30587 - DATA-DRIVEN ANALYSIS AND DECISION-MAKING IN BUSINESS
Department of Management and Technology
LUISA GAGLIARDI
Mission & Content Summary
MISSION
CONTENT SUMMARY
The course focuses on the best practices that a firm can adopt to make rational decisions namely:
- A structured course of actions to make more rational decisions
- A language to describe decisions and distinguish strategies, scenarios, and outcomes
- Models and statistical techniques:
- Structured descriptive statistics
- Linear regression model
- Applications and real cases using proper software (STATA)
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Identify the main sources of uncertainty and depict a well-structured approach to decision-making
- Learn how to identify future scenarios and update the beliefs attached to them
- Learn how to use and apply data in realistic business contexts
- Improve your ability to diagnose business problems, offer appropriate solutions and generate innovative opportunities.
APPLYING KNOWLEDGE AND UNDERSTANDING
- Adopt a more structured approach to identify the sources of uncertainty, imagine different actions to be implemented under possible future scenarios
- Assess what data would be useful to make a more informed decision
- Adopt a proper language to describe decisions and distinguish strategies, scenarios, and outcomes
- Analyse data in business contexts approaches for choosing appropriate metrics and analytical methods
- Derive business insights and predictions from data, elaborate and interpret data to inform quality decision making
Teaching methods
- Face-to-face lectures
- Case studies /Incidents (traditional, online)
- Group assignments
- Interactive class activities (role playing, business game, simulation, online forum, instant polls)
DETAILS
The learning experience of this course includes:
- face-to-face lectures aimed at deepening the understanding of the theoretical foundation behind rational decision making and to master basic data analysis techniques;
- case studies discussions concerning concrete examples of decisions problems in companies facing uncertainty. Interactive calss activities will be adopted to deepen the understanding of different options and foster class participation;
- group assignments allowing students to confront with real business decisions and identify the best practices to deal with them.
Assessment methods
Continuous assessment | Partial exams | General exam | |
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ATTENDING STUDENTS
Attending students’ assessment will be based on three main components:
1. In-class participation (10% of the final grade) aimed at testing the student ability to interact in a multicultural environment and to think critically through contribution given to the class discussion.
2. Group assignment (50% of the final grade) designed for the purpose of verifying the student ability to:
· Analyse decisions problems and identify the main elements, namely the possible strategies, outcomes and scenarios
· Analyse data applying the techniques learnt in class to address decisions problems
· Work on a team to deliver a clear and articulated answer to real world business decisions
3. Final written exam (40% of the final grade), based on multiple choices related to the topics covered in class, which aims to assess the student’s learning level of the methodologies and concepts discussed during the course.
Attendance will be recorded. To take the exam as an attending student, an attendance rate equal to or higher than 75% must be reported.
NOT ATTENDING STUDENTS
Written exam, (100% of the finale grade) based on a mix of multiple choice and open questions related to the topics covered in class, which aims to assess the student’s learning level of the methodologies and concepts discussed during the course.
Teaching materials
ATTENDING STUDENTS
Slides and selected papers.
NOT ATTENDING STUDENTS
Slides and selected papers.
Hill, R. C., Griffiths, W. E., & Lim, G. C. (2018). Principles of econometrics. John Wiley & Sons. Selected chapters.