Supply Chain Analytics: Conceptualizing Complexity with the DNA Metaphor

Janaina Siegler (), Mario Henrique Callefi, Elias Ribeiro da Silva (), Elaine Mosconi () and Luis Antonio Santa-Eulalia ()
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Janaina Siegler: Butler University, Lacy School of Business
Mario Henrique Callefi: Chemnitz University of Technology, Chair of Factory Planning and Intralogistics
Elias Ribeiro da Silva: University of Southern Denmark, Department of Technology and Innovation
Elaine Mosconi: Université de Sherbrooke, École de gestion
Luis Antonio Santa-Eulalia: Université de Sherbrooke, École de gestion

A chapter in Technology Management for Intelligent, Open and Responsible Organizations and Ecosystems, 2026, pp 389-396 from Springer

Abstract: Abstract Supply Chain Analytics (SCA) has become essential for managing the growing complexity of modern supply chains. This study aims to conceptualize SCA through a meta-framework using the DNA metaphor, providing a structured and comprehensive theoretical model. The research follows a three-phase methodology: an extensive literature review to identify key SCA components, expert focus group discussions to develop the DNA metaphor, and (3) the refinement and validation of the meta-framework. The proposed SCA-DNA model illustrates how data analytics, technology, governance, strategy, and buyer-supplier relationships interact dynamically, ensuring resiliency and efficiency. Theoretical implications include a novel perspective on SCA as an interconnected system, offering a structured foundation for future studies. Practically, the model is a strategic tool for managers to optimize decision-making, improve analytical capabilities, and enhance supply chain adaptability in a data-driven environment.

Keywords: Supply Chain Analytics; Meta-framework; DNA metaphor; Data-driven decision-making; Supply chain strategy (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-032-23124-6_47

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DOI: 10.1007/978-3-032-23124-6_47

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