Course 2018-2019 a.y.

The course provides concepts for managing innovations and big data in the public sector, including:

Understand the landscape of innovating in public sector organizations

an analytical framework to assess needs, prioritize objectives, support decision making and set the road map for implementation, given the public agency’s context;

tools and capabilities to plan and develop an innovation processes;

·     Explore emerging issues of open government, open and big data introducing some new practices, and the questions and dilemmas they raise, for people working in public organizations.

·     Understand the way in which data can be used to support transparency and to enhance performance in public sector organizations.

·     Organizational and cultural change challenges that occur as the nature of decision making changes with advances in big data.

·     Use data for managing different sectors/area of government: city development, healthcare, International organizations

This course aims at providing students with the knowledge and skills necessary to identify and implement innovative solutions to public problems by developing and applying analytic frameworks and using big and open data, to define strategies for making government perform better and for increasing public value.

Upon completing this course students will learn how to develop and implement an innovation strategy for a public agency; how to address such critical concerns as strategic innovation management; how to assess the impacts and the performance of innovation processes in public agencies; how to analyze that data into meaningful insights for public operations; and how to interpret that data in ways that support evidence-based decision making.

• Face-to-face lectures
• Guest speaker's talks (in class or in distance)
• Company visits
• Case studies /Incidents (traditional, online)
• Individual assignments
• Group assignments
• Interactive class activities (role playing, business game, simulation, online forum, instant polls)

There will be different modes of learning in this course, each with their own dynamic and requirements. This way, we hope to create a learning environment that accommodates diversity in terms of the way students learn.

 These modes are: 2) Interactive Lectures 1) Case Discussion, 4) Team Work, 4) Guest speakers’ talks. 

1.Interactive Lectures

Lectures are meant to discuss theory and practice of all issues related to innovation and big data use in the public sector.  Students' contribution to the lecture is considered fundamental in order to enhance your understanding of the issues.

2. Case Discussion and Role Playing

The purpose of a case study is to place participants in the role of decision-makers, asking them to distinguish pertinent from peripheral facts, to identify central alternatives among several issues competing for attention, and to formulate strategies and policy recommendations.

3. Team work and students’ presentations

Students will apply the concepts introduced during the course through group works. In particular, they will manage a decision making process in the public sector as well as an innovation project using big data.

Guest speakers’ talks (in class or in distance)

We will be hosting several guest presenters on topics relevant to learning innovation and big data. 

Guest Speaker' talks and seminars provide an opportunity to the students to benefit from the experience of prominent government officials, corporate executives and technology professionals. Distinguished speakers are invited from the public sector to highlight current issues, trends and concerns related to the innovation process and the use of big data.  Students are given the opportunity to interact with these experts and gain their viewpoint on academic concepts that are actually practiced in the public sector. 

These opportunities provide an overall perspectives to the students for evaluating theoritical concepts and transforming them into realistics plans.

The final grade will be determined by weighting grades for the following components:

15% Class active participation

35% Group work, presentation and discussion

50% Final written exam

Dates and times will be posted in the University exam timetable.

Written exam.

• Readings will be available in the Library Course Reserves
• Role playing, incidents, case studies and other relevant material will be available on the Blackboard page of the course.
• Slides will be uploaded after each session and will be available on Blackboard.
• Additional resources are available upon request based on your personal interests

• Readings will be available in the Library Course Reserves
• Additional resources are available upon request based on your personal interests