Assessing data analytics maturity: proposing a new measurement scale

Despoina Ioakeimidou, Dimitrios Chatzoudes and Prodromos Chatzoglou

Journal of Business Analytics, 2025, vol. 8, issue 1, 55-69

Abstract: In today’s ever-evolving business landscape, as data grows exponentially and data analysis techniques become increasingly sophisticated, their effective use to achieve business goals becomes more challenging. To this end, companies must identify their capabilities and detect gaps in their Data Analytics (DA) practices using a Data Analytics Maturity Model (DAMM). This empirical paper aims to provide a new measurement scale that can be used to assess companies’ awareness of their status in using DA. Unlike existing models, those from firms that promote commercial interests and academics include characteristics that make them difficult to use. To address this gap, this research outlines the development of a valid, short, not commercial, and reliable measurement tool, the Shortened TDWI Data Analytics Maturity Model (STDAMM). Data from 285 organisations were analysed using Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to ensure its validity and reliability. The STDAMM is a valid and reliable tool for evaluating and monitoring DAM using five dimensions: Organization, Infrastructure, Data Management, Analytics, and Governance, making it a crucial tool as the fifth Industrial Revolution progresses. This study is a pioneering effort to develop and validate a DAM scale. Both theoretical and practical applications are explored.

Date: 2025
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DOI: 10.1080/2573234X.2024.2439990

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