New Social Impact Scoring Tool Puts Kolkata’s Leather Industry Under the Microscope

The leather industry of Kolkata, one of India’s oldest and most economically significant manufacturing clusters, has long been scrutinized for its environmental footprint. Tanneries and leather goods factories in and around the Calcutta Leather Complex discharge effluents, consume vast quantities of water, and generate solid waste that has drawn the attention of regulators and researchers alike. Yet the social dimension of sustainability, the question of how leather production affects the well-being of workers, communities, and society at large, has remained far harder to measure. A new study published in the Journal of Industrial Ecology tackles this gap head-on, introducing a novel assessment framework called the Descriptive Subcategory Assessment Method, or DSAM, and applying it to the Kolkata leather sector with revealing results.

Social Life Cycle Assessment, commonly abbreviated as S-LCA, has gained substantial traction over the past decade as a tool for evaluating the social sustainability of products and organizations. Modeled on environmental life cycle assessment, S-LCA seeks to trace social impacts across the entire value chain of a product, from raw material extraction to disposal. International guidelines issued by the United Nations Environment Programme and the Society of Environmental Toxicology and Chemistry in 2009, and updated in 2020, have provided a common skeleton for practitioners. However, researchers have repeatedly noted that the methodology remains comparatively young and still developing, and its practical applicability, especially in developing countries where background data are scarce, has been the subject of ongoing debate. The new study, led by Soumen Ghosh of RV University in Bengaluru together with Unmesh Patnaik and Bino Paul of the Tata Institute of Social Sciences in Mumbai, argues that existing impact assessment approaches often stumble precisely where they are needed most: in data-poor, informal, and socially complex industrial settings.

The core innovation of the study is the Descriptive Subcategory Assessment Method, a hybrid impact assessment approach designed to be more practical and context-sensitive than conventional techniques. DSAM integrates quantitative scoring with qualitative field narratives, pairing numerical performance ratings for each social impact subcategory with rich descriptive accounts gathered directly from affected stakeholders. This dual structure allows the method to capture not only how a subcategory scores but also why it scores that way, preserving the texture of lived experience that purely numerical methods tend to flatten. The approach builds on earlier subcategory assessment methods developed for S-LCA, which organized social impacts into stakeholder categories and subcategories, but adapts them for regions where reliable background databases simply do not exist. In doing so, the authors offer a template that other researchers working in developing economies could replicate across industries far beyond leather.

The empirical focus of the study is the leather industry in Kolkata, a cluster that processes hides and skins into finished leather and leather products and supports thousands of livelihoods across tanning, footwear manufacture, and allied trades. Rather than concentrating solely on factory workers, the research deliberately examines four stakeholder groups that are indirectly affected by the sector: the local community living around production sites, broader society, value chain actors such as suppliers and traders, and customers. This indirect-stakeholder lens is a distinctive feature of the work. Much of the existing S-LCA literature privileges direct workers, whose conditions are comparatively easier to observe and quantify. By widening the aperture, the Kolkata study illuminates social impacts that ripple outward from the factory gate into neighborhoods, markets, and households that never set foot inside a tannery.

The findings paint a nuanced and, in places, uncomfortable picture. The study reveals notable gaps in several subcategories under the Local Community and Society stakeholder themes, gaps that the authors describe as frequently violated, either unintentionally or deliberately. These shortfalls point to pressures that industrial activity imposes on surrounding populations, from strains on shared infrastructure and environmental amenities to broader societal obligations that the industry has not fully met. The qualitative narratives collected in the field give these quantitative gaps human texture, documenting how residents and community members experience the presence of the leather sector in their daily lives. The authors emphasize that such violations are not always the product of malice; in many cases they reflect structural constraints, weak enforcement, and the sheer difficulty of coordinating social responsibility across a fragmented value chain.

Not every result is negative, and some of the positive findings are genuinely surprising. Although customers are not directly linked to the producers in any contractual or organizational sense, the subcategories associated with this stakeholder group show relatively strong performance. This suggests that the reputational and relational dimensions of the leather value chain, the ways in which end consumers relate to the products they buy, are functioning better than might be expected in an industry often associated with informality and opacity. The outcomes for value chain actors are also largely positive, indicating that suppliers, traders, and other intermediaries who keep leather moving from rawhide to finished goods report comparatively favorable social conditions. The contrast between these bright spots and the deficits recorded for local communities and society underscores a central lesson of the study: social sustainability performance is not uniform across a value chain, and aggregate assessments can mask serious localized harms.

Methodologically, the study demonstrates how mixed methods can strengthen social impact assessment. The quantitative component assigns scores to subcategories, enabling comparison across stakeholder groups and identification of hotspots, while the qualitative component draws on field narratives to interpret, contextualize, and sometimes challenge those scores. This combination matters because social phenomena resist the kind of standardized measurement that works for carbon emissions or water use. Indicators in S-LCA have long been criticized for lacking theoretical grounding and empirical validation, and the authors position DSAM as a response to that critique, grounding each subcategory assessment in direct evidence from the people it describes. The approach also speaks to a broader methodological conversation in the field, where recent reviews of S-LCA methods since the 2020 UNEP guidelines have highlighted lingering challenges in the search for standardization.

The practical implications extend well beyond academia. The authors underscore the need for targeted and effective interventions to promote a more socially sustainable value chain in the leather industry. Because the deficits are concentrated in the Local Community and Society themes, policy responses should focus on the interfaces between industry and its surroundings, rather than exclusively on factory-floor labor conditions. The study arrives at a moment when Indian leather policy is actively evolving, with state-level initiatives such as the Tamil Nadu Footwear and Leather Products Policy of 2022 signaling growing governmental ambition for the sector, and environmental impact assessment processes for complexes like the Calcutta Leather Complex drawing public scrutiny. Embedding social criteria alongside environmental ones in such policy frameworks, the research suggests, would give regulators and industry leaders a more complete picture of sustainability performance.

For the global S-LCA community, the Kolkata case offers something arguably more valuable than a set of findings: a demonstration that rigorous social assessment is feasible even where background data are limited. The Descriptive Subcategory Assessment Method shows that careful fieldwork, transparent scoring, and honest narrative reporting can substitute, at least in part, for the comprehensive databases that practitioners in wealthy countries take for granted. As demand grows for social sustainability metrics in global trade, from footwear brands to automotive suppliers, tools like DSAM could help ensure that the social costs of production in developing economies are measured, disclosed, and ultimately addressed. The leather workers, residents, and communities of Kolkata provided the evidence; the method they helped validate may soon travel far beyond the tanneries of Bengal.

Subject of Research: A novel Descriptive Subcategory Assessment Method for social life cycle assessment applied to the leather industry in Kolkata, India

Article Title: Descriptive subcategory assessment method (DSAM) for social life cycle assessment: a case study of leather industry in Kolkata, India

Article References: Ghosh, S., Patnaik, U., & Paul, B. (2026). Descriptive subcategory assessment method (DSAM) for social life cycle assessment: a case study of leather industry in Kolkata, India. Journal of Industrial Ecology. https://doi.org/10.1007/s44498-026-00173-2

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00173-2

Keywords: social life cycle assessment, S-LCA, DSAM, leather industry, Kolkata, India, social sustainability, local community, value chain actors, stakeholder assessment, sustainability metrics, industrial ecology