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Exploring Data-Driven Decision-Making for Enhanced Sustainability
KTH, School of Industrial Engineering and Management (ITM), Sustainable production development.ORCID iD: 0000-0003-3649-4308
KTH, School of Industrial Engineering and Management (ITM), Sustainable production development.ORCID iD: 0000-0001-5102-6559
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
KTH, School of Industrial Engineering and Management (ITM), Industrial Economics and Management (Dept.).
2022 (English)In: Advances in Transdisciplinary Engineering, IOS Press , 2022, p. 392-403Conference paper, Published paper (Refereed)
Abstract [en]

The industry transition towards digital transformation opens the possibilities to utilize data for enhancing sustainability in industrial operations and build capabilities towards resilient and circular operations, i.e., shift towards industry 5.0. This paper explores how data-driven decision-making (DDDM) can enable sustainable and resilient supply chain operations within the manufacturing industry. A series of in-depth interviews were conducted with experts, researchers, and company representatives across the manufacturing industry and universities in Sweden. The findings show a consensus among companies, researchers, and literature about the potential of data utilization for sustainability purposes; however, in most cases, the complete transformation towards data-driven has not happened yet. Companies have uncertainty about what data is needed rather than its lack. Reliability & validity of data become essential to exploit the potential of the data organizations already possess. Based on the literature and interview data, a conceptual model is proposed, including three identified parameters connected to DDDM, 1) data and IT infrastructure, 2) current operations, and 3) an improved triple bottom line performance. The model captures the interconnections between such parameters, depicting the benefits and challenges of DDDM and its relation to more sustainable and resilient supply chain operations within the manufacturing industry. In a data-driven approach, real-time analysis of complex & extensive amounts of data gives unlimited possibilities to improve manufacturing operations through decision-making. 

Place, publisher, year, edition, pages
IOS Press , 2022. p. 392-403
Keywords [en]
Data-driven, decision-making, digitalization, sustainability, sustainable manufacturing, Manufacture, Metadata, Supply chains, Sustainable development, Data driven, Data driven decision, Decisions makings, Digital transformation, In-depth interviews, Industrial operations, Manufacturing industries, Supply chain operation, Decision making
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-324946DOI: 10.3233/ATDE220158Scopus ID: 2-s2.0-85132831388OAI: oai:DiVA.org:kth-324946DiVA, id: diva2:1745975
Conference
SPS2022, 10th Swedish Production Symposium, SPS 2022, 26 April 2022 through 29 April 2022
Note

QC 20230327

Available from: 2023-03-27 Created: 2023-03-27 Last updated: 2023-03-27Bibliographically approved

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Chavez, ZuharaGopalakrishnan, MaheshwaranWestbroek, Arvid

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Chavez, ZuharaGopalakrishnan, MaheshwaranNilsson, ViktorWestbroek, Arvid
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Sustainable production developmentIndustrial Economics and Management (Dept.)
Production Engineering, Human Work Science and Ergonomics

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