A literature-based business intelligence framework proposal for Finnish SMEs : synthesis of industry best practices
Doan, Duy (2025)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025101325950
https://urn.fi/URN:NBN:fi:amk-2025101325950
Tiivistelmä
This literature-based thesis develops the SME BI Optimization Framework tailored for Finnish small and medium-sized enterprises (SMEs). The research addresses the gap between SMEs' need for data-driven decision-making and their resource constraints, including limited IT budgets and scarce technical personnel.
Through a targeted literature review of sources, the research synthesized evidence from existing literature revealing patterns of BI performance improvements, with cloud-based solutions showing superior outcomes compared to on-premises deployments in documented case studies. The study integrated insights from Resource Based View, TOE framework, IS Success Model, and Technology Acceptance Model.
The proposed four-layer SME BI Optimization Framework encompasses Context Assessment, Solution Selection, Phased Implementation, and Performance Measurement, specifically designed for SME constraints. Literature-derived findings emphasize cloud-first technology selection, incremental deployment strategies, and SME-appropriate KPIs including report latency, data-error rates, and user adoption metrics.
The framework addresses identified gaps in change management guidance and performance standardization while leveraging government digitalization programs. This research contributes the literature-synthesized BI framework for resource-constrained SMEs, offering both theoretical advancement and practical guidelines for Finnish enterprises seeking competitive advantage through optimized business intelligence. The framework requires validation through future implementation studies.
Through a targeted literature review of sources, the research synthesized evidence from existing literature revealing patterns of BI performance improvements, with cloud-based solutions showing superior outcomes compared to on-premises deployments in documented case studies. The study integrated insights from Resource Based View, TOE framework, IS Success Model, and Technology Acceptance Model.
The proposed four-layer SME BI Optimization Framework encompasses Context Assessment, Solution Selection, Phased Implementation, and Performance Measurement, specifically designed for SME constraints. Literature-derived findings emphasize cloud-first technology selection, incremental deployment strategies, and SME-appropriate KPIs including report latency, data-error rates, and user adoption metrics.
The framework addresses identified gaps in change management guidance and performance standardization while leveraging government digitalization programs. This research contributes the literature-synthesized BI framework for resource-constrained SMEs, offering both theoretical advancement and practical guidelines for Finnish enterprises seeking competitive advantage through optimized business intelligence. The framework requires validation through future implementation studies.