I developed the following cases as part BUAD 425: Data Analysis for Decision Making (below). They were designed to not only illustrate various data-analysis techniques, but also to teach students how to integrate data analysis with more qualitative judgements to guide decision making.
Please contact me directly for the associated datasets, example code, and teaching notes.
- Winning an Election (A/B Testing)
- Dashboarding at Applichem (Dashboarding and Metric Creation)
- Trojan Horse: Unexpected Style at Your Door (Binary Classification and Subscription Management)
- Chowhound: Food for Thought (Clustering and Market Segmentation)
- Targeted Promotions at ArtZee (Personalized Promotions)
If you find any of these materials useful, please do drop me a line. I enjoy learning about how others are using these cases in their own classrooms
Selected Courses Taught
- BUAD 425 Data Analysis for Decision Making, 2014-present, Undergraduate Core.
- Curriculum Development (2014), Instructor (2015, 2017)
- Awarded the 2016 Evan C. Teaching and Learning Innovation Award for the redesign of this course.
- Course Description - Every aspect of the firm – organizational structure, marketing, product design, and strategic planning – is shifting towards data-driven decision-making. The goal of this course is to help you develop your skills as a data-savvy manager. To that end, we study several basic analytics techniques, focusing on how to apply them in practice, interpret their output, build intuition, and leverage them in decision-making.
- BUAD 311 Introduction to Operations Management, Fall 2014, Undergraduate Core.
- Instructor (2014)
- Course Description - Fundamentals of operations management. Skills needed to analyze, manage, and improve business processes. Topics include: process, capacity, service, and inventory management and optimization.
MIT / MIT Sloan
- 15.S60 Software Tools for Operations Researchers, IAP 2013-2014, Ph.D. and Graduate Elective.
- Instructor (2013), Curriculum Development (2013-2014)
- This is a student-run and taught class focusing on developing hands-on skills with data-analysis and optimization software. I was involved in the original course proposal, curriculum development and have taught the course previously. In 2014, several co-instructors and I co-authored a paper documenting the course design and sharing materials. Since then, it has remained a continued part of MIT’s Operations Research Ph.D. program, and several other schools have developed similar courses using our templated materials.
- Samples of 2013 Course Materials
- 2014 Course Materials
- 15.S05 Risk Management, Spring 2012, Spring 2013
Executive MBA Elective.
- Teaching Assistant with Dimitris Bertsimas and Retsef Levi.
- Leveraging students own varied experiences in industry, this short course aims to expose students to several core analytical models and tools to identify, think about, analyze and manage risk. My role was primarily to advise small teams of students on their term projects.
- 15.060 Data, Models, and Decisions, Fall 2011, MBA Core.
- Teaching Assistant with Georgia Perakis.
- Nominated for a 2013 Excellence in Teaching Award
- This core course introduce first-year MBA students to the fundamental quantitative techniques of data-driven management. Topics include decision analysis, probability, regression, simulation, and linear and non-linear optimization. My role was was to assist in designing exams and leading weekly recitations.
- 6.251J/15.081 Introduction to Mathematical Programming, Fall 2010, Ph.D. Core.
- Teaching Assistant with Vinent Blondel.
- This course is a rigorous introduction to linear optimization covering geometry, duality theory, the simplex method, interior point methods, network flow problems and linear discrete optimization. I lectured selected topics, led weekly recitations and assisted in designing problem sets and exams.