Benchmarking sustainability performance in UK free-range laying hen flocks

CONTEXT
To equitably nourish the world’s growing human population whilst halting further transgression of the planetary boundaries, there is a need to evaluate the relative performance of food and farming systems in terms of multiple and often competing food security, environmental and ethical sustainability objectives.
OBJECTIVE
We aimed to benchmark the sustainability performance of 80 free-range laying hen flocks in England and Scotland, in production between 2016 and 2022, and to identify any common characteristics between the best performers to inform supply chain policy. Benchmarking was based on multi-criteria efficiency scores, incorporating six input and two output criteria covering human, animal, and environmental domains, including the neglected measures of animal welfare and antibiotic use.
METHODS
Data Envelope Analysis (DEA) was used to derive efficiency scores. Univariate and multivariate regression analyses were then applied to explore production factors that could be associated with the attainment of maximum efficiency.
RESULTS AND CONCLUSIONS
Approximately half of the flocks attained the maximum efficiency score, relative to their peers. Analysis of their component inputs and outputs demonstrated the favourable performance of the most efficient flocks across a broad array of criteria compared to inefficient flocks, indicating that some farms are successfully reconciling production and profitability with superior environmental, animal welfare and antibiotic use performance. Univariate analysis and multivariate regression revealed no statistically significant predictors of efficiency at the level of p<0.05, with unexplained variation in relative efficiency scores of the flocks of between 0.7 and 1.0, indicating a path of improvement amongst farmers with similar production systems and standards, potentially based on unmeasured human factors. However, univariate analysis revealed an association between laying hen breed and the attainment of efficiency at the level of p<0.1, supporting the notion that breeds with balanced genetic merit will play an important role in food systems seeking to mitigate externalities of production.
SIGNIFICANCE
DEA allows multiple sustainability dimensions to be combined into a single performance metric to benchmark and compare production units. It offers a method for industry and government to identify potential leverage points to incentivise improved performance, and is a basis for better data collection in relation to both market and non-market (external) cost impacts of production, including animal welfare and antimicrobial use.