The Choice Architecture Lab

Goal: This course will empower you to apply behavioral science concepts and methods outside the classroom for real-world impact in organizations. 

Overview: It’s one thing to learn about decision heuristics and biases, choice architecture tools, and nudging in the classroom. It’s an entirely other thing to successfully apply these insights and methods to real-world problems. This semester-long lab is designed to give you that hands-on experience, pairing small teams of students with external organizations (a mix of for-profit and nonprofit, large-scale and startup companies) in mini-consulting engagements and providing coaching along the way. Whatever your post-Wharton career – brand management, product design, human capital management, policymaking, finance, consulting, etc. – if you’re interested in applying behavioral science to your professional work, this course may be a good fit for you.

Throughout the semester, you will strengthen your muscles across: 

• diagnosing a decision or choice process using psychological theories,

• designing ‘nudges’ to improve that decision or choice process,

• evaluating your diagnosis and design with a randomized controlled experiment, and

• communicating your findings to external stakeholders.

You will be researching, observing, writing, listening, debating, creating, testing, analyzing, and presenting—all to implement a real and valuable change in your organization’s world. 

Timing: Tuesdays 3:30-6:30pm

Teams: Students work in groups of ~4, based on schedule and topic interests. Each team has a designated partner organization, as well as a coach whose "day job" is in behavioral science consulting.

Teaching style: Lectures and working sessions will focus on reviewing core decision and behavioral science concepts, sharing more about their nuances and complexities, tackling common challenges in applying them in the “real world”, and strengthening skills in running experiments. Class activities will be highly hands-on, including games, debates, and mini-hackathons - with a particular focus on helping you progress on your client projects. Where applicable, practitioners and experts will visit class to share their stories and give advice on your work. 

Individual Components (55%)

Take-home assignments (30%): To give you objective feedback on your progress through the course material, we will have 3 open-book, open-notes take-home individual assignments. (10% each)

Reading quizzes (12%): As a commitment device to do the reading, we will have random in-class, very short quizzes on the readings for that day. We will use a randomizer to determine whether it happens on any given day. Each quiz will take ~5 minutes.

Participation (13%): Participation includes constructive questions, comments, and debates during class. Late arrivals or missed classes that have not been pre-approved count negatively towards participation. 

Group Components (45%)

Your capstone assignment as a group comprises six elements: (i) Diagnosis, (ii) Solution Design, (iii) Experimental Design, (iv) Data Analysis, (v) Final Presentation, and (vi) Final Report. 

I will share templates at the start of the semester, and you will select one “owner” for each of the intermediate elements (i)-(iv). While each of those elements counts towards 5% of your grade, it counts 10% towards the grade of the “owner”. (So 3*5% + 10% = 25% of your grade.)

(i)-(iv): The intermediate elements are chunked to help move you through a typical project, and are due at designated deadlines (below). To accommodate the diversity of client situations, your team may request an extension as needed; be sure to explain why and think through the implications for later deadlines. Each team must also meet with me the week before Spring Break to make sure you are on track. Further, if you incorporate my feedback on these by the end of the course, I will adjust your grade upward.

(v) In our final class, (Tuesday April 22), you will deliver a final presentation in-class, as a dry-run for you to later present this work to stakeholders at your client organization. At least one person from your team must be present in person; all team members should block the class time to zoom in.

(vi) Your final report will be due for the class and the client during finals period (Friday May 2). (10% of your grade)

Finally, your group will provide feedback that comprises 10% of your final grade.

Readings

There is no required textbook for this class. All required readings will be posted to Canvas, including links to a handful of multimedia “readings” (e.g., podcasts, videos). Where I assign book chapters, I will work with the Penn library to secure online access to these chapters, subject to copyright restrictions.

Application: 

Given the hands-on nature of this course and involvement of outside organizations, the class is capped at 36 students. Interested students will be asked to complete a short application by mid November.

Course credit: 

This class counts as 1 CU towards the OIDD major at Wharton.

Prerequisites: 

None, but it helps to have taken some intro behavioral science class (or at least read Thinking, Fast & Slow and Nudge). This class is effectively an advanced decision processes and behavior change course. Students will get the most out of the experience if they already have a basic understanding of judgment and decision making biases and interventions to mitigate them. Perhaps 1/3 of the class will cover behavioral barriers, biases, and their applications; 2/3 of the class is on experimentation in business with all its complexities.

Past MBA students have mixed feelings about OID 690 Managerial Decision Making. Some think it is a helpful class to take before or in tandem, to reinforce material and prove to yourself how well you actually can remember and apply it; others think the material is somewhat redundant (although the focus on testing and client work is not). Similarly, MBDS students last year noted there is some repetition with Prof. Dimant's class (such as around problems in psychology), but that this class is helpful for going deeper and beyond the material. If you did NOT enjoy those classes, or if some repetition bothers you, the Choice Architecture Lab is probably not a good fit for you.

There is no requirement for quantitative background, but it helps to have taken a statistics class like STAT 6130 or STAT 6210, or have waived out of the statistics requirement due to past training. If you are not generally familiar with the following statistical concepts, I recommend reading about them before class: mean, standard deviation, proportion, standard error, the normal distribution, a t-test.  During the class, you will be engaging in analysis of your experiment's data, but you will have your whole team working on it together.

Students: 

Open to Wharton MBA students and Penn Masters of Behavioral and Decision Sciences students. Priority will be given to Wharton MBAs but we will increase the number of MBDS students we admit this year. Why? Last year's students overwhelmingly appreciated "blended" teams of MBAs-MBDS students, so we plan to continue that this year for all teams.

Caveat emptor: 

In many ways this class is an advanced Managerial Decision Making course; if you did not like OID690, you may not like this course. Further, the bulk of the assignments center on running a research project with an external organization, much like a behavioral science consulting team might do; if you do not like consulting or group work, you may not like this course. Finally, we will cover the statistics and operations of experimentation; if you are experienced running experiments from your time in industry, you may find that those lectures and activities are redundant with your past training.

Class policies:

Given the small size of our class and interactive content, late arrivals can be quite disruptive. If you anticipate having to arrive late to any class, email me at least 2 hours beforehand to explain your tardiness. Failure to do so will count against your participation grade.

Over the years, I have experimented with allowing and prohibiting the use of laptops in class. Based on this experience and on popular opinion by your peers who took this class in the last two years, my policy this spring is as follows: laptops and phones are NOT allowed on your desk during class, unless we are expressly using software (e.g., R, GPower) on the former. Tablets for note-taking are allowed, as long as you only use them for note-taking – i.e., no email, no social media, no internet surfing, etc. If you need to take a call or check an important text, just step out of the room and do so. Treat it like a bathroom break: If nature is calling you - or your mom or friend or a recruiter - just step outside to do your business.