Towards facilitating BI adoption in small and medium sized manufacturing companies / Kristens Gudfinnsson.

• This work concerns how to support Small and Medium sized Manufacturing Enterprises(SMMEs) with their Business Intelligence (BI) adoption, with the long term aimof supporting them in making better use of their BI investments and becoming (more)data-driven in their decision-making processes. Current BI research focuses primarilyon larger enterprises, despite the fact that the majority of businesses are small or mediumsized. Therefore, this research focuses on the body of knowledge concerning howSMMEs can be more intelligent about their business, and better adopt BI to improvedecision-making. Accordingly, the overall research aim is to create an artefact that cansupport SMMEs to facilitate BI adoption. An understanding of the current situation ofBI adoption within SMMEs needs to be attained to achieve this, which is the focus forthe first research question: What is the current state-of-practice in relation to BIadoption in SMMEs? The research question adds to current knowledge on howSMMEs are taking advantage of BI and highlights which functions within companiesare currently supported by BI. Research question two identifies the main challengesthat SMMEs are facing in this context: What are the main challenges for BI adoptionin SMMEs? This question adds to knowledge regarding some of the barriers and hindrancesSMMEs face in BI adoption. Finally, the third research question addresseshow SMMEs can address the challenges in successfully adopting BI: How can the mainchallenges be addressed? The research question is answered by providing descriptionsof work in four participating companies addressing different types of problems. Manyof 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-onapproach for companies to address chosen problems in their settings, and addressingmany of the factors previously found in the BI adoption literature.An action design research (ADR) method is used to fulfill the overall research aim. TheADR 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 andusage. Empirical material was gathered both through interviews and by reviewing documentsfrom the companies. The work that was done in participating companies wassupported 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 BImaturity model. The principal contribution of the research is in the form of a framework:the Business Intelligence Facilitation Framework (BIFF), which includes fourphases. All phases contain activities that support companies in addressing BI adoptionVIIIchallenges from the literature and empirical data, in order to achieve the overall researchaim.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 inliterature that need to be in place to increase the likelihood of successful BI adoption.From a practice perspective, the framework supports practitioners offering guidancein how to improve their BI adoption, providing activities for them to take, and guidancein how to carry out the activities. 

Ämnesord

Omvärldsanalyser  (sao)

Natural Sciences  (hsv)

Computer and Information Sciences  (hsv)

Information Systems  (hsv)

Naturvetenskap  (hsv)

Data- och informationsvetenskap  (hsv)

Systemvetenskap, informationssystem och informatik  (hsv)

Information Systems  (his)

Informationssystem (IS)  (his)

Business intelligence  (LCSH)

Genre

government publication  (marcgt)

Klassifikation

658.472 (DDC)

Qbac (kssb/8 (machine generated))