This repo is used for a collaborative book-writing project as part of an Executive MPA class at Arizona State University.
The page design was adapted from the contrast theme.
Public agencies are increasingly interested in unlocking the potential of large-scale data to improve service delivery and inform policy efforts. Computational tools capable of making productive use of big data have proliferated in recent years, drastically decreasing the barriers to entry for interested parties. This course will explore the practice of using data to improve organizational performance, including techniques for data collection, analysis, and behavior change. Students will operate as their own laboratory through a data journaling exercise, and devise strategies for incorporating data into management practices of public and nonprofit organizations.
One of the key course take-aways is that data can make your organization more effective, but data itself is not sufficient without strong management frameworks. The course is built around a quantified-self experiment where you will use life-logging tools and a journaling system to learn about managing information overload and building goal-oriented, evidence-based routines.
Students will also explore the social, political, and ethical considerations associated with building and managing data analytics programs in the public sphere. Students will engage critical dilemmas of data privacy, data protection, predictive analytics, personalized service delivery and resource provision, algorithmic regulation, and large-scale data analytics for administrative efficiencies and resource management optimization, among others.
Students will read several case studies that explore the use of data in organizations, will engage in discussions about socio-economic policy considerations, and write policy guidance frameworks on best practices in evidence-based management, open data, and privacy.