genetic description (such as Big White Chief-Mark Cow).

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We also included the date of calving and the sex of the calf. This system proved to be very useful in culling and breeding decisions (How long has Alice been milking?) as well as having accurate data for 4-H project animals.

With a lifetime fascination of data, I recall learning Lotus 1-2-3 spreadsheeting in my first year at college, followed by some Quattro Pro, and nearly falling in love with these software programs. I wrote a small, simple spreadsheet to accomplish the same thing as my brother’s notebook … but more. I could calculate a cow’s days in milk (DIM) and, if we recorded breeding dates, we could project due dates and dry-off dates – the possibilities were mind-boggling.

Many producers aren’t quite as likely to get as excited about data and spreadsheets as me, but I think we can all appreciate the value in tracking our herds to best manage their health and performance.

Of course, today things are different and much more advanced than our original tracking system. We not only have sophisticated software packages to manage cows’ lactation events, but we’re also tracking individual cow daily milk production, activity and rumination.

We can identify a cow with radio frequency via a little button on her ear and monitor feed inventories and intakes by pen. We can pull some of her hair out, send it off to the lab and receive a report with her genetic profile. Satellites auto-steer our tractors and help to variably apply fertilizers and herbicides.

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Furthermore, today on our dairies we are discussing the possibility of installing equipment that will allow us to know the component concentration of each cow’s milk at each milking and her real-time bodyweight and body condition score. We may even use cutting-edge instruments that will tell us our cows’ body temperature, rumen pH and other potentially useful real-time metabolic data.

With so many tools at our disposal, stepping back and looking at how far we’ve come – and where we could go – can be somewhat overwhelming.

Which pieces of data are valuable to your business and can help you make better decisions? How big of an impact could they have? How much should you be willing to pay to get such information? More and more dairy producers are asking these questions.

Finding value in your data

Are you using your data to make decisions on your dairy? Is your team helping you pick out the key measures most important to your business?

Part of my job with my dairy clients is to summarize performance data and use it to help them answer questions. We use both external and internal benchmarks for judging success, but the progress measured against history is the most valuable.

From my experience, the most valuable measures of dairy performance in my arsenal are:

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  • Pounds of combined fat and protein produced per cow per day for any given time period: I like to measure this and many others on a rolling-year basis to see if we’re making progress and to remove any seasonal effects. Pounds of fat and protein make up the majority of milk income for dairy producers in the upper Midwest.
  • Milk basis, which is the difference between the dairy’s pay price for milk and the Class III benchmark, is valuable in gauging financial performance. This metric, when evaluated with combined fat and protein produced, really drives the revenue side of the dairy business.
  • Turnover rates are calculated for the whole herd as well as for segments of the herd (for example, first-lactation animals and fresh cows less than 61 DIM). Different types of turnover are also monitored, including dairy turnover (excess cattle sold to other farms) and deaths (both on adults and youngstock). Typically, lower rates in this department are considered more desirable, though overall turnover rates could be high due to high replacement rates.
  • Metabolic disease rates, including rates of displaced abomasums, milk fevers, retained placentas and ketosis, are also calculated as rolling annual rates. These can be good indicators of the transition program’s success in getting fresh cows off to a good start.
  • Reproductive efficiency – primarily measured by pregnancy rate – is monitored for both youngstock and adult herds. Higher stats here lead to shorter calving intervals and more replacements. Very high pregnancy rates can be a potential liability, however, if you have no plan in place for the dairy to profit from the extra replacements. Higher pregnancy rates in the youngstock herd can lead to fewer days on feed and lower replacement costs.
  • Labor costs per hundredweight is an area of current challenge for many dairies in the upper Midwest. Labor supplies seem to be shorter, and compensation demands are higher. Efficiency is more important than ever.

You’ll note that my short list of key measures does not yet include many of the newest technology-derived data on the horizon. I tend to be a skeptic. (It’s getting more obvious as I age.) As I look at the sea of potential new data sources, I’m hopeful, but not 100 percent sold on all of the new technologies’ value just yet. Many of the new options are “cool” and intriguing, but be sure to ask the most important question: How will this investment pay for itself?

The new technologies may also have other challenges. As more types of data become easier to obtain, we will need systems to assimilate the data into useful forms for decision-making. Standard formatting will be key to allow the industry to move forward in this area so that the information can be measured, compared and discussed.

How will the new data get incorporated into existing systems? As an industry, we’ll be challenged to work together to standardize our data platforms and allow different systems to talk to each other.

So for now, the strategy remains simple. Work with your team to identify the key measures that have a real and significant impact on your herd’s health and your farm’s financial performance. Figure out how to record them and track them over time. PD 

Randall Greenfield
  • Randall Greenfield

  • Dairy Technical Specialist
  • Vita Plus Corp.
  • Email Randall Greenfield

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