The Future of Data-Driven Decision Making: Exploring the Governance Models of Data Collaboratives and Their Relative Success

Thumbnail Image



Journal Title

Journal ISSN

Volume Title


The Ohio State University

Research Projects

Organizational Units

Journal Issue


There is a growing interest in using data-driven decision making in public policy. One response to this need is data collaboratives, which seek to fill the gap between data aggregation and public utilization of said data. Data collaboratives are a platform upon which different kinds of public and private data are collected, stored, and managed among private and public stakeholders to share data and conduct analysis. Different types of emerging data collaboratives include private intermediaries for data collection and public partnerships with smart city programs. Studying these collaboratives can provide insights into the future on how the government uses data by exploring its interaction with citizens in creating and implementing policy. In this paper, we will review various data collaboratives and look at their organizational leadership, governance approaches, mission statements, and successes/shortcomings. The research team used a mixed-methods approach by first conducting interviews to develop a more robust understanding of the nature of the problems and possible solutions. These conclusions were then validated through a survey and follow-up interviews. The results of the survey showed that many data collaboratives experience similar challenges - such as bureaucratic limitations and funding shortages - as they attempt to produce deliverables. Many data collaboratives are often narrowly focused on a policy issue such as transportation, healthcare, or infrastructure; therefore, looking at other examples of collaboratives in one city could contrast with the governance approach of another. Learning more about the successes and barriers of existing data collaboratives can help interested cities and regional partners build a comparable model.