Course 2020-2021 a.y.

20595 - BUSINESS ANALYTICS

Department of Management and Technology

Course taught in English
Go to class group/s: 23
DSBA (8 credits - I sem. - OB  |  SECS-P/08)
Course Director:
ALFONSO GAMBARDELLA

Classes: 23 (I sem.)
Instructors:
Class 23: ALFONSO GAMBARDELLA


Mission & Content Summary

MISSION

This course focuses on how to make data-driven decisions in a business context. Specifically, it is divided in two parts. The first part discusses the basics of managerial theories such that students learn how to formulate their business strategies and actions. This first theoretical block paves the way for the second part of the course in which the students learn how to apply analytical tools to make theory-based and data-driven decisions. In particular, this part of the course focuses on theoretical and practical aspects of data analysis aimed at finding causal relationships that can be useful in directing managerial action. The overarching goal is to provide the students with an analytical framework to make decisions like investment decisions, the launch of an innovation, the creation of a start-up. The approach can be employed both in smaller firms and start-ups, or larger companies. The course follows a practical flavor and involves concrete uses of data and real-world examples from leading companies. Attending students will have the chance to engage in a group project, where real managerial problems have to be tackled. The performance in the projects counts as part of the student’s evaluation for the course.

CONTENT SUMMARY

  • Theory of the firm.
  • The use of theory and data to build analytical frameworks to make managerial decisions.
  • Methods and instruments to test and predict the results of managerial actions.
  • Understanding the difference between correlation causality in making managerial decisions.
  • Application of technique to nail down causal relations to make managerial decisions.
  • Building experiments to make informed managerial decisions.
  • Use of textual and machine learning tehniques to make managerial decisions.

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Learn about the most important theories in management, and their application to practical managerial problems and contexts.
  • Learn how to use theory and data to build analytical frameworks to make practical managerial decisions.
  • Learn methods and instruments to test and predict the results of managerial actions, and make the underlying managerial decisions in more informed ways.
  • Learn to nail down causal relations to make managerial decisions, and build experiments to make such decisions.
  • Learn textual and machine learning tehniques to make managerial decisions.

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Master managerial theories to make managerial decisions.
  • Develop theories and use data to make data-driven managerial decisions.

Teaching methods

  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)
  • Group assignments
  • Interactive class activities (role playing, business game, simulation, online forum, instant polls)

DETAILS

  • Lectures.
  • Practical activities: formulation of theories about innovation decisions, and test with actua data using relevant software.
  • Class project developed by groups of students and discussed at different points in time in class with the instructor and the other students.

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

Attending students

The final grade for attending students is composed of three components.

Final Group project:                         50%
Two in-class exercises:                    10% + 10%
Final Exam:                                        30%

An attending student is a student who participated in at least 75% of the classes: class attendance is central for learning in this course, and it is strongly encouraged.

The two in-class exercises are aimed at testing the ability of students to apply analytical techniques to business decision-making problems, formulating a clear theory and using the most appropriate empirical strategies to test them. They entail the use of analytical software (such as Stata) on the lines of what has been explained and practically executed with the instructor.

The final group project is a team project (4 members per team) where students have to develop and test a business idea. The goal is to test student's ability to formulate and develop clear business ideas and theories, to collect relevant data for testing business hypotheses and design rigorous tests and empirical strategies. Particularly, the project aims at testing the knowledge of the scientific method for decision-making taught in class. All teams have to present the project in one of the final classes of the course. More details about the project will be provided in the first lectures, including opportunities to conduct the project with leading companies in the consulting and business development fields.

The final written exam consists of one open question on the course topics to be chosen among three questions. The purpose is to verify that students master the underlying theoretical concepts and methods presented in the class material.

 


NOT ATTENDING STUDENTS

Non - Attending students

Non-attending students take a written exam consisting of three open questions on the course topics that counts for 100% of the final grade.

The exam aims at testing the knowledge of students about course contents (including some relevant referenced material) and their ability of choosing the most appropriate analytical techniques for different business problems, according to the framework explained in the course.

The material for the preparation of the exam as a non-attending student is the course material listed above for attending students.


Teaching materials


ATTENDING STUDENTS

  • Lecture slides & handouts
  • Material referenced in the slides & handouts

 

 


NOT ATTENDING STUDENTS

The material for the preparation of the exam as a non-attending student is the course material listed above for attending students.

Last change 27/11/2020 10:26