Project Management and Innovation*
A.Y. 2023/2024
Learning objectives
The course proposes a critical reflection on how the strategic use of Big Data shapes and informs the practice of management, managerial expertise, and the way of managing businesses. The course aims to provide students with conceptual grounds and frameworks for thinking analytically about how innovation and data-driven insights can shape organizations and impact sectors and institutions.
Course learning objectives are the following:
· Explain the challenges of using Big Data for businesses decision-making.
· Identify types and forms of innovation and understand how innovation, fueled by Big Data, shape businesses' practices and work organization.
· Discuss how companies advance innovation by using project-based structure and identify different forms of project organizing (such as single-project organizations, project networks, and project ecologies).
· Discuss how projects, such as R&D projects or new product development projects, are used to accomplish innovation, solve complex problems, and explore entrepreneurial opportunities.
· Assess the opportunities and challenges afforded by Big Data and data-driven culture within business and across sectors and society.
Course learning objectives are the following:
· Explain the challenges of using Big Data for businesses decision-making.
· Identify types and forms of innovation and understand how innovation, fueled by Big Data, shape businesses' practices and work organization.
· Discuss how companies advance innovation by using project-based structure and identify different forms of project organizing (such as single-project organizations, project networks, and project ecologies).
· Discuss how projects, such as R&D projects or new product development projects, are used to accomplish innovation, solve complex problems, and explore entrepreneurial opportunities.
· Assess the opportunities and challenges afforded by Big Data and data-driven culture within business and across sectors and society.
Expected learning outcomes
Having successfully completed this course, students will be able to:
· Explain the key challenges of relying on Big Data for businesses decision-making
· Discuss the effects of technological change and digital technologies to businesses
· Discuss the different views and forms of innovation
· Assess the relevance of user-based, collaborative and platform innovation
· Explain the ways in which companies use projects to achieve innovation
· Discuss the different types of project organization and how each affords opportunities for creating systematic and formal approaches to harness innovation
· Evaluate prospects and challenges offered by Big Data and examine the implications for businesses, sectors and society
· Explain the key challenges of relying on Big Data for businesses decision-making
· Discuss the effects of technological change and digital technologies to businesses
· Discuss the different views and forms of innovation
· Assess the relevance of user-based, collaborative and platform innovation
· Explain the ways in which companies use projects to achieve innovation
· Discuss the different types of project organization and how each affords opportunities for creating systematic and formal approaches to harness innovation
· Evaluate prospects and challenges offered by Big Data and examine the implications for businesses, sectors and society
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
The course prepares students to be able to reflect on the role of data for business innovation. Most companies have been involved in making data a key corporate asset in order to improve marketing, sales, supply-chain management and other pivotal business functions. The course focuses on how innovations fueled by big data lead to new ways of organising and to the new business models adopted across organizations.
The course examines what are the implications of 'Big Data turn' for businesses, the practice of management and organising.
The course examines what are the implications of 'Big Data turn' for businesses, the practice of management and organising.
Prerequisites for admission
Basic knowledge of Management is recommended.
Teaching methods
The course will combine traditional class lecture, interactive case based sessions, individual and group presentations.
Teaching Resources
Attending students:
A list of readings will be assigned for pre-class preparation and in-class discussion. Reading list to be announced at the beginning of the course.
Non-attending students:
- Barley, S. R., 2020. Work and Technological Change, Clarendon Lectures in Management Studies.
- Davies. A. 2017. Projects: A Very Short Introduction. Oxford University Press.
- Core readings as detailed in the slides available on Ariel (same as attending students)
A list of readings will be assigned for pre-class preparation and in-class discussion. Reading list to be announced at the beginning of the course.
Non-attending students:
- Barley, S. R., 2020. Work and Technological Change, Clarendon Lectures in Management Studies.
- Davies. A. 2017. Projects: A Very Short Introduction. Oxford University Press.
- Core readings as detailed in the slides available on Ariel (same as attending students)
Assessment methods and Criteria
Attending students
Oral exam (40%)
Group and individual presentations (60%)
The final grade will be the weighted average between group and individual presentations (60%) and the individual final test (40%).
Non-attending students
Oral exam
Oral exam (40%)
Group and individual presentations (60%)
The final grade will be the weighted average between group and individual presentations (60%) and the individual final test (40%).
Non-attending students
Oral exam
SECS-P/10 - ORGANIZATION AND HUMAN RESOURCE MANAGEMENT - University credits: 6
Lessons: 40 hours
Professor:
Toraldo Maria Laura
Educational website(s)
Professor(s)
Reception:
Tuesday 10:30 to 13:30. Please write a meeting request email.
Department of Economics, Management and Quantitative Methods. Room 22 - second floor