The Role of Predictive Analytics Technologies in Macroeconomic Policy-Making
Keywords:
Predictive analytics, macro policy-making, big data, smart governance, data-driven decision-makingAbstract
Objective: This study aims to explore the role and functions of predictive analytics technologies in improving macro-level policy-making processes and to identify the core components of this transformation within data-driven governance systems.
Methods and Materials: This qualitative review study employed a thematic analysis approach. Data were collected through a systematic review of the scientific literature published between 2018 and 2025. From the identified sources in reputable databases such as Scopus, Springer, and ScienceDirect, twelve eligible articles were selected and analyzed using NVivo 14 software. The analysis process included open, axial, and selective coding, and data collection continued until theoretical saturation was reached.
Findings: The analysis revealed three major themes: “Data-Driven Transformation in Policy-Making,” “Institutional and Managerial Capacity Building for Predictive Analytics,” and “Outcomes and Impacts of Predictive Policy-Making.” Findings indicated that predictive analytics—through big data and machine learning algorithms—enhances agility, transparency, social equity, and crisis prevention in governance systems. Moreover, institutional capacity building and analytical human capital development were identified as essential prerequisites for implementing data-driven policy-making effectively.
Conclusion: Predictive analytics technologies improve policy-making quality and governance efficiency by enabling the forecasting of trends and policy outcomes. Institutionalizing these technologies requires robust data infrastructures, organizational restructuring, data literacy enhancement among decision-makers, and the establishment of clear legal and ethical frameworks. The findings provide practical insights for policymakers to design and implement intelligent, anticipatory, and evidence-based policies.
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References
Bertot, J. C., Estevez, E., & Janowski, T. (2019). Universal and contextualized public services: Digital public service innovation framework. Government Information Quarterly, 36(1), 118–126.
Bryson, J. M., Crosby, B. C., & Bloomberg, L. (2021). Public value governance: Moving beyond traditional public administration and the new public management. Public Administration Review, 81(2), 271–284.
Clark, J., Waddell, S., & Bianchi, C. (2021). Anticipatory governance and systems thinking for complex policy problems. Futures, 133, 102836.
Desouza, K. C., & Jacob, B. (2023). Data-driven government: The role of analytics in public sector transformation. Public Management Review, 25(7), 1134–1152.
Dunleavy, P., & Carrera, L. (2023). Digital era governance: IT corporations, the state, and e-government. Oxford University Press.
Janssen, M., & van der Voort, H. (2020). Agile and adaptive governance in crisis response: Lessons from the COVID-19 pandemic. International Journal of Information Management, 55, 102180.
Janssen, M., Brous, P., Estevez, E., & Klievink, B. (2022). Data governance in the digital transformation of public administration. Government Information Quarterly, 39(3), 101713.
Kim, S., & Lee, H. (2022). Predictive analytics in policy design: Toward evidence-based decision-making. Policy Studies Journal, 50(1), 45–66.
Kitchin, R. (2021). Data lives: How data are made and shape our world. Bristol University Press.
Klievink, B., Romijn, B.-J., Cunningham, S., & de Bruijn, H. (2023). Learning from data: Institutionalizing feedback in data-driven policy processes. Policy and Internet, 15(2), 287–305.
Meijer, A., & Grimmelikhuijsen, S. (2020). Responsible data analytics for good governance. Public Administration Review, 80(6), 964–972.
Mergel, I., Edelmann, N., & Haug, N. (2022). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 39(4), 101827.
Misuraca, G., Savoldelli, A., & Van Noordt, C. (2023). Data-driven public policy: Building resilience through anticipatory analytics. Information Polity, 28(1), 39–57.
Moon, M. J. (2021). E-government and the transformation of public administration in the digital era. Public Administration Review, 81(5), 863–878.
Mora, L., & Bolivar, M. P. R. (2024). Smart governance and the future of public policy: An integrated framework. Public Policy and Administration, 39(1), 11–29.
Wirtz, B. W., & Müller, W. M. (2019). An integrated model of e-government business models. Electronic Markets, 29(4), 659–675.