Code
MXUE QUA 9001
Field
Techniques quantitatives
Language
Anglais/English
ECTS Credits
3
Class hours
25
Total student load
60
Program Manager(s)
Department
- Data analytics, Économie et Finances
Educational team
Introduction to the module
This class deepens students’ technical understanding of evidence-informed decision making and the evaluation of digital and AI-enabled initiatives in organizational and societal contexts. Students are introduced to practical approaches for measuring impact as well as techniques for communicating results to decision-makers. They learn how business intelligence tools and evaluation frameworks can be combined to guide strategic and operational choices. The week emphasizes translating data and evidence into actionable insights, enabling students to assess whether digital innovations deliver their intended economic, social, and environmental outcomes.
Learning objectives
- 1 - Being able to extend digital intelligence through its different dimensions
- 2 - Produce and mobilise highly specialised knowledge, derived from critical thinking, in a field of expertise
- 2.1 - Develop a critical awareness of highly specialised knowledge, some of which is at the forefront of knowledge, with a view to formulating innovative contributions to complex issues, in line with the strategic plan of organisations and with scientific
- 2.3 - Conduct a reflective and detached analysis that takes into account the challenges, issues and complexity of a request or situation in order to propose appropriate and/or innovative solutions in line with regulatory developments.
- 3 - Communicate strategically in global and multicultural environments
- 4 - Lead projects for the societal, digital, energy and/or environmental transformation of organisations
- 4.2 - Lead a complex project with responsibility, with the aim of supporting the transformation of organisations (design, management, team coordination, implementation and management, control, dissemination), by mobilising multidisciplinary skills and bri
- 5 - Develop a strategic and innovative vision, drawing on the potential of digital intelligence and on a favourable ecosystem
- 6 - Design and/or pilot innovative management solutions, ensuring sustainable value creation for all stakeholders
- 6.1 - Design, develop and implement policies and practices conducive to the dynamism of the organisation, in order to resolve identified issues, taking into account the specific characteristics of the business context.
- 6.2 - Optimise the use of tools adapted to different areas of management, and define and interpret relevant KPIs in order to measure and guarantee sustainable value creation for all stakeholders.
Content : structure and schedule
5 Days of the second week of summer school.
Day 1: Morning Lecture Intro to Evidence-Informed Decision Making. Afternoon Company Visit
Day 2: Morning Lecture Experiments & AB Testing. Afternoon Student project session Hands-on lab and Project work
Day 3: Morning Lecture Impact Measurement & Communication. Afternoon: Student project session: Presentations
Day 4 and Day 5: Entrepreneurship Challenge
Sustainable Development Goals
ODD 4 — Quality Education: The week builds rigorous analytical skills — causal inference, experimental design, impact measurement — that are directly applicable across professional contexts and sectors.
ODD 11 — Sustainable Cities and Communities: Two of the three case study examples (city energy consumption, carbon tax) directly address urban and environmental sustainability challenges.
ODD — Climate Action: Impact evaluation frameworks are applied to environmental initiatives, equipping students to assess whether sustainability policies actually work.
Number of SDG's addressed among the 17
3
Learning delivery
synchrone
Pedagogical methods
Interactive lectures with case illustrations, Hands-on lab (A/B testing in Python/Excel), Company visit, Group project (evaluation framework), Group presentations, Entrepreneurship challenge (problem framing, pitching)
Evaluation and grading system and catch up exams
Class activities (40%)
Applied exercises / short tests (20%)
Student Presentations (40%)
Catch up exam: individual written assignment +online oral evaluation
Module Policies
Professor-Student Communication
● The professor will contact the students through their school email address (IMT-BS/TSP) and the Moodle portal. No communication via personal email addresses will take place. It is the student responsibility to regularly check their IMT-BS/TSP mailbox.
● Students can communicate with the professor by emailing him/her to his institutional address. If necessary, it is possible to meet the professor in his office during office-hours or by appointment.
Students with accommodation needs
If a student has a disability that will prevent from completing the described work or require any kind of accommodation, he may inform the program director (with supporting documents) as soon as possible. Also, students are encouraged to discuss it with the professor.
Class behavior
● Out of courtesy for the professor and classmates, all mobile phones, electronic games or other devices that generate sound should be turned off during class.
● Students should avoid disruptive and disrespectful behavior such as: arriving late, leaving early, careless behavior (e.g. sleeping, reading a non-course material, using vulgar language, over-speaking, eating, drinking, etc.). A warning may be given on the first infraction of these rules. Repeated violators will be penalized and may face expulsion from the class and/or other disciplinary proceedings.
● The tolerated delay is 5 minutes. Attendance will be declared on Moodle during these 5 minutes via a QR code provided by the teacher at each course start.
● Student should arrive on time for exams and other assessments. No one will be allowed to enter the classroom once the first person has finished the exam and left the room. There is absolutely no exception to this rule. No student can continue to take an exam once the time is up. No student may leave the room during an examination unless he / she has finished and handed over all the documents.
● In the case of remote learning, the student must keep his camera on unless instructed otherwise by the professor.
Honor code
IMT-BS is committed to a policy of honesty in the academic community. Conduct that compromises this policy may result in academic and / or disciplinary sanctions. Students must refrain from cheating, lying, plagiarizing and stealing. This includes completing your own original work and giving credit to any other person whose ideas and printed materials (including those from the Internet) are paraphrased or quoted directly. Any student who violates or helps another student violate academic behavior standards will be penalized according to IMT-BS rules.
Textbook Required and Suggested Readings
Cunningham, S. (2021). Causal Inference: The Mixtape. Yale University Press. Chapters 1-2, 6, 8-9. Available online at: mixtape.scunning.com
Angrist, J., & Pischke, J.S. (2014). Mastering Metrics. Princeton University Press. Chapter 1 (overview only).
Huntington-Klein, N. (2021). The Effect: An Introduction to Research Design and Causality. Available online at: theeffectbook.net
Kohavi, R., & Thomke, S. (2017). The surprising power of online experiments. Harvard Business Review, September-October 2017.
Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments. Cambridge University Press. Chapters 1-3.
Bojinov, I., & Gupta, S. (2022). Online experimentation: Benefits, operational and methodological challenges, and scaling guide. Harvard Data Science Review. Available at: hdsr.mitpress.mit.edu
Gertler, P. et al. (2016). Impact Evaluation in Practice (2nd ed.). World Bank. Available at: worldbank.org
Keywords
Causal analysis, entrepreneurial challenge
Prerequisites
INF 9001