The development of data analytics maturity assessment framework: DAMAF

Date

2021-12-01

Author

Gökalp, Mert Onuralp
Gökalp, Selin
Koçyiğit, Altan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Today, data analytics plays a vital role in attaining competitive advantage, generating business value, and driving revenue streams for organizations. Thus, the organizations pay significant attention to improve their data analytics maturity. Nevertheless, the existing literature is dramatically limited in proposing a comprehensive roadmap to assist organizations for this scope. Thus, this study focuses on developing data analytics maturity assessment framework (DAMAF) that evaluates the organizational data analytics maturity in a staged manner from maturity level 0: incomplete to maturity level 5: optimizing. The DAMAF comprises the nine different data analytics attributes to address the specific needs of each data analytics maturity level. Accordingly, it aims to support organizations in assessing their current data analytics maturity, determining organizational gaps in data analytics, and preparing an extensive roadmap and suggestions for data analytics maturity improvement. In this research, we employed the DAMAF in an organization as a case study to evaluate its applicability and usefulness. The results showed that DAMAF properly reveals the data analytics gaps and provides a structured roadmap for continuously advancing the data analytics maturity of an organization.

Subject Keywords

assessment framework, business intelligence, data analytics, maturity assessment, maturity model, ASSESSMENT MODEL, GUIDANCE

URI

https://hdl.handle.net/11511/94997

Journal

JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS

DOI

https://doi.org/10.1002/smr.2415

Collections

Graduate School of Informatics, Article

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Citation Formats

M. O. Gökalp, S. Gökalp, and A. Koçyiğit, “The development of data analytics maturity assessment framework: DAMAF,” JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/94997.