Data-Driven Innovation Management
A.Y. 2025/2026
Learning objectives
This course has been developed to connect cutting-edge techniques for data management, analysis and protection in the field of management of innovation and organizational transformation. It aims to facilitate learning about key developments and applications in the management of innovation field. The course helps students to develop up-to-date empirical skills for the formulation of appropriate strategies in the area of innovation at the business level. It examines available data sources of intellectual property rights and equips students with up-to-date knowledge and thinking from experts in this area. This course aims to provide a dynamic platform for learning, which exploits the latest research and practice from experts (academics and practitioners) exploiting a hand-on approach.
Expected learning outcomes
Having successfully completed this module, students will be able to demonstrate knowledge and understanding of: the key and advanced dimensions of data management for intellectual property rights - Retrieval, Cleaning, Analysis, Choice and Implementation; diagnostic, practical and creative skills to analyse and evaluate a range of business solutions in relation to intellectual property rights; organisations' ability to implement chosen strategies and identify the areas requiring change. Students will develop skills in generating alternative solutions to complex issues surrounding intellectual property rights management at the business level, underpinning each with a supportive and well researched rationale in order to achieve critical success; evaluate these solutions, analysing the impact of potential outcomes on the various stakeholder groups; analyse alternative strategies for intellectual property development in differing operating contexts; assess the importance of data quality and design of indicators to effective intellectual property management. In order to acquire these skills, students will learn how to obtain, analyse and apply information from a variety of sources in the public and private domains; master new skills in relation to the retrieval and analysis of intellectual property data; work collectively as an effective and efficient group member, including, where appropriate, organising, guiding and motivating others; plan and enact the successful completion of a personal workload; communicate both orally and in written form, using and justifying arguments within reports, presentations and debates.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
1. IP Rights and Competitive Advantage
- Patents, Trademarks, Copyrights and other solutions for IP protection
- Patent analysis
- Patent quality indicators
- Patent valuation
2. Technological Innovation & Tech Mining (TM)
- How tech mining works
- finding the right sources
- TM models
6. Data retrieval, analysis and protection
- Introduction to databases, data models, and database querying
- Patents databases (e.g., Google patents, Patstat)
- Basics of sentiment analysis
- Main issues about IP and data protection
5. Introduction to blockchains and their applications
- Blockchain characteristics and cryptocurrencies
- NFTs (Non-Fungible Tokens)
- Patents, Trademarks, Copyrights and other solutions for IP protection
- Patent analysis
- Patent quality indicators
- Patent valuation
2. Technological Innovation & Tech Mining (TM)
- How tech mining works
- finding the right sources
- TM models
6. Data retrieval, analysis and protection
- Introduction to databases, data models, and database querying
- Patents databases (e.g., Google patents, Patstat)
- Basics of sentiment analysis
- Main issues about IP and data protection
5. Introduction to blockchains and their applications
- Blockchain characteristics and cryptocurrencies
- NFTs (Non-Fungible Tokens)
Prerequisites for admission
There are no specific prerequisites for following this course.
Teaching methods
Teaching methods include theoretical lesson, hands-on experience with patents data bases, teamwork (for attending students), and seminars.
Attending lessons is warmly suggested.
Attending lessons is warmly suggested.
Teaching Resources
There is no core textbook that students should read in preparation for this course. As this is an advanced course, the core of the preparation comes from a variety of material (slides, cases, academic and professional readings, exercises, hands-on tutorials etc.). Details on all the material (including slides for each class) can be found on Ariel.
Some sections (specified during lessons) of the following textbooks will be used:
M. Cantamessa, F. Montagna (2016) Management of Innovation and Product Development: Integrating Business and Technological Perspectives. Springer-Verlag London
Alan L. Porter & Scott W. Cunningham (2005) TECH MINING: exploiting new technologies for competitive advantage. John Wiley & Sons, Inc.
M. Fortnow & Q. Terry (2022) The NFT handbook: how to create, sell and buy non-fungible tokens. John Wiley & Sons
Some sections (specified during lessons) of the following textbooks will be used:
M. Cantamessa, F. Montagna (2016) Management of Innovation and Product Development: Integrating Business and Technological Perspectives. Springer-Verlag London
Alan L. Porter & Scott W. Cunningham (2005) TECH MINING: exploiting new technologies for competitive advantage. John Wiley & Sons, Inc.
M. Fortnow & Q. Terry (2022) The NFT handbook: how to create, sell and buy non-fungible tokens. John Wiley & Sons
Assessment methods and Criteria
ATTENDING STUDENTS -------------------
The exam consists of a practical project (weight: 50% of the final grade) and a written exam on the theoretical content of the course (weight: 50% of the final grade).
Students will be required to work in groups to carry out a technological sector analysis project, respecting the deadlines and design constraints set by the professors. It is necessary for each group member - individually - to have attended at least 65% of the lessons.
At the end of the course, students will then have to illustrate and discuss (orally) their work, also based on the theoretical knowledge acquired during the lessons. The presentation will be public, and the times and methods for carrying it out will be defined during the first lessons of the course.
A positive evaluation of the project is a prerequisite for accessing the written exam, which consists of some simple theoretical questions and practical exercises.
To access the questions of the written exam, it is necessary to pass a short multiple-choice test on the course topics with at least 50% + 1 correct answers.
Should the result of the written exam not be sufficient to pass the overall exam, it is possible to retake it on one of the following dates. The project is valid for 1 year from submission.
The overall evaluation will be based on: the quality and completeness of the project, the degree of knowledge of the course topics, the ability to apply acquired knowledge to solve concrete problems, and critical reasoning skills. It will also consider clarity of exposition and linguistic accuracy.
Students who achieve a score of 18 or 30 in the written exam may be called for an oral confirmation exam of the grade.
NON-ATTENDING STUDENTS -------------------
The exam is written and focuses on the theoretical content of the course. The exam is divided into two parts. The first part consists of multiple-choice questions, and passing it with at least 50% + 1 correct answers is a prerequisite for accessing the second part.
Passing the first part of the exam does not contribute to the final grade. The second part consists of open questions and simple exercises on the course syllabus and contributes 100% to the final grade.
If you do not pass the first part, you must repeat the exam in a subsequent session. Similarly, if you pass the first part but not the second, you must repeat the entire exam.
The final evaluation reflects knowledge of the topics, clarity of exposition, and linguistic accuracy.
Students who achieve a score of 18 or 30 in the written exam may be called for an oral confirmation exam of the grade.
The exam consists of a practical project (weight: 50% of the final grade) and a written exam on the theoretical content of the course (weight: 50% of the final grade).
Students will be required to work in groups to carry out a technological sector analysis project, respecting the deadlines and design constraints set by the professors. It is necessary for each group member - individually - to have attended at least 65% of the lessons.
At the end of the course, students will then have to illustrate and discuss (orally) their work, also based on the theoretical knowledge acquired during the lessons. The presentation will be public, and the times and methods for carrying it out will be defined during the first lessons of the course.
A positive evaluation of the project is a prerequisite for accessing the written exam, which consists of some simple theoretical questions and practical exercises.
To access the questions of the written exam, it is necessary to pass a short multiple-choice test on the course topics with at least 50% + 1 correct answers.
Should the result of the written exam not be sufficient to pass the overall exam, it is possible to retake it on one of the following dates. The project is valid for 1 year from submission.
The overall evaluation will be based on: the quality and completeness of the project, the degree of knowledge of the course topics, the ability to apply acquired knowledge to solve concrete problems, and critical reasoning skills. It will also consider clarity of exposition and linguistic accuracy.
Students who achieve a score of 18 or 30 in the written exam may be called for an oral confirmation exam of the grade.
NON-ATTENDING STUDENTS -------------------
The exam is written and focuses on the theoretical content of the course. The exam is divided into two parts. The first part consists of multiple-choice questions, and passing it with at least 50% + 1 correct answers is a prerequisite for accessing the second part.
Passing the first part of the exam does not contribute to the final grade. The second part consists of open questions and simple exercises on the course syllabus and contributes 100% to the final grade.
If you do not pass the first part, you must repeat the exam in a subsequent session. Similarly, if you pass the first part but not the second, you must repeat the entire exam.
The final evaluation reflects knowledge of the topics, clarity of exposition, and linguistic accuracy.
Students who achieve a score of 18 or 30 in the written exam may be called for an oral confirmation exam of the grade.
SECS-P/08 - MANAGEMENT
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT
Lessons: 60 hours
Professors:
Livraga Giovanni, Ripamonti Laura Anna
Professor(s)