High-risk supply chain mapping for ABB Robotics Investigating why, what, and how to map in terms of human rights and environmental issues.

Abstract

In a landscape where many speaks upon sustainability there is also an increase in regulations, ethical obligations that must be followed from the organizations due to global interconnectedness. Meanwhile, in the present landscape of global supply chains, the need for thorough understanding, visibility, and mitigation of risks has never been more critical. This places organizations in a position where they must identify and mitigate the various risks hidden in their supply networks. As a result, this thesis begins an investigation into the arena of supply chain mapping in the upstream supply chain, with an emphasis on ABB Robotics. The overall aim is to investigate why, what, and how ABB Robotics should map their high-risk supply chain in terms of human rights and environmental issues. The investigation steers through a variety of legislations and their counterparts. These regulatory frameworks, demanding transparency, and due diligence, indicates a new era of accountability and sustainability, compelling organizations to extend their scrutiny beyond Tier 1 suppliers, to the far-reaching levels of Tier n. Further, implicating the focus on high-risk categories within ABB Robotics to empathize while adhering to the compliances of regulations diligently. Drawing inspiration from the Accountability Framework Initiative (AFi), a comprehensive framework encompassing human rights and environmental considerations, this research yields a multi-dimensional mapping approach. The proposed framework rests on three pillars: Supply Network Maps, Supply Chain Maps, and the innovative Supply Chain Network Structure. These components collaboratively decode the sophisticated circle of supply chain interactions, combining macro-level insights with micro-level granularity. Furthermore, the thesis delves into the practical complexities of multi-tier mapping. It unravels the step-by-step methodology, urging ABB Robotics to embark on a journey from stakeholder identification to supplier engagement and comprehensive risk assessment. As the study delves into data sources and tools, it underscores the potential of digital technologies, such as blockchain, artificial intelligence, and big data analytics, to enhance the accuracy and agility of supply chain mapping. These transformative tools have the capacity to elevate ABB Robotics ability to trace materials, validate suppliers, and ensure compliance across the complexity of its supply chain. This thesis outlines an initiative-taking approach to supply chain mapping, enabling ABB Robotics resilient in the face of dynamic regulatory environments, ethical considerations, and sustainability obligations. Through the comprehensive adoption of multi-tier mapping, ABB Robotics can enable its commitment to identify, assess, prevent, and mitigate the human rights and environmental issues in its upstream supply chain.