ABSTRACT
Supply Chain Design is a complex, strategic decision-making problem relevant to multiple stakeholders within an organization. In this chapter, we explore the role of interactive visualization and human-in-the-loop optimization as a way to improve human decision making in the context of Supply Chain Design. By combining the power of data and analytical models with the tacit knowledge of expert human decision makers, innovative, visually interactive human–machine interfaces attempt to improve the quality, speed, and transparency of decision making. They further strive to enable elaborate and data-driven design solutions that are better capable of responding to the real-life supply chain challenges faced by many companies. We draw from macro-cognitive theory to investigate how these new technological approaches enable the facilitation of group decision-making processes and elaborate a framework allowing to conceptualize group decision making in such a setting. We then present two real-world case studies in which this framework was followed to create interactive visual analytics systems supporting complex Supply Chain Design decisions of major multi-national companies
