The course “data-driven innovation” focuses on the strong correlation that exists nowadays between data and the innovation path of organizations. The first part of the course focuses on firms’ innovative processes and on the issues arising from them. The second part of the course provides an overview on peculiarities, challenges and issues in management of digital innovation. The course analyses challenges and criticalities relevant the development and maintenance of an organizational structure that facilitate innovation and to the management of the key individuals in the firms innovative processes. The course provides students with an overview on strategic, organizational and operative dimensions of innovative processes. By providing both theoretical and practical approaches, the course focuses on innovation methods and approaches that enable organizations to create and accelerate innovation in the business world. The course demonstrates how data has become the primary driver of innovation and a key source of competitive advantage.

Knowledge & Understanding The course offers conceptual frameworks for understanding main concepts of innovation management within organizations. The course provides knowledge and analytical resources that will enable students to - describe the main models of innovation, use analytical tools to understand and interpret technological innovations; - illustrate the fundamental characteristics of the innovation processes; - understand the most diffused approach to the development and deployment of innovations -understand he main challenges and opportunities of digital innovation -use the theoretical frameworks, methods and analytical resources to understand data as an important source of innovation Applying knowledge & understanding Upon completion of this course, students should be able: to understand technological innovations and their management to assess various models of innovation with a focus on the Open Innovation paradigm to understand the role of different sources innovation to understand challenges of digital innovation management to understand business model innovation to understand and apply innovation methods and approaches to have an innovative mindset, which is necessary to tackle the new challenges to understand and use data as source of innovation Making Judgment During the course, students will be asked to analyze organizations, challenges, issues related to innovation process and provide suggestions. The course is based on inquiry-based learning where students asked to apply knowledge gained from the course and solve real problems. During the course, students will work on a project where they need to analyze real cases and at the same time made, develop and discuss solutions to problems. Communication skills The resulting multidisciplinary communication skills are the main result of teaching. The student will indeed be able to combine the technical and managerial terminology related to innovation management to contribute to the resolution of problems related to innovation management to express ideas and concepts clearly and concisely to pitch a data-driven innovation to business audiences. to give and receive feedback in a way that is supportive Learning skills The course facilitates the development of learning skills through analyzing of case study and inquiry-based learning. Various online collaborative tools will be used.

The course is organized in the following modules: Module 1: Overview of Innovation Management Strategic Management of Technological Innovation Open Innovation: characteristics, modes and challenges Innovation deployment strategies Module 2: Digital Innovation and Innovation Methods - Innovation in the digital age - Design thinking Module 3: Business models, Agility and Data ecosystems - Business models - Agility to sense and respond to business changes - Data governance

All information concerning the course, the lecture notes, the support materials and the exercises and all communications will take place through the e-learning platform. A list of the required and suggested readings is included in the detailed program.

The course mixes theory with practice, and students will be challenged to apply principles, concepts and frameworks to real world situations. Theory and practice sessions will be distributed throughout the course. In theory sessions, we will engage in traditional, yet highly interactive, lectures that provide a comprehensive overview of the topic. These sessions will be further enriched by collective discussions among students, based on the assigned readings, fostering a dynamic learning environment. In practice sessions, the class will focus on discussing relevant studies/case studies that highlight the topic, seminars/guest lectures. The discussion is going to be guided by the inputs provided by students through their active involvement, by which we mean that for each session, students are expected to: Before each session, study the material – usually one paper and / or case studies – suggested in the reading list; During the session, actively discuss other students’ presentations and papers. Students are also asked to develop a final project work, in collaboration with a company. This will reinforce the possibility of applying the theory in live business cases

Attending students: The grade is based on a Individual written exam*(30%), Group class activities** (40%) (3 activities) Group final project work** (30%). * Students can participate only to ONE examination session among the two scheduled right after the end of the semester. They can register and sit to the second examination session ONLY if they are ABSENT at the first one. **as student work in a self-managed team, there will be peer-evaluation to assess one’s role and contribution in the team context. Non-attending students: They will be assessed as follow: Written exam (100%). For non-attending students the course’s material to prepare for the exam comprises both required and optional readings

No specific criteria required.