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<p>Leveraging data is becoming increasingly important for businesses. However, this transformation can be complex, as it requires a&#xa0;vast array of social and technical capabilities. To generate consensus in this domain, this study examines data &amp; analytics maturity models by analyzing their architectures, maturity levels, and maturity domains. A&#xa0;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&#xa0;comprehensive overview of the status quo in data &amp; analytics maturity models and provide a&#xa0;foundation for further research in this field. The study thus contributes towards enabling businesses to conduct more sophisticated data &amp; analytics maturity assessments and support more effective use of data.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月29日

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  • Benedict Langer

摘要

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.