Effective managers do not make decisions in disciplinary silos. A pricing decision requires understanding margin structures from accounting, ratios from finance, customer preferences from marketing, and demand patterns from statistics. My teaching philosophy centers on preparing students to make well-supported business decisions by integrating analytical models across disciplines. Rather than teaching marketing, finance, or accounting in isolation, I show students how these frameworks work together to illuminate managerial problems. I do so through structured, experiential learning that moves students from observation to independence. I take a student-centered approach that puts students, not lectures, at the center of the work and depends on knowing who is in the room and what each of them needs to fully engage.
 
I follow an “I Do, We Do, You Do” approach that scaffolds students’ development as decision-makers. In my Principles of Marketing course, students spend the semester as brand managers for an over-the-counter cold medicine on Interpretive Simulations’ Market Share platform. Early in the term, I introduce a margin model that integrates concepts from across the business curriculum: contribution margins from accounting, markup chains from finance, and competitive positioning from marketing. I demonstrate how to build the model in a spreadsheet, explaining where each number comes from and what it reveals about whether their brand meets retailers’ needs better than competitors’.
 
Next, we collaborate to extend the model to analyze competitors’ actions, discussing the required assumptions and how to interpret results when data is incomplete. Finally, students apply the model independently in their weekly strategy reports, using it to diagnose problems, evaluate alternatives, and justify their decisions. By semester’s end, students not only understand margin analysis but also ask “What does the data suggest?” before making strategic moves. I use similar progressions across my courses: customer lifetime value analysis in Sales to identify which accounts deserve focused attention, markdown optimization in Retail Management to balance inventory and profitability, and conjoint analysis in MBA Marketing to determine product configurations and price points.
 
There is a lot of fear, uncertainty, and doubt bound up in speaking up in class, joining an analytics team, or attending a professional networking event for the first time. I have learned that telling students directly that they belong, and showing them evidence that they are succeeding, goes a long way toward unlocking real participation.
 
In practice, I start with small things like calling on every student over the course of a class. When a student works through a question that requires genuine recall or deeper thinking, I give them a high five. This visible signal of recognition carries weight precisely because it is not handed out for free. One of the proudest moments of my career came from a quiet student in my Fundamentals of Marketing Analytics course who had not spoken up for most of the semester. The day she worked through a question that required recalling and applying material from earlier in the term, that high five meant as much to me as it clearly did to her.

I restate students’ answers and ask whether I heard them correctly, which confirms understanding while modeling the active listening I want them to practice. I explain that this question-and-answer process prepares them for the workplace. Students who are less comfortable speaking up understand why the discomfort is worth pushing through.

I treat student feedback about my materials the same way. After a student told me my course website’s color scheme was hard to read due to color blindness, I reworked it. Another student’s suggestion led me to strengthen text in sections that were hard to follow. I would not catch either change on my own.
 
The content of my courses reflects the same commitment. In Retail Management, our discussion of where to locate a store extends into how housing policy has shaped which neighborhoods have access to retail in the first place. In my Analytics courses, I raise who has access to which technologies and how data analysis can be used toward both pro-social and harmful ends, treating these as systems questions. How did conditions get this way? What could change them?

In my Principles of Marketing and Marketing capstone courses, I start the term with a discussion on aging and declining population. How does that change products and price points? What kind of retailers would we expect more and less of, and how many of them? How could employers respond with a decaying labor force?
 
The same intentionality carries outside the classroom. For example, when I organize an analytics career panel, I look for participants who reflect our student body, and I point students toward professional communities such as Web Analytics Wednesday and the Women in Analytics conference, because seeing someone who looks like you succeeding in a field changes what seems possible.
 
This approach develops more than business acumen. When students learn to build models, question assumptions, interpret results, and defend recommendations, they develop critical thinking skills that extend beyond the classroom. They learn to communicate complex analyses to different audiences, listen critically to peer feedback during collaborative exercises, and revise their thinking when data challenge their intuitions. These skills make them valuable employees in their first roles, but more importantly, they possess the analytical and communication capabilities that make them informed citizens who can evaluate evidence, consider trade-offs, and make reasoned judgments in a complex world. 
 
My goal goes beyond preparing students for their first job to developing their capacity to make well-supported decisions throughout their careers and civic lives. I hold this goal for every student who walks into my classroom, regardless of the background they walk in with.