GRA 6843 Doing Digital Business

GRA 6843 Doing Digital Business

Course code: 
GRA 6843
Department: 
Communication and Culture
Credits: 
6
Course coordinator: 
Christoph Lutz
Christian Fieseler
Course name in Norwegian: 
Doing Digital Business
Product category: 
Master
Portfolio: 
MSc in Business - Elective course
Semester: 
2020 Autumn
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

(Max 30 students each semester)

In a changing business environment, it becomes increasingly important to innovate business and service models. New technologies and social movements, such as the sharing economy, require businesses to constantly reinvent themselves, and future leaders need to be equipped with skills to guide their organizations through this change. In particular, the course will cover aspects of changing media and forms of engagement on the one hand, as well as innovation models on the other hand to help students design future digital organizations and business models. As part of this course, we also intend to visit and work with digital innovators and develop business model reinvention in practice. We will impart concepts or value proposition and business model design, as well as tools to assess the potential impact of digital market offerings. Furthermore, the course will look at both matters of interaction design, as well as alignment of digital initiatives with society and external stakeholders.

During the course there will be an intensive study trip to Berlin. Students must be aware that cost for and connected with the trip is not covered by BI Norwegian Business School and students are expected to cover this cost themselves.

Learning outcomes - Knowledge
  • Participants will obtain an understanding for foresight methods and digital data in today’'s world, and will get acquainted with an up-to-date methodology to plan and to frame research questions, both for practical as well as for academic endeavors.
  • Strong emphasis will be laid on methodological concerns and a fundamental understanding for the nature of data, combined with hands-on training and discussion of tools and sources for insight generation.
  • Participants will also work with business model development frameworks and get acquainted with start-ups and social ventures. They will combine the methodological knowledge acquired about analysing social media data with conceptual expertise about start-ups and business models in order to develop a social business idea.
Learning outcomes - Skills

Participants will get to know effective ways to derive and present findings from data, ranging from visualization to insights-driven argumentation.

Participants will work with innovative approaches of developing business ideas, based on the value proposition design framework and inspired by their data analysis. In particular, they will:

  • learn how to develop stakeholder personas
  • think about conrete benefits of a business idea (customer gains)
  • think about concrete disadvantages and problems of a business idea (customer pains)
  • develop strategies to enhance the benefits (customer gains) and remove the disadvantages (customer pains)
General Competence

Strong emphasis will be laid on:

  • developing a critical understanding of current trends in digital technology, development and design, especially regarding the role of machine learning, data science and algorithms
  • appreciating the role of both big and small data
  • developing expertise on social businesses, particularly in a start-up context
  • applying business model development frameworks to develop tangible ideas
Course content

Introduction: Digital Innovations
An overview of the current developments around digital innovations, and a showcase of current examples in the form of interesting research and company studies is given. Students will obtain insights into the way of thinking of foresight planning and get a first grasp of practical questions and challenges that can occur when conducting innovation research.

Digital Ventures and Value Propositions
The context of social ventures and start-ups - an important element for the course in general and the assignment in particular - is introduced. Students will familiarize themselves with examples and conceptual approaches to the topic of start-ups in general and social ventures in particular. They will apply the value proposition design method to get structured insights into the eco-system of social ventures.

Personas
In this session, students will get acquainted with the design of stakeholder personas. This qualitative approach serves to illustrate potential customers and stakeholders in a vivid and intuitive way. Students will learn about the conceptual underpinnings of personas, the application - with concrete cases and examples - and they will develop their own personas in an interactive exercise. 

Project Work and Guest Lectures
In these sessions, students will work hands-on with data to learn ways to model relevant research questions, discovering what different interest groups are taking about, and identifying potential needs. Thus, the tools and methods discussed in the previous session will be put into practice. Moreover, guest lectures will deepen the content from the previous sessions.

7) Project Presentation and Discussions 
The students will present their projects and the current status of their reports to the group. The assignments will be discussed critically with the other participants and the instructors of the course. The main findings, implications and challenges during the research project are addressed, trying to condense the key learning across the groups.

Teaching and learning activities

The course aims at combining formal lectures with a case teaching approach. The course will consist of the following elements:  

  • Formal lectures for basics of the topics and to provide a conceptual framework; 
  • Case studies for deepening knowledge of the research process, as well as for applying theoretical knowledge to real-world situations; 
  • Guest lectures by practice experts in order to gain insights in their roles/activities and experiences. 

The course includes a study tour abroad. Students must be aware that costs connected with the trip is not covered by BI and students are expected to cover this costs themselves.

Software tools
No specified computer-based tools are required.
Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Covid-19

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA68431
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
100No1 Semester(s)Group ( 2 - 3)Term paper. To gain attestation, the participants will be asked to form teams of maximum 3 students. They work on a task over the course of the semester. Students are expected to produce a report on a set methodological topic (no longer than 20 pages). To do so, students will gather primary social media data on a topic, relying on the approaches outlined in class (descriptive analysis of social media data, social network analysis, sentiment analysis).
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:No
Grouping (size):Group (2-3)
Duration:1 Semester(s)
Comment:Term paper. To gain attestation, the participants will be asked to form teams of maximum 3 students. They work on a task over the course of the semester. Students are expected to produce a report on a set methodological topic (no longer than 20 pages). To do so, students will gather primary social media data on a topic, relying on the approaches outlined in class (descriptive analysis of social media data, social network analysis, sentiment analysis).
Exam code:GRA68431
Grading scale:ECTS
Resit:Examination when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Sum workload: 
0

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.