Understanding Data & Analytics Maturity: A Systematic Review of Maturity Model Composition

Benedict Langer ()
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Benedict Langer: Technical University of Munich

Schmalenbach Journal of Business Research, 2025, vol. 77, issue 2, 205-227

Abstract: Abstract Leveraging data is becoming increasingly important for businesses. However, this transformation can be complex, as it requires a vast array of social and technical capabilities. To generate consensus in this domain, this study examines data & analytics maturity models by analyzing their architectures, maturity levels, and maturity domains. A systematic review based on the PRISMA framework identifies 38 maturity models and inductively derives insights into their composition. Three different content types are differentiated, namely organization-oriented, technology-oriented and data-oriented models. The initial findings provide a comprehensive overview of the status quo in data & analytics maturity models and provide a foundation for further research in this field. The study thus contributes towards enabling businesses to conduct more sophisticated data & analytics maturity assessments and support more effective use of data.

Keywords: Data; Analytics; Maturity; Maturity models; Literature review (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s41471-024-00205-2

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