GRA 3117 Strategy and Entrepreneurship Analytics
GRA 3117 Strategy and Entrepreneurship Analytics
This course will teach the students applied and quantitative approaches to model and analyze businesses as well as typical problems of a strategic and entrepreneurial nature that they face. Students will learn how to quantify and analyze businesses, business environments, as well as different strategic and entrepreneurial initiatives. The course offers the students a set of quantitative tools, methods and skills that complement their knowledge of conceptual theories in entrepreneurship, innovation, and strategic management.
After completing this course, students will have advanced knowledge of the relevant theories, tools, and methods required to model businesses to solve strategic and entrepreneurial problems. The students will have advanced understanding of how they can implement a variety of state of the art analytic tools, e.g., decision support, system dynamics, scenario analyses, simulation, NK modeling, and inductive approaches to address such problems.
After completing this course, students will be able to carry out applied modeling of real-world business challenges in an Excel framework, such as modeling market estimates, operational cost structures, investments, conducting valuation analyses under conditions of uncertainty, and calculating the effect of different initiatives. The students will be able to collect data for such modeling, structure the data, make sound judgements in how to analyze the data and use the data to make strategic decisions. They will be able to set it up in a structured way, manipulate it, and conduct sensitivity analyses.
After completing this course, students will have the knowledge and skills to quantitatively model and analyze businesses to support their decisions. The students will be able to quantify their theoretical knowledge of strategy and entrepreneurship, and to make critical assessments for the business in question.
Being able to model and analyze strategic and entrepreneurial choices is central to the course. The course will consist of a combination of lectures and group assignments and will contain quantitative components. Students will learn about various methodologies used in practice, e.g. by management consultants, venture capitalists, experts carrying out due diligence, and others, and to apply these methodologies in a range of contexts chosen to represent real world analytic challenges facing businesses across a spectrum of activities.
The course will be a combination of lectures, action learning activities, application, reflection and class discussions. We will apply concepts and skills associated with the topics and also critically evaluate them. We will assess applications, decisions made, and question/problematize these. We will also think about other ways to apply/alternative decisions. Students will need to use Excel for excercises.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course start.
At re-sit all exam components must, as a main rule, be retaken during next scheduled course.
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 spesific 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.
Teaching
Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.
Use of Excel for modeling.
| Assessments |
|---|
Exam category: Activity Form of assessment: Class participation Weight: 30 Grouping: Individual Duration: 1 Semester(s) Comment: Participation in class and through asynchronous platforms. Exam code: GRA 31171 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Activity Form of assessment: Presentation Weight: 20 Grouping: Group (2 - 4) Duration: 20 Minute(s) Comment: Presentation of group project (same group as written submission) Exam code: GRA 31171 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 50 Grouping: Group (2 - 4) Duration: 1 Semester(s) Comment: Written group project report (same group as presentation) Exam code: GRA 31171 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 36 Hour(s) | In class or online synchronous lecture plus asynchronous activities. |
Student's own work with learning resources | 60 Hour(s) | Student readings and preparation for lectures. |
Group work / Assignments | 30 Hour(s) | Student work in groups on projects and assignments. |
Examination | 34 Hour(s) | Examination related work. |
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.