Efficiency is a word that conjures up organisation, order, planning, logic, even cleanliness – it also brings to mind effectiveness, productivity and profitability. We talk of fuel-efficient cars and aircraft, energy-efficient homes with better insulation and LED lights, and making food production more efficient. Food and Agriculture Organization Director-General José Graziano da Silva, speaking at the Global Forum for Food and Agriculture earlier this year, stated that “the food systems of the future need to be smarter, more efficient”, by which he probably meant they need to produce more food with less water, energy and land. In other words, we need a food system with a lower ratio of units ‘in’ to units ‘out’. But which units should we be measuring and how many different ‘ins’ and ‘outs’ should we include in our analysis of efficiency?

In a new paper entitled Lean, green, mean, obscene…? What is efficiency? And is it sustainable? published by the Food Climate Research Network (FCRN), the authors tackle this question head-on by exploring the term ‘efficiency’ as it relates to aquatic and land-based animal production and consumption.

They start by providing an overview of various ways of expressing efficiency when it comes to animal production, the most common being the ‘feed conversion ratio’ – the ratio of feed inputs to food outputs (in the form of meat, milk, eggs and so on). But things quickly become more complex once undesirable outputs, such as greenhouse gas emissions and soil and water pollution, along with the negative impacts of producing some of the inputs (for example, nitrogen fertiliser), are included together with the ‘useful’ inputs and outputs. Following this thinking, efficiency, according to the FCRN paper, then becomes “a measure not just of the desired outputs relative to inputs but also of the desired outputs relative to undesired outputs or impacts” (p.5).

The concept of efficiency allows us to understand the relationship between inputs and outputs in a production system and therefore offers us a tool to evaluate one production system against another, but it also hides the fact that some inputs and outputs are either unquantifiable or extremely hard to measure accurately (for example, the social and cultural value of a production system).

An important example of the complexity of applying an efficiency lens to a food production system is that of animal production. At a simplistic level, eating animals that have eaten plants seems inefficient. Humans should eat the plants directly themselves thereby saving a great deal of energy, land and other inputs. This is often part of the narrative that anti-meat advocates use to campaign against animal farming. But what about the nutritional value of animal products, the environmental benefits of (non-intensive) livestock farming, the ‘metabolic miracle’ of ruminants converting unirrigated, unfertilised pasture into valuable foods and other products (leather, wool, bone meal), all the while increasing biodiversity and helping to support rural livelihoods and maintain traditional land-based skills?

Following the logic of efficiency, meat production has moved towards greater intensification and specialisation of production, which by some measures reduces the carbon footprint per unit of food output compared to extensive livestock production. But the picture is quickly complicated by evidence that grasslands used in extensive farming systems act as carbon sinks, and intensively reared livestock is fed on crops grown on previously forested land. Demand for soya is a significant driver of deforestation and therefore of emissions related to deforestation – factors that are usually not included in the carbon footprint analyses of farm systems. Which brings us back to the original question of which inputs and which outputs to include in the efficiency equation and how far back along the ‘Life Cycle Analysis’ chain should one go for a more accurate estimate?

A good example of how different efficiency lenses produce different results, comes from a research paper by Weiler et al. (2014) entitled Handling multi-functionality of livestock in a life cycle assessment: the case of smallholder dairying in Kenya. Comparing a conventional intensive dairy farm with a smallholder dairy, the authors find that the conventional dairy farm performs better than the smallholder farm when solely food outputs (meat and milk) are included in the efficiency equation. Once other outputs are included, such as the manure for fertiliser, the finance and insurance provided by the cattle, and the non-tangible value that the cattle hold in the farmers’ lives, the carbon footprint of the smallholder farm becomes much more similar to that of the intensive production system.

The main challenge facing researchers and policy makers that are making use of tools such as Life Cycle Analysis to measure and compare the efficiency of farming systems is to account for all the linkages between inputs and outputs, impacts and benefits across a wide range of categories. Slightly sidestepping this challenge, and offering a “re-orientation of the discourse”, the authors of the FCRN paper suggest that we start thinking instead about effectiveness. They conclude their wide-ranging analysis of efficiency by stating that: “Effectiveness – which we deliberately do not define – simply by shifting the emphasis onto ends rather than means, enables us to talk openly about our values” (p.48).

Values clearly need to be an important part of the analysis, given that part of the problem with measuring efficiency lies in quantifying the unquantifiable or non-tangible. But let’s not throw the efficiency baby out with the bathwater of complexity. Great advances have been made, and continue to be made, by people working on measuring the inputs, outputs and impacts of various farming systems. For example, the European Nitrogen Assessment, which recently estimated the overall environmental costs of all ‘reactive nitrogen’ losses in Europe at €70–320 billion per year, has played an important role in highlighting the serious threats posed by excess nitrogen in the environment. Quantifying environmental and, where possible, other inputs and outputs in food production systems will continue to provide important insight into the differences between farming methods and ultimately empower us to choose a more effective one.