Big data maturity models for the public sector: a review of state and organizational level models

Abstract

Purpose Despite several big data maturity models developed for businesses, assessment of big data maturity in the public sector is an under-explored yet important area. Accordingly, the purpose of this study is to identify the big data maturity models developed specifically for the public sector and evaluate two major big data maturity models in that respect: one at the state level and the other at the organizational level. Design/methodology/approach A literature search is conducted using Web of Science and Google Scholar to determine big data maturity models explicitly addressing big data adoption by governments, and then two major models are identified and compared: Klievink et al.’s Big Data maturity model and Kuraeva’s Big Data maturity model. Findings While Klievink et al.’s model is designed to evaluate Big Data maturity at the organizational level, Kuraeva’s model is appropriate for assessments at the state level. The first model sheds light on the micro-level factors considering the specific data collection routines and requirements of the public organizations, whereas the second one provides a general framework in terms of the conditions necessary for government’s big data maturity such as legislative framework and national policy dimensions (strategic plans and actions). Originality/value This study contributes to the literature by identifying and evaluating the models specifically designed to assess big data maturity in the public sector. Based on the review, it provides insights about the development of integrated models to evaluate big data maturity in the public sector.

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