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BUS 108 — Making Critical Bets: Strategies for Modeling Business and Technical Decisions

Quarter: Fall
Day(s): Thursdays
Course Format: Live Online (About Formats)
Duration: 6 weeks
Date(s): Sep 28—Nov 2
Time: 7:00—8:40 pm (PT)
Refund Deadline: Sep 30
Unit: 1
Tuition: $495
Instructor(s): Colby Hawker
Class Recording Available: Yes
Status: Open
ACCESS THE SYLLABUS » (subject to change)
Live Online(About Formats)
7:00—8:40 pm (PT)
Sep 28—Nov 2
6 weeks
Refund Date
Sep 30
1 Unit
Colby Hawker
ACCESS THE SYLLABUS » (subject to change)
​​Whether you're a product developer faced with complex design choices, a financial analyst tasked to predict market volatility, or a general manager expanding business to a new market, decisions are often made under uncertainty. This introductory course will teach students how to approach and model complex decisions. In the context of both business and engineering, students will learn innovative frameworks and applications to make better “bets.”

We will explore theoretical frameworks centered on framing decisions and making trade-offs. Students will learn the difference between decision analysis based on experience (a posteriori) and analysis independent of experience (a priori). We will look at new research on intuition in decision-making and framing ambiguous problems without clear, singular outcomes. We’ll also examine new methods inspired by animal behavior, such as swarm intelligence, which derives wisdom from crowds.

Next, we will focus on applying these frameworks using basic simulation and modeling. We’ll cover common techniques and tools that can be applied across a broad spectrum of domains (operations, finance, marketing, and product development). Assignments and case studies will include sensitivity analysis and Monte Carlo simulation, frequently used by Wall Street and business analysts to make predictions. We will also discuss forward-looking AI applications for more complex decisions. Students will come away with the ability to appropriately frame different types of complex problems and apply new decision frameworks and applications to their own domain.

Students should have a basic working knowledge of Microsoft Excel. No programming experience is necessary.

Product Manager, Google

Colby Hawker has spent the last eight years at Google in operations and product management. Over the course of his career, he has led strategic and technical initiatives with complex trade-offs and high risk. Most recently, he has worked on the development, commercialization, and safety of Generative AI products as one of the pioneering product managers. Hawker received an MEng from Cornell.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.