Towards Facilitating BI Adoption in Small and Medium Sized Manufacturing Companies
1:00 PM -
Location: G110, G-Building, University of Skovde
Kristens Gudfinsson defends his thesis ”Towards Facilitating BI Adoption in Small and Medium Sized Manufacturing Companies”.
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 medium sized. 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 previous literature, 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.
Jeremy Rose, Professor of Information Systems, University of Skövde
Mattias Strand, Senior Lecturer in Computer Science, University of Skövde
Anne Persson, Professor of Computer Science, University of Skövde
Mikael Berndtsson, Senior Lecturer in Computer Science, University of Skövde
Dr. Robert Winter, Professor, University of St. Gallen, Switzerland
Christina Keller, Professor, Lund University
Tero Pävärinta, Professor, Luleå University of Technology
Sven Carlsson, Professor, Lund University
Add to iCal