Study Guide

Learning outcomes

The student is able
- to gain an in-depth understanding of financial management, budgeting and investments.
- to consider and evaluate macro economical situations and their impact.
- to apply scenario thinking / identify possibilities of alternative futures / for pre-active / proactive business development, decision making and resilience.
- to identify new possibilities for profitability and disruptive business models.

Implementation and methods of teaching

The course is delivered entirely online, consisting of scheduled online sessions complemented by on-demand content in Moodle.

Teaching methods include lectures, individual and group assignments that focus on the application of business analytics in innovative decision-making processes.

Timing and attendance

The course is segmented into main building blocks:

• Knowledge management process - 19.03.2024 (online session)
• Open Innovation - 09.04.2024 (online session)
• Business analytics - 30.04.2024 (online session)
• Scenario thinking - On-demand content (available in early May 2024)

Attendance at the live online sessions is required, while the on-demand content can be accessed by students at their convenience.

Learning material and recommended literature

Course materials will be provided through Moodle, where students can also find a list of recommended readings tailored to each section of the course content.

Alternative completion methods

There are no alternative completion methods available for this course.

Working life cooperation

Real-life case studies and analytics scenarios will be incorporated into the course, providing insights into the application of business analytics in various industries.

Learning environment

The learning environment consists of:

• Online sessions via Zoom/Teams.
• Moodle for on-demand content, assignments and online forums for group discussions.

Student time use and work load

The extent of the course is 5 ECTS, indicating a total workload of approximately 133 hours. This workload is divided across individual study, group work, and participation in online sessions.

Contents

The course content will cover:

• Principles, benefits, and practical applications of knowledge management and business intelligence
• Exploration of open innovation and its integration with business analytics
• In-depth look at business analytics, including data warehousing and analysis processes.
• Scenario thinking and its application in conjunction with knowledge management.

Additional information for students: previous knowledge etc.

A foundational knowledge of business principles is beneficial.

Assessment criteria

Individual learning assignments.
Group learning assignments.
Participation and activeness during the online lectures,

Assessment scale

1-5

Failed (0)

The student does not fulfill the basic requirements of the course. There is a clear lack of understanding of the core principles of business analytics, difficulty in applying theoretical knowledge in practical contexts, or a failure to submit essential assessments.

Assessment criteria: level 1 (assessment scale 1–5)

The student has a minimal understanding of the concepts of knowledge management and business analytics. Basic concepts are recognized, but applying these ideas and performing critical analysis proves difficult. The student's work includes notable mistakes or omits important content, showing a struggle to produce coherent outcomes.

Assessment criteria: level 3 (assessment scale 1–5)

The student shows a good understanding of the course material and can apply key principles of business analytics in common situations. Although the analysis and strategic development are structured appropriately, they may lack some complexity, creativity, or detail. The understanding of the integration of analytics with innovation processes is evident, but it might not be particularly inventive.

Assessment criteria: level 5 (assessment scale 1–5)

The student excels in understanding and applying the concepts of business analytics and knowledge management. The student can analyze complex situations in depth, create cutting-edge strategies, and formulate comprehensive plans for data-driven innovation. The student's ability to strategize and optimize data use is evident, and the student’s work represents a thoughtful, strategic approach to combining analytics with innovative decision-making for industry leadership.