Technological game changers: convergence, hype, and evolving supply chain design

• Autor(a) principal: Fawcett,Stan
• Data de Publicação: 2018
• Outros Autores: Jin,Yao Henry, Fawcett,Amydee, Bernardes,Ednilson
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Production
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132018000100214
• topic: Evolution theory; Punctuated equilibrium; Technology disruptors; Purposive supply chain design

Abstract Paper aims Poor supply chain design cost Boeing, Chipotle, Lego, and Toyota billions in revenues, capitalization, and reputational value. This paper introduces a purposive, systematic supply chain design process, identifies economic disrupters, and describes how a proactive approach to supply chain design can support and propel visionary business models. Originality The paper introduces punctuated equilibrium as a critical lens to evaluate how technological disrupters will transform supply chain design and the development of Industry X.0. Converging game changers will place more companies at existential risk, making it essential to identify potential trigger events and how they might change the competitive rules. Research method Conceptual development following over 100 interviews with companies during a 10 year longitudinal study. Main findings Emerging technologies promise/threaten to transform the economy on the scale of the industrial and information revolutions. We discuss how each technology might influence supply chain design. Individually, each technology represents a game changer. Their convergence requires purposive supply chain design to shape the emergence of Industry X.0. Implications for theory and practice Managers who employ astute scanning and nuanced scenario analysis will position their companies to not only identify inflection points but also accurately assess the timing of the transformation. This skill set will be critical to designing and developing a supply chain able to support and propel visionary business models.