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Course module: USEMDDE
USEMDDE
Data-driven Entrepreneurship
Course infoSchedule
Course codeUSEMDDE
ECTS Credits5
Category / LevelM (M (Master))
Course typeCourse
Language of instructionEnglish
Offered byFaculty of Law, Economics and Governance; Graduateschool REBO; International Economics and Business;
Contact persondr. L.A. de Bell
E-maill.a.debell@uu.nl
Lecturers
Course contact
dr. L.A. de Bell
Other courses by this lecturer
Teaching period
2  (15/11/2021 to 06/02/2022)
Teaching period in which the course begins
2
Time slotA: A (MON-morning, TUE-afternoon, WED-morn)
Study mode
Full-time
RemarkRequired in masters International Management & Business Development and Entrepreneurship.
Enrolment periodfrom 31/05/2021 up to and including 27/06/2021
Course application processadministratie onderwijsinstituut
Additional informationYou will be enrolled for this course by administration of the programme of this course.
Enrolling through OSIRISNo
Enrolment open to students taking subsidiary coursesNo
Pre-enrolmentNo
Waiting listNo
Course goals
Learning objectives
At the end of the course the student is able to:
  • Understand the Lean Startup Methodology;
  • Analyse situations of high uncertainty to exploit entrepreneurial opportunities;
  • Apply appropriate research methods to support validated learning;
  • Design appropriate experiments to conduct hypothesis testing;
  • Analyze data and measure progress to support entrepreneurial decision making.
Content
In today’s business landscape, that is characterized by digital disruption and technological innovation, firms must make decisions about new products or business ideas under growing uncertainty. Decision making under uncertainty has discouraged firms from relying on heavy ex-ante commitments of resources and has encouraged them to adopt more flexible approaches based on market feedback about early outlines of ideas and/or prototypes.
 
When introducing new ideas/products/services to the market firms can rely on heuristics – e.g., trial-and-error approaches, effectuation, or confirmation search. An alternative, however, is to apply a more scientific approach and to test the underlying mechanisms that might affect the performance of new ideas, products, or services. The Lean Startup provides a systematic approach on how test the viability of new ideas and business models by running frequent experiments that allow entrepreneurs to test each element of their vision, and quickly learn whether to pivot or persevere. Examples of relevant questions are, e.g., who are our customers?; what should our product or service look like? However, the implementation of such a data driven decision model requires entrepreneurs to: i. formulate hypotheses; ii. design and effectively execute small scale experiments, qualitative research (e.g., interviews, observations, group discussions), or quantitative research (e.g., surveys, secondary data, simulations, big data analysis); iii. to synthesize data and to effectively use the ‘lessons learned’ to improve the business model.
 
During the Data Driven Entrepreneurship course, we combine the Lean Startup methodology with rigorous business research methods commonly applied by seasoned business developers and entrepreneurs when evaluating new business opportunities. The course will provide students with a toolbox of relevant and actionable research methods and a systematic approach to analysing data. The evaluation of business opportunities is brought to life within the course by analysing real-life entrepreneurial or intrapreneurial opportunities and developing recommendations to improve the business model (‘learning by doing’). By doing so, the course builds on the quantitative and qualitative research methods acquired during previous courses such as Empirical Economics, Intrapreneurship, as well as reporting skills acquired during the Entrepreneurial Marketing course.


Learning objectives
At the end of the course the student is able to:
  • Understand the Lean Startup Methodology;
  • Analyse situations of high uncertainty to exploit entrepreneurial opportunities;
  • Apply appropriate research methods to support validated learning;
  • Design appropriate experiments to conduct hypothesis testing;
  • Analyze data and measure progress to support entrepreneurial decision making.

Format
The research project is an interactive course that stimulates active participation and discussions during tutorials and feedback sessions: 
  • Tutorials: instructions on specific topics and methods
  • Ideation sessions and matchmaking (group formation)
  • Feedback sessions
  • Individual assignments

Assessment method
  • Team assignment (50% of the final grade)
  • Individual assignment (50% of the final grade)
Competencies
-
Entry requirements
You must meet the following requirements
  • Enrolled for a degree programme of faculty Faculty of Law, Economics and Governance
Required materials
Book
-
Title:Lean Analytics. Use Data to Build a Better Startup Faster
Author:Croll, A. & Yoskovitz, B. (2013)
Instructional formats
Assignments

Feedback sessions

Ideation sessions

Tutorial

Tests
Retake
Test weight1
Minimum grade1

Assignment(s) 1
Test weight50
Minimum grade1

Assignment(s) 2
Test weight50
Minimum grade1

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