As part of Defra’s plan to become ‘open by default’, the first datasets relating to milk production have just been released. These include information on milk prices and composition, milk utilisation by dairies and estimation of dairy farm greenhouse gas emissions. As yet, there is surprisingly little information about trends in herd health and productivity.

Within the dairy industry, data are being collected at all levels of the supply chain: from the laboratory bulk milk analysis, the feed analysis, the farm records and veterinary interventions and prescriptions. Potential future sources of data may come from automated milking machines, pedometers and lameness force plate analysis. Integration of these different data streams could provide the information to move the whole industry forwards. The question is how to ensure alignment of incentives and ensure that value is realised for every stakeholder along the value chain, to ensure that these datasets can be used effectively.

There is exciting potential for such data use. Correlating food quality, food safety and animal welfare with measurable farming inputs provides a standard metric for all farms, and can be used to reward and incentivise good farming practice. Additionally, this standard enables clearer communication with consumers, which can be used to leverage premium prices.

A useful comparison is the changes in egg production in the UK: where public awareness of the conditions of battery hens drove industry change. Consumers deliberately selected eggs from non-caged farming systems, as these were perceived to provide better welfare for the layer hens. However, consumer awareness of health and welfare problems related to current dairy farming practices is low.

Increasing data use in the dairy supply chain is stymied by low levels of trust between the main stakeholders. Rightly there are concerns about data ownership, disruption to the value chain and the use of information from big data to slant the balance of commercial relationships between farmers, their suppliers and their customers.

Good animal health and welfare has an economic importance. Lower levels of disease leads to lower levels of antibiotic use, less animal suffering and reduced loss of income from diseased stock. Learning what consumers are prepared to pay for could be really valuable to the dairy industry.

If the hurdles to better data use can be overcome, big data analysis has the possibility of transforming the dairy sector – improving the health and welfare of the animals, reducing the financial and animal costs of the farming process, and improving overall productivity.