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

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  • Benedict Langer

    (Technical University of Munich)

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.

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  • Benedict Langer, 2025. "Understanding Data & Analytics Maturity: A Systematic Review of Maturity Model Composition," Schmalenbach Journal of Business Research, Springer, vol. 77(2), pages 205-227, June.
    • Handle: RePEc:spr:sjobre:v:77:y:2025:i:2:d:10.1007_s41471-024-00205-2
    DOI: 10.1007/s41471-024-00205-2
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