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Erscheinungsjahr: 
2025
Quellenangabe: 
[Journal:] Schmalenbach Journal of Business Research (SBUR) [ISSN:] 2366-6153 [Volume:] 77 [Issue:] 2 [Year:] 2025 [Pages:] 205-227
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
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.
Schlagwörter: 
Analytics
Data
Literature review
Maturity
Maturity models
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