Titular Professors
The course aims to achieve the following objectives:
-Foster students' proficiency in conducting data analyses across various real-world scenarios in logistics and supply chain.
-Cultivate students' capacity for strategic thinking within the world of data, specifically in the digital logistics and supply chain sector, enabling them to analyze companies and real cases, design data solutions for sustainable competitive advantage, and efficiently execute and implement those strategiesall through a data-driven approach and new technologies: blockchain and AI.
-Blend the knowledge gained from other courses, demonstrating how different elements within the logistics and supply chain framework are interconnected.
-Develop students' BI skills by creating a dynamic dashboard using Tableau.
-Emphasize the growing importance of entrepreneurial and innovative thinking, along with new technological trends (AI, blockchain
), and explain which applications they would implement to solve different cases within the digital logistics and supply chain sectors.
-Refine students' communication skills to effectively convey analysis results and offer pertinent recommendations derived from their findings.
-Explore real-world e-logistics and supply chain scenarios: Practical examples in e-logistics and supply chains.
-Compare traditional logistics with digital solutions: Differences between conventional and digital methods.
-Analyze AI and blockchain's impact on logistics: How emerging technologies affect logistics processes.
-Understand tech's role in better decision-making: Technology's contribution to improving decisions.
-Optimize supply chains using data insights: Leveraging data for efficiency in supply chains.
-Promote innovation through tech-driven problem-solving: Encouraging creativity and tech adoption for innovation.
-Build dashboards to showcase business analytics: Using dashboards to emphasize the value of analytics.
-Teach key data analysis skills: collect, clean, visualize, interpret: Key steps in effective data analysis.
-Equip students to use AI and blockchain in logistics challenges: Preparing students to apply new tech in logistics.
Alongside the cases and presentation slides covered during class sessions, the instructor will intermittently provide students with additional readings. Extra readings or assignments will be distributed during class meetings, and students may also be tasked with locating specific readings in the library databases.
The course is designed to foster both individual and group learning through various methods:
1. Active Case Study Discussion in Logistics and Supply Chain:
- Participation in dynamic discussions through the use of real case studies focused on logistic problems and the application of technological solutions like AI and blockchain.
- The selected cases emphasize issues relevant to the international logistic sector.
- Students are expected not only to read and thoroughly prepare the cases but also actively engage in class discussions on applying technological solutions to logistic problems.
- Beyond preparation, students are required to contribute with interventions in group sessions to address innovative strategies in logistics.
2. Idea Exchange and Critical Thinking Development in Logistics:
- The main objective is to collectively present and discuss conceptual frameworks and fundamental tools centered around logistics and new technologies.
- Discussion process will be facilitated, highlighting key concepts and lessons related to the application of emerging technologies in logistics.
- However, each student is individually responsible for formulating their own synthesis, based on conceptual readings, class attendance, active participation, and class discussions focused on technological innovation in logistics.
- To effectively follow the course, students must read and prepare assigned readings before each class, with emphasis on understanding technological concepts applied to logistics.
- The course content is structured sequentially, with each session serving as a basis for the next. Therefore, thorough preparation and class attendance are crucial for a comprehensive understanding of the logistic challenges.
3. Tableau:
- The course incorporates a practical dimension with hands-on exercises using Tableau.
- Examples and exercises are provided to allow students to apply theoretical concepts in a real context.
- This practice aims to enhance understanding and proficiency in using Tableau for strategic analysis and decision-making.
- Students are encouraged to actively participate in these practical sessions to reinforce their learning and practical skills.
Your final grade will be determined by three components:
1. Class Participation: 10%.
2. Case Resolution: 25%.
3. Group Projects: 1) Project 1 (E-Logistics Dashboard): 40%, 2) Project 2 (Supply Chain Network Design): 25%.
The submission dates for individual and group assignments will be specified, and failure to adhere to them will result in a percentage deduction from the grade. This course requires students to submit a hard copy of their work during the indicated session. Assignments will assess course outcomes, including analytical skills, understanding of theory and management functions, as well as their application to practical cases. Proper linguistic style (academic) and format will also be considered.
Anthony M. Pagano, Matthew Liotine: Grant, Robert: Technology in Supply Chain Management and Logistics