Market observation shows that consumers have a preference and higher willingness to pay for products that can distinguish their environmental credentials through various eco-labels such as the Rainforest Alliance, Forest Stewardship Council (FSC) or Energy Star ratings. And while eco-labels have increased the transparency of products’ environmental credentials, pause to consider how much you know about the social impacts of your consumption. Do the products you buy involve child labour? Have they been produced in unsafe working conditions? Have the workers received fair pay? Quantifying this has become the focus of the emergent process of Social Life Cycle Assessment (S-LCA).
In the mid-1990s, John Elkington pioneered the sustainability accountancy framework through the triple bottom line, which went beyond the traditional measures of profits, return on investment, and shareholder value to include environmental and social dimensions. A visual description of the linkages between Environment, Economy and Society is given below, with the Triple Bottom Line illustrated as the full accountability across all three areas of economy, society and environment.
Since the development of the sustainability accountancy framework, social and environmental responsibility in investment and operation have become increasingly important, being driven in concert by internal company motivations and regulatory requirements. Consequently, the accurate recognition and quantification of social and environmental achievements has emerged as a critical means of both meeting regulatory requirements and branding products.
Social Life Cycle Assessment is the method emerging to explore and account for the social impacts of a products production, consumption and disposal. With availability of modelling software and online information databases, the technique is reaching market readiness but concerns remain over data representativeness, granularity and accuracy, as well as agreement over methodology.
S-LCA methodology is developed from the existing Environmental Life Cycle Assessment (E-LCA) methodology, which often utilises a range of generalised data for production systems based on geographic area or production technology. For example, decades of data collection and research has provided practitioners with detailed emissions profiling for each kWh of electricity consumed in any given location across the world. Such generalized data reduces costs of undertaking an E-LCA while achieving the required representativeness and granularity, which has greatly assisted the take up of E-LCA.
Whereas environmental impacts can generally be reduced to a functional impact measure such as kgCO2 equivalents, the variety of impact measures required by S-LCA is far less developed. The measures are also often binary in nature. For the purpose of demonstration, consider child labour exploitation. While a risk profile (being the likelihood of child labour occurring) for a geographic area can be developed, the actual answer is likely to be firstly binary (i.e. Yes/No), often making geographically stratified risk estimates largely redundant in product specific analyses. Acknowledging this, perhaps it needs to be noted that S-LCA studies using currently available market data sets may only be useful for scoping level assessments.
The implications of this simple thought experiment hint on the challenges that S-LCA methodology needs to address before it can be used to underpin consumer decisions. My research will explore the accuracy with which aggregated database information are able to replace real information through a comparative analysis of a single product, firstly using actual observed inputs, and secondly using generalised database metrics based on geographic area or other criteria. This will provide a basis for comparison of the accuracy of these database tools and also a practical example with which to discuss their strengths, shortcomings or required improvements.
A further difficulty facing the emergent S-LCA is its United Nations Environment Programme mandate to explore the ‘actual and potential positive as well as negative impacts along the life cycle’. While attributional E-LCA picks up on this, accounting for reductions to carbon footprint during production (e.g. growing trees), the treatment of positive social impacts are less easily quantified and their potential to offset different negative impacts implies implicit value judgments – variations to which, one would expect to significantly effect the outcome of a study.
The realisation of the ‘triple bottom line’ in production systems lies tantalisingly close, but is dependent on the success of the S-LCA methodology, the data it requires, as well as an effective connection to market. S-LCA has the potential to be a scientific, rigorous and thorough means of identifying and conveying the social impacts of a product’s life cycle, but the question is, just how close S-LCA is to achieving this?
Stay tuned for updates over the course of the project!