The days of collecting volumes of data from your swine operation and wondering what to do with it “someday” are largely past.
In 2026 it’s possible to crunch standard data points on pigs, and even additional specialized data, to come up with a whole operations picture that assists producers with faster, even more efficient decision-making. This translates to more accurate financial records to satisfy bankers and partners and help veterinarians solve or prevent health issues, as well as giving management the ability to focus more pointedly on big-picture plans for future return on investment.
But sharp, well-informed analytics is not possible without a solid foundation of accurate production records – which is also integral to the future of automation and artificial intelligence assistance for swine producers.
It is vital that the information a producer is amassing from their operation is clean and consistent, to build the best records database. A prime way to ensure this, is for the people collecting the data to enter it into your collection system in real time, or as close to real-time as possible.
Obviously the day-to-day work of pig production is going to be a producer’s, farm manager’s, or barn employee’s main priority. With that in mind, you can see it’s easy to get caught up in other immediate tasks and not finish entering all the data at the time you’re collecting it. You may think, “I can finish this in a little while; I’ll remember.”
Nobody believes they will forget important information, but waiting a few hours or longer to enter data from memory or incomplete or confusing notes means there is a high likelihood the information could indeed be forgotten – or at least misunderstood. If you are not consistent in entering data in a timely manner, it is less likely to be clean, accurate and useful.
Say you get most of a morning’s data entered correctly but are inaccurate on even one or a few points; that mistake can compound over time. This might impact how quickly you recognize a health issue in one or more animals and delay a critical response, eventually affecting the whole herd and costing extra in treatment and mortality. Conversely, inaccurate data could distort the picture of your healthy animals and create unnecessary concern and expense.
There are two ways we help producers ensure they are recording this clean, consistent data. First, we work with a farm’s team to help them learn not just how to collect and enter data, but the ways in which it’s so important to the operation.
As I noted above, it’s easy to view data collecting as a distant or optional second responsibility to caring for the pigs. So we show them how the data is used to influence those day-to-day decisions, and why the quality of data matters to the speed of the farm being able to pivot on critical health or real-time financial information.
Second, we help producers understand the features of the data they can and do collect, based on the goals for their operation. There are different types of data collection software you can use, and each one has certain parameters you can choose to deploy.
For example, most sow farms collect basic, standard types of data on each animal such as vaccination, breeding date, farrowing, live-born, weaning and return to estrus. Some producers like to get much more detailed – such as recording every movement of the animal, specific genetic lines used in breeding, every medicine administered, total born including stillborn and more.
When it comes to pig data – any data – it’s not only about what you collect, it’s about how accurate it is.
Part of what we do is to help producers make certain they are collecting the right data to inform the details of decisions important to their operation. I talk periodically with current producers to review the value of their data and records. We discuss if they are collecting the proper data, enough data – or too much. There is a difference between data, and data that matters.
One thing I sometimes encounter are producers who want certain insights but don’t know the type of data to collect, or they presume there’s no way to glean that information from data they’ve already collected. Or, they don’t realize their software can collect particular data – on health, management practices, performance or even environmental factors – to inform even more detailed decisions.
These are good problems to encounter because it means I can help them view data in a whole new light, and we can make their operation more efficient, profitable and meaningful through advanced technological tools in the long term!
