Data systems for monitoring animal welfare outcomes on farms and in other settings are essential for evidence-based improvement, but significant gaps remain in data collection and use.
Effective animal welfare improvement depends on reliable data about welfare outcomes across populations of animals. Traditional welfare monitoring based on periodic farm inspections is expensive, inconsistent, and unable to detect problems between visits. Precision livestock farming technologies — including automated behaviour monitoring, weight tracking, and feeding pattern analysis — offer the potential for continuous welfare surveillance that catches problems early. However, data systems are only valuable if they lead to action and improvement. Sector-wide aggregation of welfare outcome data, combined with transparent reporting, would accelerate learning and drive standards improvement across the industry.