Digital Product Management (In-Person Class)

This is a 7-week course I currently teach in the residential MBA program at UVA’s Darden School of Business. If you’re looking for the online course on Coursera, check out: Digital Product Management: Modern Fundamentals.

Course Description

This course will introduce students to the modern practice of product management in digital. Students will learn how product managers create product/market fit for new products and enhance it for existing products. The students will also learn how generalist product managers establish successful interfaces with key functions like design, development/engineering, data science, sales/marketing and support/operations.

This course will help students understand best current practices in the area and how to apply them in their role as product manager. We’ll pay special attention will be paid to lessons learned in Silicon Valley and other innovation centers.

By the end of this course, students will understand how to:

– Explore and test product/market fit
– Collaborate with an interdisciplinary product team on design and development via agile
– Collaborate with sales and marketing teams to scale product/market fit
– Charter and manage interdisciplinary teams to support your product

Prerequisites

There are no course prerequisites.

Teams + Projects

There is a group project at the end of the course.

Course Structure

The material below is organized around sessions of roughly 90 minutes/each.

Grading

Category	Due Date	Percent of Final Grade
1. Attendance & Participation	Every day/ongoing	50
2. Individual Assignments	(as stated on Canvas)	20
3. Team Project	Exam period	30

Attendance & Participation: 40%

My objective is to provide a stimulating environment for you to learn the process of software development. This portion of your grade includes the following:
being prepared for class: understand the topics at hand and being able to discuss the cases and assignments
on-time, full attendance
I expect you to inform me before class if you will be missing. Absences for reasons other than illness for which I do not receive prior notice will count against your class participation grade.

Individual Assignment: 20%

This is a ‘PM Caselet’ which will be graded based on a rubric available to you.

Group Project: 40%

This is your team explanation of what you did and why, assessed with the same rubric above.

Session 1: What is product/market fit and how do you find it?

Learning Objectives

After this class, you will be able to:
1. Explain the difference between a project plan and a product pipeline (and the roles of project manager vs. product manager)
2. Analyze a new venture or product in terms of product/market fit
3. Frame progress on product/market fit with specific, testable hypotheses and experiments

Tech Note

Tech Note: Project Management vs. Product Management

(COMING SOON)

Case

Aardvark

Class Preparation

1. Review the tech note and be prepared to discuss the following questions:

a) What’s product management? How is it different than project management?
b) What’s an example of an endeavor that you think is a good fit for product management? Why?
c) What about project management? What’s the difference?

2. Review the case and be prepared to discuss these questions:

a) What existing customer needs and habits is Aardvark exploring? For who? What current alternative(s) would it replace? Why is that interesting from a customer perspective? Why is it interesting from a venture perspective?
b) You walk into the office on Monday morning. What do you want to know about the users that signed up last week? What about the ones that signed up six weeks ago?
c) Given their backgrounds, why didn’t the founders start by just build some software to start testing a solution? Why not go straight at it?
d) For a moment, let’s pretend they were starting today and there was AI tooling and platforms available which make software a lot easier to build. How might that change their approach?
e) What is a ‘smoke test’ and how did Aardvark use them? What was hard about smoke tests? What’s the difference between a smoke test and a prototype? How are they the same? Different?
f) Product/market fit is a central concept in modern product management and product creation in general. The following Wikipedia entry is a good, quick introduction: Wikipedia on Product/Market fit. How would you describe the situation at Aardvark in terms of product/market fit?
e) Normally, we consider cases in the context of their particular time and place. But here let’s create a pretend anachronism and suppose Aardvark started today. How relevant is social search today given that historically unassailable search products like Google are at risk? And given how much (relatively) easier AI has made it to build software, would you have executed differently today than Aardvark did in the case?

Session 2: How do you scale product/market fit?

Learning Objectives

After this class, you will be able to:
1. Analyze a new venture or product in terms of product/market fit
2. Frame progress on product/market fit with specific, testable hypotheses and experiments
3. Use the above to facilitate discussions on what to focus on and what to defer, week to week, quarter to quarter

Tech Note

Tech Note: Integrating Around the Job to Be Done

Case

Dropbox: ‘It Just Works’

Class Preparation

1. Review the reading and be prepared to discuss the following questions:

a) What’s a job to be done (JTBD)? How is it different than a product?
b) How would you test the importance of a JTBD for a given population of prospective customers?
c) What is the role of qualitative evidence vs. quantitative evidence in identifying and testing for JTBD?
d) What are the user JTBD at Dropbox?

2. Review the case and be prepared to discuss these questions:
a) What jobs-to-be-done was Dropbox solving? For who? What current alternative(s) would it replace? How were they able to validate the initial concept without building working software?
b) For an individual customer, how would you unpack the journey from ‘never heard of Dropbox’ to happy, profitable customer? What would that look like across acquisition, onboarding, engagement, outcomes, and retention?
c) For the above, what are the key levers you’d want to pull to test improvements in one of those? How would you decide whether a given new idea was a success or a failure?
d) Looking at their Y-Combinator application (Exhibit B), what product/market fit hypotheses would you say they validated vs. invalidated? How would you have tested those early hypotheses?
e) Where do you think they should focus now and why? More importantly, how can they test that focus quickly to see if it’s the right recipe for the rapid growth they need? What metrics would you use as focal points in that testing?
Note: There is a lot of information in this case (example: financial statements) that may or may not be central to answering the questions above.

Session 3: What’s an ‘experiment’ in product management?

Learning Objectives

After this class, you will be able to:
1. Unpack and frame ideas as a sequence of hypotheses, including dependent and independent variables
2. Effectuate between experiment vehicles given a particular set of both resources and target inferences
3. Explain the management foundations for a culture of experimentation

Reading

The Surprising Power of Online Experiments 

Case

Booking.com

Session 4: How might you use product/market fit to focus your execution in a new project?

Learning Objectives

After this session, students will be able to
1. Explain the fundamentals of persona & JTBD hypotheses and how they relate to creating hypotheses on product/market fit
2. Frame testable propositions relative to a JTBD and pair it with alternative MVP’s
3. Map the customer experience across your proposition to maximize observability

As we continue to explore how PdM’s drive to product/market fit by building better hypotheses, we’re going to try a little active practice.

Tech Note

Tech Note: Digital Product Management with Hypothesis-Driven Development

Individual Assignment

PdM Caselet: See Graded Assignment below

Class Preparation

1. Review the tech note and be prepared to discuss the following relative to your working draft (see below):
a) What’s different about the job of digital product management vs. the job of general management?
b) How do you know when a product or feature is done?
c) What’s the least and most expensive way to test a new idea?

2. Complete the Individual Assignment and come prepared to discuss your work

In-Class Reference

Please see here for the discussion questions we’ll use in our in-class breakouts: PM Caselet Questions

Graded Assignment (Individual)

As a warm up for both the final assignment and the rest of your life, you’ll be framing a testable proposition for a product you know. This could be for a product you’ve worked on, an existing product you’ve used, or a product idea you’re contemplating. The most important thing is to make sure your work is internally consistent and, above all, testable.

As a PM, you’re generally free to frame and test the proposition as you see fit. However, you do have to bring other stakeholders along with you. As you prepare this material, think of it as a communication and collaboration tool for such stakeholders- designers, developers, management, etc. You’re not selling, you’re trying to get to the right focus- polish on these materials is not important, but depth and testability is. All that said, you may be asked to share your work over Zoom, so please make sure you come prepared with a digital version of whatever you do (ex: if you sketch a storyboard on paper, just photograph it and drop it into a digital doc).

For please sketch/draft materials that help answer the following questions:

0. What is the basic idea for the company (or product)?
What’s the basic idea? What’s the business model?
Note: If you’re focused on a particular existing product at a big company (ex: Gmail), you can just focus on the individual product (like Gmail vs. Google/Alpha, at large).

1. Who is our target user and what job are we hoping to do for them?
How would you screen a subject to decide if they are or are not this user?
What kind of shoes do they wear?
Why is the JTBD in question important to them? Where does it fit into their life?
What alternatives are they using today?

2. What’s better enough about our proposition relative to the alternatives?
Generally, when/why do we think our proposition is better?
How would you frame that in testable terms like, ‘if we [do something for] [the user], then they will [respond with some observable behavior]”?

3. How does the customer experience unpack?
Generally, when/why do we think our proposition is better?
How would that look in terms of qualitative evidence and qualitative evidence: for example, a customer experience (CX) map with a storyboard?
Note: I like to encourage hand-drawing for the storyboard part, but if you’re averse to that I did create this GPT: Story Mapping GPTLinks to an external site..

4. What new idea would you like to test next week?
And how? Is there an MVP we could use that minimizes time and waste, getting you to a pivot or persevere decision?
What focal metric (DV) would you use and what’s your threshold for a pass/fail on the experiment?

You can find a template and example work here: Template & HVAC in a Hurry Example Brief.

Session 5: How does all this work for internal products?

Learning Objectives

After this class, you will be able to:
1. Analyze a new venture or product in terms of product/market fit relative to internal stakeholders
2. Effectuate the above for testability

Tech Note

Tech Note: Agile Development

Case

Tapping into a Digital Brain: AI-Powered Talent Management at Infosys 

Class Preparation

1. Review the readings and be prepared to discuss the following questions:

a) What is agile? How do you know if it’s working?
b) What’s been your experience with agile, if any?

c) How is generative AI changing the way developers work? What’s the economic impact of that?
d) What are the impacts specifically for PdM’s?

2. Review the case and be prepared to discuss these questions:

a) Who and what JTBD is Infosys management considering when they talk about AI-powered talent management?
b) For these, how might they observe how they’re doing over time and over new iterations of the system? For an individual engagement manager using the ‘digital brain’, how would you unpack the journey from ‘never heard of it’ to happy, more productive user? What would that look like across acquisition, onboarding, engagement, outcomes, and retention?
c) Please draft a ‘CX Map’ to describe the journey and how you’d measure it with a focal DV (dependent variable) that is a rate or ratio. There’s a template here (and an example) CX Map in Agile Team Charter Template.
d) How might they best sequence the program to minimize waste and maximize outcomes?

Session 6: How do teams and product programs make good decisions as they evolve?

Learning Objectives

After this session, students will be able to
1. Explain the fundamentals of agile and what focal points companies need to consider when applying it
2. Evaluate and prioritize strong vs. weak opportunities to increase performance with agile

Tech Note

Tech Note: Diagnosing the Economics of Your Code

Case

Saving Griffin

Class Preparation (Individual or Group)

1. Review the tech note and case and be prepared to discuss the following:
a) What is a stack? A toolchain?
b) How do you define success for a digital product team? What are the drivers of that?
c) What is the economic significance of these for a company or team? What’s an example of a choice that might be good in one circumstance, but bad in another?
d) What are the most important features (IV’s/independent variables) of ‘F’ for the Griffin? How do the three different options look across those features?

2. Review the case and be prepared to discuss the following:
a) Regarding the case, how would you frame a good user experience? How might it unpack, in, say, a storyboard across trigger event to start trying Griffin, the actions of the user, and their reward/conclusion?
b) For these, how might they observe how they’re doing over time and over new iterations of the system? For an individual user, how would you unpack the journey from ‘never heard of Griffin 2.x’ to happy, more productive user? What would that look like across acquisition, onboarding, engagement, outcomes, and retention?
c) Please draft a ‘CX Map’ to describe the journey and how you’d measure it with a focal DV (dependent variable) that is a rate or ratio. There’s a template here (and an example) CX Map in Agile Team Charter Template.
d) Regarding the case, do you agree with Sean’s framing of the options? Does he know enough to choose a direction? If not, why not, what else should he learn, and how?
e) What are the three options? Which option would you choose, and why? For the coming quarter, how would you define your OKR’s for that option?
f) For the option you choose, what are the key observations and metrics you’d use to evaluate progress and decide whether you’re still on the right path?
g) What are some things you’d test to see if they improve on those metrics?

Session 7: How do learning, testing, and scaling work when physical goods are involved?

Learning Objectives

After this session, students will be able to
1. Explain the fundamentals of agile and what focal points companies need to consider when applying it
2. Evaluate and prioritize strong vs. weak opportunities to increase performance with agile

Reading (Watching)

Laura Klein: Riskiest Assumptions

Case

Rent the Runway

Class Preparation (Individual or Group)

1. Watch the video and be prepared to discuss the following:
a) Why is it important to identify assumptions?
b) How should you prioritize them?
c) How would you apply this to Rent the Runway’s situation/or any of the companies from our cases?
d) Words are faulty instruments, but what might be problematic about the term ‘validating’ with regard to assumptions?

2. Review the case and be prepared to discuss these questions:
a) What jobs-to-be-done was Rent the Runway solving (at the time of the case)? For who? What current alternative(s) would it replace? How were they able to validate the initial concept without building working software?
b) For an individual customer, how would you unpack the journey from ‘never heard of Rent the Runway’ to happy, profitable customer? What would that look like across acquisition, onboarding, engagement, outcomes, and retention? What are the key levers you’d want to pull to test improvements in one of those? Please draft a ‘CX Map’ to describe the journey and how you’d measure it with a focal DV (dependent variable) that is a rate or ratio. There’s a template here (and an example) CX Map in Agile Team Charter TemplateLinks to an external site..
c) Other than the end customer, what roles inside the company are crucial to making the infrastructure work? What are their JTBD?
d) At what point would you say RtheR started to transition to some type of substantial product/market fit? How do you think their focus changed or should have changed as they move from learning to scaling in that regard?

Session 8: How is AI changing what drives value with enterprise (B2B) products?

Learning Objectives

After the this class, you will be able to:
1. Unpack and sequence the assumptions and hypotheses related to a hybrid digital + physical customer experience (CX)
2. Evaluate concierge vehicles for testing ideas, even where physical products or in-person CX is involved

Reading (Watching)

Tech note: A Primer on OKRs

Case

C3.ai-Driven to Succeed 

Class Preparation

1. What’s an OKR and why do companies use them? What jobs do they do vs. what underlying issues might they surface?

2. Describe C3’s operating environment- what are the big opportunities? Who’s executing on them successfully and why?

3. What do you think of the choices they’ve made so far?

4. What do you think they should do next?

5. What do you think Siebel should do next and how will he know if it’s working out?

Session 9: How does security figure into the life of a product and the role of a PdM?

Learning Objectives

After this class, you will be able to:
1. Describe security risks in terms of attack patterns and defense patterns
2. Explain the major attack surfaces across the security ‘stack’: Behavioral Entities, Applications, and Platforms
3. Frame a retrospective on a security breach

Reading (Watching)

Cybersecurity in the Age of AI (COMING SOON)

Case

Cybersecurity at FireEye: Human+AI

Class Preparation

1. Please read the tech note and be prepared to discuss the following:
a) The note frames security as no longer a “specialist concern” but a core managerial responsibility. As a product manager, how would you integrate security considerations into your work on a product pipeline without paralyzing innovation?
b) Table 1 distinguishes “good” vs. “bad” practices (e.g., red-team testing vs. passive scans, automated compliance vs. reactive audits). Which of these cultural or organizational shifts would be hardest to implement in a legacy company? Why?
c) The “security stack” includes behavioral, application, platform, and hardware layers. Which layer is the most underappreciated by managers, and how should they address that gap?

2. Please review the case and be prepared to discuss the following:

a) FireEye uses an “automatability spectrum” to decide which tasks should be AI-driven versus human-driven. If you were leading product at FireEye, how would you set priorities for automation?
b) The Atomicity ML tool for threat attribution improved analyst productivity but required extensive cross-functional collaboration (data science, SMEs, IT). What organizational enablers or barriers most affect the success of such initiatives?
c) The case highlights challenges in data quality, labeling, and evolving threat patterns. If you were FireEye’s CTO, how would you justify continued investment in ML models given these ongoing costs and uncertainties?
d) The Human + AI model raises issues of trust, explainability, and technical debt. From a manager’s perspective, how do you balance the push for speed and automation with the need for human oversight and interpretability?

Session 10: How do product managers create successful relationships with their development colleagues?

Learning Objectives

After this session, students will be able to
1. Explain more specifically what high performance looks like on the jobs of going from design to release
2. Identify specific activities that helps teams improve on this front
3. Identify specific metrics that help teams observe how they’re doing

Reading

Five Things every PM Should Know about DORA

Reading

HBR: Six Myths of Product Development

Class Preparation

1. Complete the DORA reading and be prepared to discuss the following:

a) DORA’s four metrics focus primarily on engineering and operational performance. How should product managers balance these metrics with customer-centric metrics such as user adoption, engagement, and revenue impact?
b) If a PdM discovers high deployment frequency but an unacceptable change failure rate, what are their next steps?
c) The article suggests PdMs should place “fewer things into the pipeline, but expect better results” and lead with a testable hypothesis. How does this approach compare with traditional roadmap planning and prioritization?

2. Complete the Six Myths reading and be prepared to discuss the following:

a) First Impressions: Which of the six myths feels most familiar or intuitive to you, and why do you think it persists in so many organizations?
b) Relative to Experimentation: Both of Thompke’s articles (this one and the one on experimentation Download experimentation) argue that managers’ mental models — whether about efficiency, planning, or risk — often undermine innovation. What connects the “six myths” to the obstacles to building a culture of experimentation?
c) Curiosity vs. Utilization:
Myths lens: High utilization creates queues, delays, and discourages exploration
Experimentation lens: Managers must create “slack” for curiosity and unplanned discoveries
How can leaders defend “underutilization” as a strategic choice in cultures obsessed with efficiency?
d) Plans as Hypotheses:
Myths lens: Treating plans as fixed commitments leads to rigidity. Rigidity is bad for innovation.
Experimentation lens: Experiments encourage planning and stakeholder management around testable hypotheses vs. fixed plans.
What practices can managers adopt to help teams treat plans as living documents guided by evidence?
e) Batch Size & Experimentation Cycle:
Myths lens: Large batches delay feedback and multiply risks
Experimentation lens: Rapid, small-scale tests reduce risk by surfacing problems earlier
What organizational structures (e.g., repositories, centers of excellence, automated tooling) best support smaller, faster learning cycles?

Session 11: How do you prototype your ideas with AI?

Learning Objectives

After this session, students will be able to
1. Apply a stepwise process for going from idea to code
2. Identify attractive opportunities for customGPT’s
3. Go from idea to working release in openAI’s customGPT development environment

Watching

See video playlist below

Preparation

1. Create a CustomGPT
a) This GPT should probably relate to whatever topic your group has selected for its final assignment. However, if there’s another topic that particularly interest you all, that is also fine to use for this.
b) Review the videos below and be prepared to discuss your work through the process of: 1) focusing your design intent 2) unpacking the UX into observable steps 3) effectuating between alternatives and 4) iteratively coding (configuring) and testing the GPT.

NOTE 1: This process is entirely codeless and does not require any coding experience.

NOTE 2: The videos that follow are pulled directly from an online course, so please ignore references to that. Also, I left in the video about interfacing to your customGPT from its API (because: interesting), but that is not part of this assignment.

NOTE 3: The videos mention a few links. They are:
Sample ‘Knowledge’ Input to GPT
Storyboarding GPT
Example Chat Transcript with GPT

Playlist (customGPT)

contact: cowana@darden.virginia.edu for the playlist

Session 12: How does an enterprise organize to foster wins with AI?

Learning Objectives

After this session, students will be able to
1. Analyze the focus of an agile team charter and evaluate its focus and actionability

Reading

Building a Culture of Experimentation

Case

Customer-Centric Design with Artificial Intelligence: Commonwealth Bank 

Class Preparation

1. Review the tech note and be prepared to discuss the following:

a) Shaping Attitudes: Thompke emphasizes that experimentation requires a “complete change of attitude” rather than just tools and processes What specific behaviors should managers encourage or discourage to shift mindsets toward curiosity and acceptance of failure?
b) Hiring & Onboarding: Booking.com looks for employees “OK with being proven wrong” and trains them in experimentation from day one. What should managers prioritize in recruiting, onboarding, and professional development to sustain this mindset?
c) Metrics & Incentives: IBM tied part of marketing units’ budgets to experimentation goals, while also creating contests and recognition programs. What incentive systems best reinforce a culture of experimentation without encouraging gaming or superficial tests?

2. Review the case and come prepared to discuss the following:

a) Consider ways in which consolidated data across a bank might improve customer engagement. Can you think of other industries where this type of consolidation of data enables better customer engagement?
b) Focus specifically on the NBC campaign “Save On Other Financial Institution ATM Fees” and the data provided in the spreadsheet.
c) How well can AI models predict the success of a “Save on OFI ATM fees” NBC? Which factors do you believe result in a higher/more successful response rate? How does this differ across the various channels? How might these insights be useful for the business?
d) From a managerial perspective, what’s important to initiating and stewarding a new initiative like this? How do you balance the initial pains and gains?

Sessions 13 & 14: Final Presentations

Format: Presenting

Each team will have 5 minutes (max) to present and around 5 minutes for questions. I’ve posted here the big questions I would be consider answering. However, it’s not important or even advisable to give all of those equal treatment. I would consider what you think is most specifically important to your product and focus on, say two to maybe three of these. For example, if it’s a new product or CX (customer experience) that enhances an existing product, carefully framing the existing product’s product/market fit may be particularly important. On the other hand, if it’s a startup idea, the specifics and testability of the CX might be more important.

Focal Questions
1. What does or what might product/market fit mean for this product? If it’s part of a larger product portfolio, how does it fit into the parent company’s business model design?
2. What are the relevant JTBD and VP’s (value propositions)? What are current alternatives does the product proposition need to ‘beat’?
3. What is the CX? What triggers it? What are the actions? Where is the user and what are they doing during this? What’s a successful reward/conclusion to it? Note: a storyboard is a good way to describe this.
4. What are the focal observations you’d want to make on an individual customer journey? Note: a CX map is a good way to describe this.
5. What would you do with this product next week to move the needle on however it defines success? What’s the testability of that execution?

Presenting
How should you present? You have five minutes, so I would decide specifically where you want to focus. I would generally avoid making specialized slides that don’t relate specifically to the work itself, but slides are fine and if that’s what makes you comfortable presenting, that’s just fine. Presenting from the charter itself is fine.

Format: Reviewing (as Audience)

Great questions will have to do with the team’s focal hypotheses and how they might test them.

Graded Assignment (Group)

While this isn’t due until the end of the exam period, I would plan to have this generally in the state of a working version so you can summarize it in your presentation.

Everything a product manager does should be anchored in one of two activities: 1) exploring product/market fit or 2) scaling product/market fit by creating productive interfaces with collaborators. If you’re doing something other than this, you may be doing something that’s necessary at the moment, but you risk becoming a ‘product janitor’, reacting to the results of a broken infrastructure instead of building a great product.

For the final project, you will draft an Product Charter. The job of this document is not to serve as a plan, per se, but rather as a set of focal points for a hypothetical product team of 7-12 individuals. This is the team’s reference, which they’ll update, for helping them make focused, testable decisions, week to week, quarter to quarter.

Ultimately, the real punchline of this work is your experiment design- the rest of the material is context for the experiment.

Here are a few initial things to consider as you get started:

1. If you’re working on a new product or product modality within a large, existing company, are the JTBD+VP’s you’re looking at specific enough? Are they clearly linked back to the parent company and/or product? For example, ‘Spotify’ would be too broad a topic. A roughly right-sized topic would be something like the customer JTBD of enjoying music while driving, or discovering new podcasts.

2. Is the materially internally consistent? Does it reflect your current point of view on the company or product?

3. Is the experiment actionable?

Note: Whether it’s through links in the Charter or notes in your submission, please submit all your working items: code, designs, test results, etc.

Assessment & Grading

Here are a few questions I would think through:

1. How well defined is the company’s overall business model design & its view of product market fit? (Parts 1, 2 of charter) As you consider the balance of the material from the individual team, is it clear how it aligns with the company-level view of p/m fit? For example, could you see how company-level OKR’s would cascade to and align with the team-level OKR’s?

2. How well delineated is the team’s target JTBD, VP, etc. (Part 2)? How clearly does it align with the working view of product/market fit the the company as a whole?

3. How testable is the customer journey for the team’s target JTBD (storyboard & notes)? How testable is the CX Map (acquisition, onboarding, etc.)? Are the metrics actionable? Are the storyboard and the CX Map consistent?

4. How did the team define their demand hypotheses and propose small batch (≈1 week) testability with MVP experiments, including metrics?

For more on how to specifically check over your fundaments, please see this rubric: Rubric for Product Charter.