Business education should enable students to critically evaluate diverse professional settings and create new ideas for designing and operationalizing business models. I hope to provide students with the analytical acumen and strategic thinking necessary to achieve this aim by teaching in the fields of Operations Management and Business Analytics.

Operations Management

I am excited to share my knowledge and experience in Operations and Supply Chain Management with students at different levels.

Operations Management (core)
This course introduces the key frameworks relevant to manage an organization's value creating processes. Students apply and evaluate a range of tools in the context of process analysis, inventory management, quality management, and business model innovation.
  • Spring 2024 (MAM): Teaching evaluation 4.7/5.0
  • Spring 2025 (MAM): Teaching evaluation 4.3/5.0
  • Spring 2025 (MiM, Stream A): Teaching evaluation 4.6/5.0
  • Spring 2025 (MiM, Stream B): Teaching evaluation 4.6/5.0
Process and Operations Management (core)
This course introduces a range of foundational topics in operations management. Leading the tutorials, I provided theoretical refreshers to approximately 350 students on process analyses, queueing theory, the newsvendor model, and business model innovation, as well as examples of how the theory can be applied in practice.
  • Teaching assistant to Andre Calmon
  • Teaching evaluation 4.7/5.0, awarded "Outstanding Tutor Award"
Competitive Supply Chains (elective)
This course introduces advanced topics in supply chain management. By designing and creating video tutorials on the newsvendor model, risk pooling, and the order-up-to inventory model, I provided students across cohorts with the support to better prepare for the in-class activities.
  • Teaching assistant to Guillaume Roels

Business Analytics

Based on my experiences with analytics electives at INSEAD, I created two new core courses in the Masters in Business Analytics at Bayes, and have taught these since I started here.

Digital Technologies and Value Creation (core)
In this course, students get hands-on experience using business analytics tools in Python to support businesses' value creating processes. We start by building the tools to gather data, focusing on web scraping and social media APIs. Next, students are introduced to prototypical business functions (e.g., strategy, marketing, human resources, operations). They then have a chance to apply analytics tools taught throughout the program and supported by their data gathering activities to specific use cases within to these functions.
  • Designed new course
  • Fall 2021: Teaching evaluation 4.7/5.0
  • Fall 2022: Teaching evaluation 4.4/5.0
  • Spring 2024: Teaching evaluation 4.6/5.0
  • Spring 2025: Teaching evaluation 4.5/5.0
Applied Deep Learning (core)
Building on their experience applying business analytics to real problems, we delve deeper into the Deep Learning and Reinforcement Learning toolbox. Students get to know the background of many state-of-the-art machine learning tools and how to apply these tools in practice to generate tangible benefits. While we continue building on some of the business use cases introduced in DTVC, students also familiarize themselves with key applications in computer vision and natural language processing.
  • Designed new course
  • Spring 2022: Teaching evaluation 4.4/5.0
  • Spring 2023: Teaching evaluation 4.3/5.0
  • Spring 2024: Teaching evaluation 4.6/5.0
  • Spring 2024: Teaching evaluation 4.5/5.0
Data Science for Business (elective)
This course introduces students to the key tools in data science and how these can be applied to different business cases. Leading the tutorials, I provided students with the necessary background on programming in R and with concrete examples of the tools taught in class.
  • Teaching assistant to Anton Ovchinnikov and Spyros Zoumpoulis
  • Teaching evaluation 4.9/5.0
Org 2.0: People Analytics (elective)
This course introduces students to fundamental questions about organizational design and how analytics tools can be used to shed answers on these questions in practice. Leading the tutorials, I introduced different machine learning tools and how these can be implemented using Python.
  • Teaching assistant to Phanish Puranam

Other Teaching Expertise

While I have built a broad teaching portfolio, it is most rewarding when I can create and deliver teaching based on my research.

Tech Talk (digital@INSEAD)
I was as a panelist at a tech talk about the future role of blockchain in supply chain management, sharing my research, discussing with the wider panel, and answering questions from the audience in a Q&A session.
  • Attended by more than 300 managers and executives
Business Sustainability (INSEAD - MBA)
This elective course introduces students to business models that aim to achieve better trade-offs between economic, social, and environmental objectives. As part of the elective, I designed and co-taught a lecture on the role of blockchain technology in sustainable operations.

Final Project Supervision (INSEAD - Global Executive MBA)
Together with Andre Calmon, I mentored a group of executives working on a novel application of blockchain technology in textile supply chains. The project was part of a larger initiative that was awarded several industry prizes.

Final Project Supervision (Bayes - Undergraduate, Masters, MBA, Executive MBA)
Every year, I supervise 10-20 thesis projects across different programs at Bayes. While these projects cover a range of topics, I mentor several students evaluating and setting up new business ventures around blockchain technology.
While at Karlsruhe Institute of Technology, I led tutorials on several courses in programming and theoretical computer science for the Industrial Engineering undergraduate core program.

Programming I: Java
  • Classroom instructor for tutorials on programming, with a focus on object-oriented programming
  • Supervision and grading of programming exercises and written exams
Foundations of Informatics I
  • Classroom instructor for tutorials on object-oriented modelling, logic, algorithms, complexity theory, and dynamic data structures
  • Grading of exams
Foundations of Informatics II
  • Classroom instructor for tutorials on automata, computer architecture, formal languages, operating systems and modes, and data organization and management
  • Development of exercises for a companion book
  • Grading of exams

Contact

Email: pblaettchen α smu.edu.sg

Phone: +44 (0) 7456 512419

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