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2023/2024  MA-MMBDV1055U  Data-Driven Decision Making

English Title
Data-Driven Decision Making

Course information

Language English
Course ECTS 3 ECTS
Type Elective
Level Part Time Master
Duration One Semester
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Min. participants 10
Max. participants 30
Study board
Study Board for Master i forretningsudvikling
Course coordinator
  • Arisa Shollo - Department of Digitalisation (DIGI)
  • Ioanna Constantiou - Department of Digitalisation (DIGI)
Main academic disciplines
  • Information technology
Teaching methods
  • Face-to-face teaching
Last updated on 03-07-2023

Relevant links

Learning objectives
  • Demonstrate how the course models and mechanisms for decision making can be used to analyse strategic decisions in your own organization or other chosen empirical context.
  • Have the competence to recognize unconscious biases when making decisions and solving problems and reflect on common decision making traps that lead to fallacious reasoning and unfavorable outcomes.
  • Have the ability to identify criteria for when to trust intuition and when to push for analysis and evidence-based decisions.
  • Reflect on how to make strategic decisions involving multiple (and changing) goals and stakeholders.
Course prerequisites
The course targets different levels of managers, specialists, and analysts who are involved in organizational decision making. The course is also relevant for professionals who would like to understand the challenges and opportunities of data-driven decision making in organizational settings.
Examination
Data-driven Decision Making:
Exam ECTS 3
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 5 pages
Assignment type Written assignment
Release of assignment An assigned subject is released in class
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

In the current competitive business environment, decision makers need to make decisions quickly and effectively based on abundant data. Data-driven decision making refers to organizations systematically collecting and analyzing various types of data, including input, process, outcome and satisfaction data, to guide, inform and/or automate a range of decisions from operational to strategic decisions. Typical examples are recommender systems that drive product recommendation decisions, credit scoring that drive lending decisions, employee analytics that drive hiring or promotion decisions etc. Making decisions includes many considerations such as weighing risk, understanding the specific situation encountered, identifying available options as well as considering long-range implications for the organization.
This course is about understanding and applying data-driven decision making while taking into consideration the decision maker’s experience and expertise. By knowing how data-driven decisions are actually made the students can learn how various decision techniques and strategies improve the quality of decisions. Some of these techniques and strategies are founded on mathematical models or computer software like algorithmic decision making; others build on theories about awareness and mindfulness. The course presents a wide range of such techniques covering the different theoretical approaches to decision making.

Description of the teaching methods
Case studies, lectures presenting readings, guest lecturers from industry and active student involvement in discussions and reflections. Teaching is based on that students have read teaching material prior to class
Feedback during the teaching period
Feedback will be given during lessons, excersizes and exam
Student workload
Lectures 21 hours
Preparation and Exam 54 hours
Last updated on 03-07-2023