A Critical Success Factors for Data-Driven Decision-Making at Local Government: The Case of Indonesia


  • Djoko Sigit Sayogo The University of Muhammadiyah Malang, Indonesia
  • Sri Budi Cantika Yuli University of Muhammadiyah at Malang https://orcid.org/0000-0003-2870-9081
  • Firda Ayu Amalia University of Muhammadiyah at Malang


data, data-driven, decision-making, data-driven decision-making, local government


A question remains regarding the effective application of data as a basis for decision-making in public sectors. In relation, the objectives of this study are twofold. First, this study identifies factors affecting the local government official's propensity to use data for decision-making. Second, this study outlines the components of the effective application of data-driven decision-making in local government. Extensive in-depth semi-structured interviews with executives at the agencies and offices of the Regency of Bojonegoro, Indonesia, were conducted to gather the data. Our findings demonstrate two predominant institutional factors instigating the officials' inclination to use data in their decision-making: a) the accountability pressures and b) the hierarchical, bureaucratic structure. Our findings further signify the existence of three interrelated building blocks necessary for the practical application of data-driven decision-making: a) transforming quality data into knowledge, b) capable and motivated people, and c) appropriate tools/apps. Furthermore, culture and norms, institutional contexts, rules, and regulations shaped the functioning of the three components mentioned above.


Download data is not yet available.


Metrics Loading ...




How to Cite

Sayogo, D. S., Yuli, S. B. C., & Amalia, F. A. (2023). A Critical Success Factors for Data-Driven Decision-Making at Local Government: The Case of Indonesia. JeDEM - EJournal of EDemocracy and Open Government, 15(2), 148–166. Retrieved from https://jedem.org/index.php/jedem/article/view/766



Research Papers

Similar Articles

You may also start an advanced similarity search for this article.