Thank you for your interest in my course. A core responsibility of business leaders is to navigate decision-making dilemmas. This course introduces you to tools and concepts to enhance decision-making when confronting high-stakes leadership challenges.
The course methodology has three pillars:
Knowledge: The core content of this course consists of analytics tools. These start with foundational decision-making concepts and culminate in data and modeling skills you can use to implement these concepts in practical situations. A typical class begins with data analysis and setting the goals you are trying to achieve. This is followed by spreadsheet modeling, simulation, and sensitivity analysis using AI tools (ChatGPT 4o or higher).
Wisdom: Tools and data are indispensable but not sufficient to make wise decisions. A wise decision-maker uses knowledge to discern what is true, right, and lasting. Wisdom builds on knowledge by combining a deep understanding of the problem with experience and ethical values.
Context: We will use business cases, landmark historical events, and current news to bring concepts and tools to life. There is a wealth of information about decision-making practices—good and bad. Effective decision-making builds on learning from past experience, emulating good practices, and challenging biased and unthoughtful ones.
The business world is changing before our eyes! Large Language Models (ChatGPT being the best-known example) are on the cusp of transforming social and business life. Starting last year, I began using ChatGPT in class to probe complicated decision problems. This year, ChatGPT Version 4o will be this course's primary data and model analysis tool.
AI technology is changing fast, so the list of capabilities I plan to show you in class will likely expand throughout the semester. At a minimum, we will conduct simulations, sensitivity analysis, and advanced data analysis using ChatGPT. I expect everybody to use at least Version 4o. This version is currently free but restricts the number of daily queries. You may have to purchase a monthly subscription for around $25 for all or part of the semester to complete the work for this course.
While our focus will be on economics and strategy topics (this, after all, is a MECN course!), we will take a holistic approach to decision-making dilemmas. Thus, we will examine cases with substantial marketing, finance, and operations content to highlight the common underlying principles and tools that can be used in a variety of business contexts.
Wisdom of the Crowds vs. Madness of the Crowds
Wisdom of the crowds, betting markets, and informational herding.
Cases and examples: Financial crises.
Leadership and Corporate Risk Culture
What is risk, and how much risk should we take? Incorporating risk aversion in decisions: sigma, R-value, and Value-at-Risk.
Cases and examples: Risk in the oil and gas industry, with uncertainty capacity and prices.
Judo strategies and the incumbent dilemma
Viral adoption and exponential spread of ideas, practices, and fashions.
Cases and examples: Microsoft and the People PC Program in Thailand. The long tail in marketing.
Tail Risk and Optionality
Outliers and tail events.
Cases and examples: "If you are to die, die fast:" optionality in technology and other tail risk environments.
Boeing 737 Max: Near misses and the management of rare disasters.
Tail Risk
Near misses and the management of rare disasters using distribution fitting.
Cases and examples: The Boeing 737 Max debacle.