Descriptif
MIE 556 - Introduction to Marketing and Strategy
Lecturer: Philippe Ginier-Gillet
Most innovative products and services do not succeed, nor do the majority of start-ups. Failures may occur for a variety of reasons, but quite often it is :
partly because entrepreneurs have misinterpreted the needs and willingness of their potential users and partners to adopt the new products
partly because they have not fully grasped the industry’s dynamics and competition.
Strategy and Marketing skills help managers to avoid these failures and deliver value at a profit.
Focus of the course:
This course aims:
To impart knowledge of strategy & marketing key tools and concepts
To think strategically in competitive and uncertain settings
To develop insights and skills around the conception, launch, and management of new products and businesses in entrepreneurial settings
Course organization
The course applies inductive teaching methods. It draws heavily on the case method of instruction.
Each class will be based primarily around a business case that requires students to study a real business situation, identify what the key issues are and how to address them and discuss their findings during the lecture.
Business cases used in this course are drawn from business case libraries of leading Business schools such as Harvard or Stanford BS.
The pedagogical objective is to give students the following opportunities:
To apply concepts and models to various industry settings - in terms of offers, maturity and competitive dynamics;
To be exposed to key issues that they may face during their careers as managers;
To develop diagnostic and decision-making skills in environments where the available information is incomplete and ambiguous and where there is no final ‘correct answer’.
Students will have to prepare one case study per week.
Background reading, role plays and simulations will complete the learning process.
Who should attend this course?
This course is a mandatory course for students whose major is Technology entrepreneurship but is also open to students who consider a career in consulting or business management or are keen to learn in English through the business case method. There is no prerequisite for attending this course.
- Langue du cours : Anglais
Credits ECTS : 4
effectifs minimal / maximal:
/45Diplôme(s) concerné(s)
- Echanges PEI
- Non Diplomant
- Economics, Data Analytics and Corporate Finance
- Economics for Smart Cities and Climate Policy
- Cybersecurity : Threats and Defenses
- Titre d’Ingénieur diplômé de l’École polytechnique
- M1 Innovation, Entreprise, et Société - Voie Innovation technologique
- Internet of Things : Innovation and Management Program (IoT)
- Artificial Intelligence and Advanced Visual Computing
- M1 Data AI - Data and Artificial Intelligence
Parcours de rattachement
Format des notes
Numérique sur 20Littérale/grade réduitPour les étudiants du diplôme Non Diplomant
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme M1 Data AI - Data and Artificial Intelligence
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS
Pour les étudiants du diplôme Cybersecurity : Threats and Defenses
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Economics for Smart Cities and Climate Policy
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Titre d’Ingénieur diplômé de l’École polytechnique
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 5 ECTS
Pour les étudiants du diplôme Echanges PEI
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
Pour les étudiants du diplôme Internet of Things : Innovation and Management Program (IoT)
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Artificial Intelligence and Advanced Visual Computing
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme Economics, Data Analytics and Corporate Finance
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Pour les étudiants du diplôme M1 Innovation, Entreprise, et Société - Voie Innovation technologique
Le rattrapage est autorisé (Note de rattrapage conservée)- Crédits ECTS acquis : 4 ECTS
La note obtenue rentre dans le calcul de votre GPA.