30495 - INNOVATION AND BIG DATA FOR THE PUBLIC SECTOR
Course taught in English
Go to class group/s: 31
Change and innovation processes are fundamental for the modernization of the public sector. In most cases these processes are implemented with the support of data. The public sector is becoming increasingly aware of the potential value to be gained from big data. Governments generate and collect vast quantities of data through their everyday activities, such as managing pensions and allowance payments, tax collection, national health systems, recording traffic data, and issuing official documents. These data and new technologies are immense opportunities but they also come with particular challenges. Moreover, policy and governance innovations are transforming the role of states and citizens around the world.
The course provides concepts for managing innovations and big data in the public sector. The topics include:
- Understanding the landscape of innovation in public sector organizations.
- An analytical framework to assess needs, prioritize objectives, support decision making and set the road map for implementation of innovation processes given a public agency’s context.
- Tools and capabilities to plan and develop an innovation process.
- Exploring the emerging issues of open government, open and big data, and discussing new practices, questions and dilemmas they raise for people working in public organizations.
- How to use data to support transparency and to enhance performance in public sector organizations.
- How to use data to manage different areas of government: city development, healthcare, security.
- Organizational and cultural change challenges in the public sector.
This is an Engage Course within the CIVICA Bachelor Engage Track developed within the framework of the CIVICA alliance.
This course aims at providing students with the knowledge, analytical frameworks and skills necessary to:
- Define strategies for making government perform better and for increasing public value.
- Identify and implement innovative solutions to public problems using big and open data.
- Address critical concerns in strategic innovation management in the public sector.
- Assess the impact and performance of innovation processes in public agencies.
- Extract meaningful insights for public operations from big and open data.
- Interpret data in ways that support evidence-based decision making.
- Develop and implement an innovation strategy for a public agency.
- Present a collaborative project in a professional way.
- Face-to-face lectures
- Guest speaker's talks (in class or in distance)
- Group assignments
- Interactive class activities (role playing, business game, simulation, online forum, instant polls)
This course employs different teaching and learning modes, each with their own dynamic, requirements, advantages and disadvantages. This learning environment accommodates students’ diversity and different ways of learning. These modes are: 1) Interactive lectures, 2) case discussion, 3) group work. Please find explanations below.
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. The lectures are held by three professors with different expertise to provide you with a comprehensive understanding of the topic. We have tried to arrange the professors’ thematic blocs logically but sometimes, schedules did not allow this match. As a result, some topics bleed into other weeks. We think that is a good thing, since knowledge development is not linear. Students' contribution to the lectures is considered fundamental for the success of the course and your learning success.
2. Case study and role playing
The purpose of the case study is to place students in the role of public officals and 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. Group work and student presentations
Students will apply the concepts introduced during the course through group works. In particular, they will develop an innovation project for the public sector using (big) data. Details will be discussed in class.
|Continuous assessment||Partial exams||General exam|
The final grade is determined by weighting grades for the following components:
15% Active and prepared participation in class.
35% Group work, two presentations and discussion.
50% Final written exam.
Dates and times are posted in the University exam timetable.
Prepared, complete and on-time attendance is expected. Every class builds on the previous ones, so it is desirable to attend all sessions. Students are expected to be prepared and to have read the reading materials listed in the syllabus before class (required readings). The readings in italics, marked as “additional readings” are not required but mainly intended for future reference, if you are especially interested in a specific topic. Active participation is required. What matters is less the quantity or volume of comments, but rather the quality and relevance to the discussion.
The exam for attending students is based on lecture slides and the topics discussed in class. Attending students are those who participate in a group project.
100% Final written exam.
The exam for non-attending students is based on lecture slides and the readings.
- Readings and further materials (incidents, case studies) will be available on Blackboard
- Slides will be uploaded on Blackboard after each session