Dive Brief:
- Arla Foods has artificial intelligence software to better estimate how much milk 1.5 million cows belonging to 10,300 farmers will provide in the future. The Denmark-based cooperative said in a release about 440 million pounds of milk annually can now be used more efficiently and sustainably using this AI tool.
- Before developing the software, company personnel would have to make manual calculations on Excel spreadsheets. The task can now be done in a few hours and is 1.4% more accurate than the previous system, the company said.
- The software is being used in all of Arla's European markets, including Denmark, Germany, Sweden, the U.K., Belgium, Luxembourg and the Netherlands.
Dive Insight:
Like many dairy producers today, Arla is doing whatever it can to maximize efficiencies and make sure profits and sustainability are at the highest levels.
As the largest dairy company in the U.K. — and with thousands of farmer-owners as members — replaing the the labor-intensive method with high-tech tools is practical.
The AI forecasting tool isn't the only forward-looking approach the dairy cooperative is taking. In 2017, Arla automated some of its cheese-making procedures in Denmark and started using robot arms equipped with sensors to milk cows. With plant-based competition stealing consumers in the global marketplace, the company opted for efficiency.
The new software will allow Arla to predict how much milk will be produced by factoring in a number of variables. These include seasonal changes, how many farmers are converting to new types of milk, geographical aspects and how much milk farmers are producing each day. Consequently, the company said it is now possible to determine the amount of milk expected from farmers in different parts of the world several months in advance.
There are also transportation and environmental advantages. By planning ahead, companies can reduce cost and reduce carbon dioxide emissions.
It's likely other dairy companies will investigate AI technology and find ways to implement more sustainable production practices.
