DATA-DRIVEN INNOVATION

DATA-DRIVEN INNOVATION

Federica Ceci, Niloofar Kazemargi

Instructional goals

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 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. The second part of the course provides an overview on peculiarities, challenges and issues in management of digital innovation. 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 shows how data become the main source of innovation and thus competitive advantage.

Intended learning outcomes

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; - list the market strategies for introducing an innovation in the market. - illustrate the fundamental characteristics of the innovation processes; - understand the most diffused approach to internal development 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 assess various models of innovation, and understand technological innovations ·to understand and use market strategies for introducing an innovation in the market ·to understand challenges of digital innovation management · 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, analyze and solve real problems. During the course, students will be continuously asked to explain and 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 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.

Course Contents

The course is organized in the following modules: Module 1: Overview of Innovation Management -Management of technological innovation and Open innovation -Technological life cycles and standard design battles - Learning from the Market Module 2: Digital Innovation, Platforms and Innovation Methods - Platforms and ecosystems - 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 - Digital and Data ecosystems

Reference Books

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.

Teaching Methods

The course mixes theory with practice, and students will be challenged to apply principles, concepts and frameworks to real world situations. Each week is comprised of two classes. Usually in the first sessions of weeks, an overview of the topic is provided using traditional – though interactive – lectures. The second sessions of weeks will be focused on the discussion of relevant studies or cases that highlight the topic or on seminar and guest lecture. 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 (but the first one), 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

Assessment Method

Attending students: The grade is based on a written exam (30%), group discussion and presentation (40%) and final project work (30%). In this case, students can ONLY retake written exam. Non-attending students: They will be assessed as follow: Business case individual assessment, written exam and individual project.

Thesis assignment criteria

No specific criteria required.

Week 1 Contenuto sessioni on line e on campus

Week 1: Management of Technological innovation and Open innovation Required Readings: Chesbrough, H., (2003) The Era of Open Innovation, MIT Sloan Management Review, 44, 3, 35–41 Optional Readings: Tennenhouse D. (2004) ‘Intel's Open Collaborative Model of Industry-University Research’, Research-Technology Management, 47, 4, 19-26; Bogers, M., H. Chesbrough, and C. Moedas. "Open innovation: research, practices, and policies." California management review 60.2 (2018): 5-16. Cases for Discussion: Procter & Gamble

Week 2 Contenuto sessioni on line e on campus

Week 2- Project work introduction Introduction of project work, in collaboration with a company Guest speaker Technological life cycles and standard design battles Required Readings Chapter 3 and 4 Schilling (2017) Strategic Management of Technological Innovation, McGraw Hill Optional Readings Dosi G. 1982. Technological paradigms and technological trajectories. Research Policy, 11: 147‐162. Abernathy WJ, Utterback JM. 1978. Patterns of Industrial Innovation. Technology Review, June‐July: 40‐47. Adner, Ron, and Rahul Kapoor. "Innovation ecosystems and the pace of substitution: Re‐examining technology S‐curves." Strategic management journal 37.4 (2016): 625-648.

Week 3 Contenuto sessioni on line e on campus

Week 3- Technological life cycles and standard design battles Cases for Discussion: BlueRay vs HD-DVD Facebook vs SixDegrees Learning from the Market Required Readings: Learning from the market, ch. 7, Leonard-Burton, D. (1998), Wellsprings of Knowledge, Harvard Business School Press. Optional Readings von Hippel, E. 1976. The dominant role of users in the scientific instrument innovation process. Research Policy, 5 (3): 212‐39. Bower, J. and Christensen, C. (1995) ‘Disruptive Technology: Catching the Wave’, Harvard Business Review, 43-53

Week 4 Contenuto sessioni on line e on campus

Week 4: Learning from the Market Cases for Discussion: TataNano Platforms and Ecosystems Required Readings: Chapter 2: Tiwana A (2013) Platform Ecosystems: Aligning Architecture, Governance, and Strategy. Newnes. Optional Reading: Jacobides MG, Cennamo C and Gawer A (2018) Towards a theory of ecosystems. Strategic Management Journal 39(8). Wiley Online Library: 2255–2276; Tiwana A, Konsynski B and Bush AA (2010) Platform Evolution: Coevolution of Platform Architecture, Governance, and Environmental Dynamics. Information Systems Research 21(4): 675–687.

Week 5 Contenuto sessioni on line e on campus

Week 5: Platforms and Ecosystems Cases for Discussion: Mobile Payments Uber Innovation in the data age Required Readings: F. Pigni, G. Piccoli, and R. Watson, “Digital Data Streams: Creating value from the real-time flow of big data,” Calif. Manage. Rev., vol. 58, no. 3, pp. 5–25, 2016 Nambisan, S. (2017). Digital Entrepreneurship: Toward a Digital Technology Perspective of Entrepreneurship. Entrepreneurship: Theory and Practice, 41(6), 1029–1055. https://doi.org/10.1111/etap.12254

Week 6 Contenuto sessioni on line e on campus

1st check point- meeting with groups

Week 7 Contenuto sessioni on line e on campus

Week 7- Business models Required Readings: Redman , 2015, 4 Business Models for the Data Age, Harvard business review Wiener, M., Saunders, C., & Marabelli, M. (2020). Big-data business models: A critical literature review and multiperspective research framework. Journal of Information Technology, 35(1), 66-91. Optional reading: Mayer-Schönberger and Ramge, 2018, Are the Most Innovative Companies Just the Ones With the Most Data?, Harvard business review

Week 8 Contenuto sessioni on line e on campus

Week 8: Design thinking Required Readings: •Brown, T. (2008). Design thinking. Harvard business review, 86(6), 84. Optional readings: •Liedtka, J. (2018). Why Design Thinking Works. Harvard business review

Week 9 Contenuto sessioni on line e on campus

Week 9: Individual assessment

Week 10 Contenuto sessioni on line e on campus

Week 10: Agility to sense and respond to business changes Required Readings: Tallon, P. P., Queiroz, M., Coltman, T., & Sharma, R. (2019). Information technology and the search for organizational agility: A systematic review with future research possibilities. The Journal of Strategic Information Systems, 28(2), 218-237. Optional readings: Walter, A. T. (2021). Organizational agility: ill-defined and somewhat confusing? A systematic literature review and conceptualization. Management Review Quarterly, 71(2), 343-391. Croll, A., Yoskovitz, B., Tesler, M., Bauer, H., Monoghan, R., Ries, E. (Eds.). Lean analytics: Use data to build a better start-up faster, O'Reilly Media, 2013 Cases for Discussion will be distributed in class.

Week 11 Contenuto sessioni on line e on campus

Week 11: Data ecosystems Subramaniam, M. (2020). Digital ecosystems and their implications for competitive strategy. Journal of Organization Design, 9, 1-10. Kazemargi, N., Spagnoletti, P., Constantinides, P., & Prencipe, P. (2022). Data control coordination in cloud-based ecosystems. Cases for Discussion will be distributed in class.

Week 12 Contenuto sessioni on line e on campus

Group Presentations Wrap up session – Q&A