Current
courses at LSM
Research Ethics and Open Science
In recent years, the scientific community has confronted significant challenges that threaten its credibility and its contribution to society. A substantial share of published findings cannot be reliably replicated, raising concerns about the robustness of current research practices. At the same time, growing awareness of questionable research practices has highlighted the urgent need for stronger norms of integrity, transparency and responsible conduct. This course engages with these challenges by examining the principles of research ethics and the transformative potential of open science. Students will explore how to implement responsible data management, share research outputs openly, and navigate complex ethical dilemmas, particularly in a landscape increasingly shaped by AI. By fostering integrity, accountability and critical reflection, this course prepares future researchers to work with rigor, openness, and responsibility in a rapidly evolving scientific environment.
Business Analytics
In today’s economy, organizations have access to an unprecedented amount of data, often referred to as the new “oil” of the economy. The rise of artificial intelligence (AI) is further transforming business intelligence and analytics. However, effectively leveraging data and AI to support business decisions remains a major challenge for many organizations. This course explores the increasingly important role of data and AI in business and examines how organizations can develop competitive advantages and create impact through decision-driven business analytics. This course teaches widely-used frameworks, techniques and approaches of business analytics including descriptive analytics (BI and data visualization), causal analytics (experimental design), and predictive analytics (machine learning). Students will learn and use these techniques to leverage and turn data into relevant business insights. Particular attention is paid to corporate digital responsibility, that is the legal and ethical issues behind data gathering, storage and usage.
Customer Relationship Management
Customer relationships are a critical source of competitive advantage and long-term business success. This course explores CRM as a technology-enabled strategic approach to creating and sustaining customer value. Combining strategic thinking with data-driven decision-making, the course covers the key concepts, tools, and analytical methods used to develop and manage relationships with the right customers. By the end of the course, students will be equipped to apply strategic customer management principles and foster a customer-centric mindset in which customers are at the heart of organizational decisions.
Omnichannel Retailing
Retailers play an important role in the distribution chain; they represent the final link between producers and end consumers. Retailing is therefore the point where supply literally meets demand. The objective of this course is to understand the realities of traditional retailing and its evolutions, particularly those related to omnichannel retailing. Effective omnichannel retail management is now a key source of value and can provide a significant competitive advantage in the modern market. In this context, this course focuses on the strategic and operational challenges that retailers face on a daily basis: Developing effective omnichannel distribution strategies; Implementing these strategies through a coherent retailing mix (e.g., assortment management, store location, return policy); Negotiating and building sustainable relationships with the various stakeholders in the retailer’s ecosystem; and Ensuring that the customer experience is as high-quality and seamless as possible, regardless of the distribution channels used.
Comprendre son marché
Ce cours offre une introduction complète aux études de marché, depuis la définition d’un problème d’étude jusqu’à l’analyse et l’interprétation des données. Les étudiants apprendront à formuler des objectifs de recherche pertinents, à mobiliser des cadres théoriques adaptés et à développer des hypothèses de recherche rigoureuses. Le cours aborde également les différents types de designs de recherche (exploratoires, descriptifs et causaux), les méthodes de mesure et de conception de questionnaires, ainsi que les principes de l’échantillonnage. Une attention particulière est accordée aux techniques de collecte et d’analyse de données, tant qualitatives que quantitatives, afin de permettre aux étudiants de concevoir, réaliser et évaluer des études de marché de manière rigoureuse et pertinente.
Digital Data Analysis
Le contexte digital se caractérise par une abondance de données disponibles dans les systèmes de l’entreprise, mais également à l’extérieur de celle-ci. Ces données une fois récoltées, assemblées, et analysées de manière appropriée peuvent nous renseigner sur le comportement des consommateurs, les activités des concurrents, ou la performance de l’entreprise. L’analyse de ces données issues du digital nécessite à la fois des compétences techniques et des compétences analytiques, et surtout un sens inné du marketing et du management. L’objectif premier du cours est de fournir les connaissances et les outils nécessaires afin d’identifier, recueillir, et analyser les données utiles et pertinentes, transformer les données en connaissance, et guider les décisions organisationnelles.
