Resilience in Value Chain - Project Description for Turing Webpage

Resilience in Value Chain and Worker Vulnerability Reduction - Trusted digital identity and payments in supply chain

Title: Resilience in Value Chain and Worker Vulnerability Reduction - Trusted digital identity and payments in supply chain.

Team: Professor Ser-Huang Poon (PI), Martin Carpenter (PDRA), Traidcraft Exchange (Subcontractor), Incudeas (Subcontractor)

Brief description: Informal sector workers are a significant part of manufacturing supply chains yet are subject to various forms of labour exploitation. We are conducting an in-depth survey and stakeholder consultations to contextualise and explore challenges associated with assigning identities to homeworkers, who are typically women and often migrants. In this we are focused on understanding whether and if so, how digital identity systems can support these vulnerable groups and lead to improvement in supply chain transparency and resilience, and ultimately contribute to improvements in working conditions. The resulting findings will inform a high-level design for some proposed technology-assisted solutions intended to achieve these aims.

Long description (Explaining the science):
Without an identity as a worker, many workers in the informal sector are unrecognised and therefore invisible in the supply chain. They are likely to be subject to very low rates of pay, often below the minimum wage. Lacking an employment contract, they also struggle to access social security and other entitlements under ILO conventions such as freedom of association and collective bargaining. Further there are legal and regulatory risks associated with the use of centralized identity systems for formal sector supply chain actors. Our hypothesis is that these distributed and decentralized patterns of work and manufacture are better served by an identity system that is based on decentralized identifiers and is based on the principles of self-sovereign identity, which mirrors the human patterns of trusted relationships already in operation in the supply chain.

We will use as a case study of the Indian garment manufacturing sector with a particular focus on homeworkers in Kapas Hera in SW Delhi, all of whom are women and migrants. Through Traidcraft India, we will first conduct an in-depth, in-person, survey that illuminates some of the contextual challenges as well as the assignation of identities to workers and supply chain actors. We will also analyse the supply chain mapping flows of product, money and data, and review examples of other digital solutions developed for vulnerable groups subject to similar risks and vulnerabilities. We will then develop potential solutions for a further round of interviews as part of a participatory and inclusive design process. We will particularly consider the needs of users who are unable to manage their own digital identities for example due to low literacy or digital exclusion and factors of access, risk, resilience, and privacy.

The research aims to consult workers from different tiers within the supply chain and garner insights on risks and challenges they face. In doing so, we plan to arrive at feasible solutions and distil major challenges involved in designing such a system. We will also draw out and recommend relevant design principles that any proposed solution for comparable contexts should adhere to.

Real world application:
Supporting this work will be a deep focus on homeworkers in the Indian garment sector. The identities of these workers are currently only known to the middlemen who mediate between them and the factories. The precariousness of this position has been forcefully driven home by Covid-19 – their status as workers was unknown leaving industry and the Government less well-equipped to support them at a time of crisis. More generally, an identity method that supported payment would be of great benefit to the homeworkers, and suppliers and brands who are ultimately employing them. Such an ID and payment system must interoperate with existing federated or centralized identity systems.