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On transforming into the data-driven decision-making era: current state of practice in manufacturing smes
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Informationssystem, Information Systems)ORCID iD: 0000-0001-5435-9535
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och automatiseringsteknik, Production and Automation Engineering)
2018 (English)In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, Vol. 8, p. 337-342Conference paper, Published paper (Refereed)
Abstract [en]

Current research lacks details on how SMMEs are able to capitalize on how their IT-solutions supports data-driven decision-making. Such details are important for being able to support further development of SMMEs and assuring their sustainability and competitive edge. Prosperous SMMEs are vital due to their economical and societal importance. To alleviate the lack of details, this paper presents the results of four case studies towards SMMEs partly aimed at investigating their current state of data-driven decision-making. The findings reveal that IT-solutions in some areas are either underdeveloped or unexplored. Instead, the SMMEs tend to focus on traditional manufacturing techniques, continuous improvements in the manufacturing process, and manual support routines and thereby neglects opportunities offered in relation to e.g. incident management, product quality monitoring, and the usage of KPIs not directly linked to manufacturing.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2018. Vol. 8, p. 337-342
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords [en]
Decision making, Manufacture, Metadata, Competitive edges, Continuous improvements, Data driven decision, Incident Management, Manufacturing process, Product quality monitoring, State of practice, Traditional manufacturing, Industrial research
National Category
Production Engineering, Human Work Science and Ergonomics Other Mechanical Engineering
Research subject
Information Systems; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-16494DOI: 10.3233/978-1-61499-902-7-337ISI: 000462212700054Scopus ID: 2-s2.0-85057361916ISBN: 978-1-61499-901-0 (print)ISBN: 978-1-61499-902-7 (electronic)OAI: oai:DiVA.org:his-16494DiVA, id: diva2:1270541
Conference
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden
Available from: 2018-12-13 Created: 2018-12-13 Last updated: 2019-04-04Bibliographically approved

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Gudfinnsson, KristensStrand, Mattias

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