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Abstract
Agricultural benchmarking and input optimisation are ripe for further development using tools that are now freely available for manipulating larger volumes of data. These new systems will not replace existing benchmarking methods but, used carefully, add another dimension to help improve profitability. These techniques are beginning to merge systems used to derive agronomic optimums, such as random block replicated trials, and farm management analysis based on use of comparative data to relate inputs and outputs to target metrics, such as profit. However, mapped data while providing considerable scope for improving farm management practice is often badly analysed allowing incorrect conclusions to be reached. Data analysis is not a substitute for innovation.