Bridging the Business Intelligence Gap in Small Enterprises: A Conceptual Framework for Scalable Adoption

• Author(s): Oyinomomo-emi Emmanuel Akpe ; Azubike Collins Mgbame ; Ejielo Ogbuefi ; Abraham Ayodeji Abayomi ; Oluwatobi Opeyemi Adeyelu
• Paper ID: 1708222
• Page: 416-431
• Published Date: 30-11-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 5 November-2021

Abstract

Despite the growing relevance of data-driven decision-making in modern business environments, many small enterprises (SEs) continue to face substantial barriers in adopting business intelligence (BI) tools effectively. These barriers stem from limited financial resources, lack of technical expertise, and inadequate infrastructure. This paper presents a conceptual framework designed to bridge the business intelligence gap in small enterprises by proposing a scalable, modular, and context-aware BI adoption model. The framework integrates elements of cloud computing, low-code/no-code platforms, and tailored data literacy programs to enhance BI readiness and usability among SEs. The model is grounded in the diffusion of innovations theory and supported by empirical insights from recent SME digital transformation case studies. It comprises five key pillars: (1) Business Context Assessment, (2) Scalable Infrastructure Planning, (3) Simplified BI Tool Integration, (4) Capacity Building and Data Literacy, and (5) Iterative Feedback and Evolution. Each pillar is designed to address a specific pain point in BI adoption and provide SEs with a flexible pathway to integrate BI into their operations without significant overhead costs. By emphasizing scalability and contextual relevance, the framework allows small enterprises to start with minimal capabilities and expand their BI functions as they grow, reducing the risk of technological obsolescence and resource misallocation. The framework also promotes collaboration with external stakeholders, such as technology vendors, academic institutions, and government agencies, to facilitate knowledge transfer and capacity development. This conceptual framework contributes to the academic discourse on digital inclusion and SME competitiveness, and provides a practical guide for policymakers, technology providers, and enterprise support organizations seeking to empower small enterprises through data-driven innovation. Future research will focus on empirically validating the framework across different industry sectors and geographic contexts, as well as developing toolkits and dashboards aligned with the framework’s principles to support real-time adoption tracking and impact assessment.

Keywords

Small Enterprises, Business Intelligence, Digital Transformation, Scalable Framework, Data-Driven Decision-Making, SME Competitiveness, Cloud-Based BI, Data Literacy, Low-Code Platforms, Innovation Diffusion.

Citations

IRE Journals:
Oyinomomo-emi Emmanuel Akpe , Azubike Collins Mgbame , Ejielo Ogbuefi , Abraham Ayodeji Abayomi , Oluwatobi Opeyemi Adeyelu "Bridging the Business Intelligence Gap in Small Enterprises: A Conceptual Framework for Scalable Adoption" Iconic Research And Engineering Journals Volume 5 Issue 5 2021 Page 416-431

IEEE:
Oyinomomo-emi Emmanuel Akpe , Azubike Collins Mgbame , Ejielo Ogbuefi , Abraham Ayodeji Abayomi , Oluwatobi Opeyemi Adeyelu "Bridging the Business Intelligence Gap in Small Enterprises: A Conceptual Framework for Scalable Adoption" Iconic Research And Engineering Journals, 5(5)