Course 2020-2021 a.y.

20728 - DECISION ANALYSIS IN MANAGEMENT

Department of Management and Technology

Course taught in English
Go to class group/s: 31
AFC (6 credits - I sem. - OP  |  SECS-P/07)
Course Director:
ALFONSO GAMBARDELLA

Classes: 31 (I sem.)
Instructors:
Class 31: ALFONSO GAMBARDELLA


Mission & Content Summary

MISSION

Decisions are the only means you have to change your future life. We make decisions every day. Some decisions are routine, like choosing a television program to watch. Occasionally we make decisions that have profound effects on us and those around us. Gaining competence in decision making is a highly desirable attainment. Although many of the principles of good decision making have been known for centuries, there is little emphasis on this subject throughout our educational lives. The important concepts in this course could be taught in grad school and in high school. Yet when we ask graduate students about having taken previous courses in decision making, few say that they have. Students in professional courses from major companies with global interests have the same response. The purpose of this course is to provide an opportunity to gain this mastery; to be able to achieve clarity of action in making any decision on which you focus your attention. One of the biggest obstacles in gaining decision competence is that most of us think we are pretty good at making decisions. Yet it is easy to demonstrate that even in relatively simple decision situations people make decisions that they see as unwise when they carefully review them.

CONTENT SUMMARY

The course focuses on the best practices that can be adopted to deal with conditions of uncertainty, when facing decisions problems. Namely:

 

  • A structured course of actions to make more efficient decisions
  • a language to describe decisions and distinguish strategies, scenarios, and outcomes
  • experimentation as a tool to solve critical uncertainties and to get feedback on innovation
  • the adoption of optimization and simulation techniques to solve decisions problems

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • explain how to adopt a systematic approach to decision-making under uncertainty
  • identify the sources of uncertainty behind strategic decisions and address them using experimentation
  • illustrate how to integrate all steps by optimization and simulations to reduce the uncertainty

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • apply techniques to efficiently represent decisions and their elements, understand the related uncertainties, making effective use of creativity and individual insight
  • adopt a proper language to describe decisions and distinguish strategies, scenarios, and outcomes
  • Assess how decisions problems can be managed by reducing the underlying uncertainty

Teaching methods

  • Face-to-face lectures
  • Case studies /Incidents (traditional, online)
  • Individual assignments
  • Group assignments

DETAILS

The learning experience of this course includes, in addition to face-to-face lectures, case studies discussions, group assignments, concrete examples of decisions problems in companies facing uncertainty. Aside real cases, theoretical insights will be provided.

Two group works are assigned during the course: students are expected to discuss and analyse the assignment within their group and deliver a presentation about their findings.

Moreover, each student is asked to prepare a presentation about an additional individual assignment. Both the group and individual assignments deliverable are used for the student assessment (see next paragraph) and are discussed in class to encourage a vibrant learning experience.

The active participation in class is also considered for the overall student assessment.

Attendance: due to this teaching methodology, heavily based on interaction and class participation, attending is recommended.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
    x
  • Individual assignment (report, exercise, presentation, project work etc.)
x    
  • Group assignment (report, exercise, presentation, project work etc.)
x    
  • Active class participation (virtual, attendance)
x    

ATTENDING STUDENTS

With the purpose of measuring the acquisition of the above-mentioned learning outcomes the student assessment is based on three main components:

 

1. In-class participation (5% 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. Two group assignments (30% of the final grade - 15% each) and one individual assignment (10% 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
  • Apply the appropriate approach and methodologies (e.g. experimentation) learnt in class to address decisions problems
  • Work on a team and individually and deliver a clear and articulated report about the relevant outcomes

3. Final written exam (55% of the final 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.

 

The attendance are measured by the specific app available to all students. 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 discussed in class and uploaded on the e-learning platform.


NOT ATTENDING STUDENTS

Slides discussed in class and uploaded on the e-learning platform. More information will be provided at the beginning of the course.

Last change 16/07/2020 10:27