Australasian Agribusiness Review - Vol

In this paper, we assess the potential for rehabilitation of comparative analysis under its new guise of benchmarking. After a brief description of comparative analysis, we discuss the deficiencies that surrounded its fall in reputation: neglect of economic principles, limited scope for action, failure to establish causal relations between farming practices and performance, lack of a holistic approach and failure to take account of production risk. Each of these deficiencies is diagnosed, and it is argued that they can be overcome through the careful selection of farm performance criteria and use of long-established and recent methods of efficiency and productivity analysis. The case is put for widespread application by benchmarkers of recently developed methods of efficiency and productivity analysis. These methods have so far remained almost wholly in the province of research. If successful, their application would enable a benchmarker to examine economic efficiency and its components over many variables by using frontiers to capture the complex relationships between several inputs and several outputs. This form of analysis is useful where farm inputs are not monotonic and where both substitute and complementary relationships exist between them. Examples are provided from benchmarking case studies that show progress has been made in some but not all areas of concern. Regardless of the progress made in methodology, skilled and experienced benchmarkers familiar with the data are needed to interpret and apply results. Antecedents of benchmarking The practice of benchmarking has been developed as a farm management tool for detecting areas where individual producers could increase net operating profit by adopting the methods of their peers who are able to achieve better results. Use of the term, benchmarking, is a relatively recent occurrence; the early form of benchmarking was called comparative analysis (or, less commonly, account analysis). Barnard and Nix (1979) described comparative analysis as the opposite of, and an advance on, cost accounting for decision making on the farm. (Their main criticism of cost accounting in this context was that each enterprise or, our preferred term, activity is treated as a self-contained business.) They summed up comparative analysis concisely when they said that it ‘emphasises the integrated nature of the farm business and its essence lies in calculating various “efficiency factors” or “indices” to compare with standards (average or “premium” figures) obtained from other, similar farms’ (Barnard and Nix 1979, p. 524). Although written over a quarter of a century ago, this definition adequately describes the usual benchmarking approach applied in Australian agriculture today. Outputs and costs are usually calculated for comparative analysis on a per hectare basis, or sometimes on the basis of some other factor of production such as labour. Calculations incorporate adjustments for opening and closing values, and the addition of non-cash items of receipts and payments. Net output figures are used to account for internal transfers between activities, such as feed produced from crops that is used in livestock production (Barnard and Nix 1979, p. 527). Reasons why comparative analysis was consigned to oblivion Around the time that Barnard and Nix (1979) and many other critics were writing, it was becoming clear that comparative analysis had some major inadequacies as a decision support tool for farmers. Five broad criticisms were particularly damaging to its reputation: • It failed to incorporate sound economic principles in its application. • There was limited scope for action once indices were calculated. • The approach failed to establish causal relations between farming practices and performance. • It was not consistent with a holistic approach to farm decision making. • Risks and uncertainty in farm decision making were neglected. We now outline these inadequacies and present a case for making its reincarnation in the guise of benchmarking as a legitimate tool in agribusiness analysis today. Inadequacies of comparative analysis as a decision support tool for farmers Neglect of economic principles The most damaging criticism of comparative analysis was its neglect of economic principles. If it is assumed that the major objective of the farm is to maximise profit, comparative analysis should reflect sound economic principles of optimal resource allocation if it is to have value as a decision-making tool. Yet traditional comparative analyses have little to say on this key issue. Malcolm (2004, p. 396) lambasted research and development organisations in Australia that ‘have invested substantial funds in conducting large scale “average benchmarking” or comparative analysis studies with onfarm diagnostic and prescriptive intent’. State departments of agriculture were also the targets of his criticism, in that they ‘have invested large amounts of resources over long periods of time conducting comparative analysis for farm management’ with little payoff. Malcolm (2004, p. 401) posited that economics is the core discipline of farm management, meaning that ‘the discipline organises the practically obtainable relevant information about a question or series of questions into a framework and form which enables an informed, reasoned, rational choice to be made between alternative actions faced by management’. Without its contribution, results from comparative analysis have little prescriptive value. Limited scope for action In comparative analysis, producers were typically categorised into fractiles according to a given performance measure, such as in the top quartile, bottom quartile, top half or middle 50 per cent of producers. Farmers who were above average had little to learn from any comparisons with other farmers in the sample. They had even less to learn when they were told that they lay in the band of the top 25 per cent (or an even smaller proportion) of farms. Such crude rankings provided little help in diagnosing producers’ problems and providing targeted management advice. Lack of a holistic approach A comparative analysis of farms was typically focused on a series of partial performance measures. Individual producers were categorised according to their relative standing across all producers included in the sample according to each partial measure, such as yield or stocking rate. A chronic problem with this approach was the absence of a standard against which to measure the farm performance of each producer. A more serious problem identified with partial performance measures was that they conveyed information on only one, often small, part of farm performance. A more comprehensive measure was needed to get an accurate picture of whole-farm performance. The approach that came closest to achieving this aim was to rank producers according to their overall net operating profit, which was a comprehensive measure of performance. However, by itself it did not convey information about the relative performance of each producer for benchmarking purposes. Some producers were likely to have many more resources at their disposal than other farmers, so such a comparison would show farmers who operate on a small scale to be less profitable, and hence performing less well, when that might not be the case. This problem led analysts to scale profit according to one or more of the resources that producers use on their farm. Each measure provided a single profile of producer profitability according to the level of use of one farm input. The most popular such measure used was profit per hectare of land; another was profit per man-day of labour. Two other common measures related to return on capital: operating profit as a percentage of equity and operating profit per dry sheep-equivalent. Comparisons across producers were still invidious because producers undertook different farm activities to varying degrees. The difficulty (some would say, with some justification, impossibility) of allocating overhead operating costs across a number of different farm activities led to a ‘short-cut’ measure being used for profit, namely gross margin. Performance measures used as a consequence of following this approach include gross margin per hectare and gross margin per man-day of labour. There was still a major problem of partial profit measures of performance, as demonstrated in the following simple example for a single farm activity. A producer with a relatively high gross margin per hectare may be using many more non-land resources than another producer who has a relatively low gross margin per hectare. Of course, analysts could then look at the other partial gross margin measures and, indeed, may have found that the second farmer had a much higher gross margin per man-day than the first producer. They could continue this approach until gross margin rankings by producer were obtained against all possible farm inputs (even gross margin per dollar of a particular chemical used if they wished). It then might be possible to say something about their relative performances if one producer out-performed another producer in all measures. But this is unlikely, and not very useful when measuring relative farm performance across many producers and trying to develop prescriptions for improved farm performance. Lack of consideration of the variability in production and risk, and its