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The project was designed in conjunction with benchmarkers to develop a rigorous method for analysis of their data and to determine key performance indicators of the profitability of a variety of sheep production systems. Technical efficiency was estimated, which relates all outputs to inputs, and used principal component analysis to identify the most important performance indicators that influence technical efficiency. Productivity for wool enterprises was measured over several seasons, which ranged from very bad to excellent, and varied by up to 30 % between farms. The annual improvement in productivity was about 5 % for best-practice producers, while the average technical efficiency of less efficient producers declined by 1,4 to 2,8 % per year. Principal components analysis indicated that maximum technical efficiency in south-western Victoria was associated with sheep with slightly finer wool and lower fertility than average, suggesting that emphasis was placed on a higher stocking rate and more wool per ha. Technical efficiency estimates afford producers a more balanced indication of their relative performance than was previously possible. When used in combination, the principal component analysis and regression analysis represent a powerful tool for diagnosing problems and exploiting opportunities for improved income in Merino wool enterprises. It was concluded that comparisons of technical efficiencies across a range of environments are not effective and that more sophisticated statistical methods required for this purpose.