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Big Data Analytics Maturity Model for SMEs

Willetts, Matthew and ATKINS, Anthony (2024) Big Data Analytics Maturity Model for SMEs. International Journal of Information Technology and Computer Science, 16 (2). pp. 1-15. ISSN 2074-9007

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Official URL: https://doi.org/10.5815/ijitcs.2024.02.01

Abstract or description

Small and medium-sized enterprises (SMEs) are the backbone of the global economy, constituting 90% of all businesses. Despite being widely adopted by large businesses who have reported numerous benefits including increased profitability and increased efficiency and a survey in 2017 of 50 Fortune 1000 and leading firms’ executives indicated that 48.4% of respondents confirmed they are achieving measurable results from their Big Data investments, with 80.7% confirming that they have generated business. Big Data Analytics is adopted by only 10% of SMEs. The paper outlines a review of Big Data Maturity Models and discusses their positive features and limitations. Previous research has analysed the barriers to adoption of Big Data Analytics in SMEs and a scoring tool has been developed to help SMEs adopt Big Data Analytics. The paper demonstrates that the scoring tool could be translated and compared to a Maturity Model to provide a visual representation of Big Data Analytics maturity and help SMEs to understand where they are on the journey. The paper outlines a case study to show a comparison to provide intuitive visual model to assist top management to improve their competitive advantage.

Item Type: Article
Uncontrolled Keywords: Big Data Analytics, Maturity Model, SMEs, Scoring Tool
Faculty: School of Digital, Technologies and Arts > Computer Science, AI and Robotics
Depositing User: Anthony ATKINS
Date Deposited: 06 Dec 2024 15:50
Last Modified: 06 Dec 2024 15:50
URI: https://eprints.staffs.ac.uk/id/eprint/8568

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