Problem Conceptualization as a Foundation of Data Analytics in Local Governments: Lessons from the City of Syracuse, New York

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2020-01-07
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Cronemberger, Felippe
Gil-Garcia, J.
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The use data and data analytics (DA) has been attracting the attention of academics and practitioners in the public sector and is sometimes seen as a potential strategy for process and service innovation. While research on the many possible uses of data have clearly increased - open data, big data, data analytics- empirical research on the socio-technical process that local governments followed when using data analytics to improve services and policies is still scarce. Based on existing literature about data analytics in the public sector and the data lifecycle concept, this paper examines how data analytics is actually used in a local government and what are the main steps in this process. It analyzes the experience of a mid-size American city that had a dedicated task force to data analytics use to support decision making at the local level – Syracuse, New York. Findings suggest that data analytics as a process not only involves data analysis and representations (such as visualizations), but also data collection and cleaning. Further, it seems clear that the conceptualization of the problem is a critical step in producing meaningful data analytics, but also in thinking about innovations even when data is not readily available.
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Digital Government: Social and Service Innovation, data analytics, data lifecycle, government data, innovation, problem conceptualization
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11 pages
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Proceedings of the 53rd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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