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On transforming into the data-driven decision-making era: current state of practice in manufacturing smes
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Informationssystem, Information Systems)ORCID-id: 0000-0001-5435-9535
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0002-8619-3776
2018 (engelsk)Inngår i: 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, s. 337-342Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Amsterdam: IOS Press, 2018. Vol. 8, s. 337-342
Serie
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Emneord [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
HSV kategori
Forskningsprogram
Informationssystem (IS); Produktion och automatiseringsteknik
Identifikatorer
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 (tryckt)ISBN: 978-1-61499-902-7 (digital)OAI: oai:DiVA.org:his-16494DiVA, id: diva2:1270541
Konferanse
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden
Tilgjengelig fra: 2018-12-13 Laget: 2018-12-13 Sist oppdatert: 2023-06-20bibliografisk kontrollert
Inngår i avhandling
1. Towards facilitating BI adoption in small and medium sized manufacturing companies
Åpne denne publikasjonen i ny fane eller vindu >>Towards facilitating BI adoption in small and medium sized manufacturing companies
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This work concerns how to support Small and Medium sized Manufacturing Enterprises(SMMEs) with their Business Intelligence (BI) adoption, with the long term aim of supporting them in making better use of their BI investments and becoming (more)data-driven in their decision-making processes. Current BI research focuses primarily on larger enterprises, despite the fact that the majority of businesses are small or mediumsized. Therefore, this research focuses on the body of knowledge concerning how SMMEs can be more intelligent about their business, and better adopt BI to improve decision-making. Accordingly, the overall research aim is to create an artefact that can support SMMEs to facilitate BI adoption. An understanding of the current situation of BI adoption within SMMEs needs to be attained to achieve this, which is the focus for the first research question: What is the current state-of-practice in relation to BI adoption in SMMEs? The research question adds to current knowledge on how SMMEs are taking advantage of BI and highlights which functions within companies are currently supported by BI. Research question two identifies the main challenges that SMMEs are facing in this context: What are the main challenges for BI adoption in SMMEs? This question adds to knowledge regarding some of the barriers and hindrances SMMEs face in BI adoption. Finally, the third research question addresses how SMMEs can address the challenges in successfully adopting BI: How can the main challenges be addressed? The research question is answered by providing descriptions of work in four participating companies addressing different types of problems. Many of the challenges from literature (and from empirical data from the participating companies) regarding BI adoption are met. The outcome adds to the literature a hands-on approach for companies to address chosen problems in their settings, and addressing many of the factors previously found in the BI adoption literature. An action design research (ADR) method is used to fulfill the overall research aim. The ADR method is used to guide the development of a framework artefact based on previousliterature, and on empirical findings from working with participating companies. Theoretical background was obtained through a literature review of BI adoption and usage. Empirical material was gathered both through interviews and by reviewing documents from the companies. The work that was done in participating companies was supported by previous literature in several ways: through the use of an elicitation activity, through the core concepts of BI, and by focusing on categories presented in a BI maturity model. The principal contribution of the research is in the form of a framework: the Business Intelligence Facilitation Framework (BIFF), which includes four phases. All phases contain activities that support companies in addressing BI adoption challenges from the literature and empirical data, in order to achieve the overall research aim. This research contributes both to research and practice. From a research point of view, the framework provides a way to address many of the factors previously identified in literature that need to be in place to increase the likelihood of successful BI adoption. From a practice perspective, the framework supports practitioners offering guidance in how to improve their BI adoption, providing activities for them to take, and guidance in how to carry out the activities.

sted, utgiver, år, opplag, sider
Skövde: University of Skovde, 2019. s. 126
Serie
Dissertation Series ; 30 (2019)
HSV kategori
Forskningsprogram
Informationssystem (IS)
Identifikatorer
urn:nbn:se:his:diva-17819 (URN)978-91-984918-2-1 (ISBN)
Disputas
2019-11-22, G110, University of Skövde, Skövde, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2019-10-30 Laget: 2019-10-28 Sist oppdatert: 2019-11-08bibliografisk kontrollert

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