Connecting Data Analytics with Managerial Success

Course Preview Deck (Updated on June 19th, 2024)

Course Code: BUS 36

Instructor Name: Jeremy Gu

• Semester: Summer 2024 (Entire Stanford Summer Catelog)
• Course Registration: Official Stanford Continuing Studies Page
• Canvas: TBD
• Syllabus: Google Doc, or this website
• Dates: 6/27 - 8/15 (Except July 4th - No Class)
• Parking: Free parking in Stanford after 4PM.
• Final Project Submission: Please submit final project through Canvas.
• Class Sessions: Thursdays 7:00 to 8:30pm (PT), On campus

Course Description

This course is designed for managers and professionals from various domains, such as marketing, finance, product management, and operations, who aspire to lead data analytics teams but lack a technical data analytics background.

Data analytics teams are often embedded within different functions across a company, each with unique goals and requirements. This course aims to equip students with the skills and knowledge needed to align data teams' efforts with students' specific functional objectives.

No prior mathematics or coding expertise is required. Students will learn how to ask the right questions, understand the capabilities and limitations of data analytics, and translate insights into actionable strategies.

Class Sessions and Recording

Meeting days and times: Thursdays 7:00 to 8:30pm (PT)

Meeting location: On campus

Class recordings will not be available.

Course Features

• Live session
  • Lecture, discussions, and Q&A
  • Requires interaction and active participation
  • Guest speakers
  • An informal drop-in time for student Q&A
• Assignments & Coursework
  • Instructor will provide feedback on assignments
  • Assignments posted in Canvas
• Individual conferences available by request

Grade Options and Requirements

• No Grade Requested (NGR)
  • This is the default option. No work will be required; no credit shall be received; no proof of attendance can be provided.
• Credit/No Credit (CR/NC)
  • Students must attend at least 5 of the 7 class sessions
• Letter Grade (A, B, C, D, No Pass)
  • Students must attend at least 5 of the 7 class sessions, and turn in a final assignment.

*Please Note: If you require proof that you completed a Continuing Studies course for any reason (for example, employer reimbursement), you must choose either the Letter Grade or Credit/No Credit option. Courses taken for NGR will not appear on official transcripts or grade reports.

Target Audience and Prerequisites

This course is designed for managers and professionals from various domains, such as marketing, finance, product management, and operations, who aspire to lead data analytics teams but lack a technical data analytics background.

Data analytics teams are often embedded within different functions across a company, each with unique goals and requirements. This course aims to equip students with the skills and knowledge needed to align data teams' efforts with students' specific functional objectives.

No prior mathematics or coding expertise is required. Students will learn how to ask the right questions, understand the capabilities and limitations of data analytics, and translate insights into actionable strategies.

Learning Objectives

Students will be able to get ready as a data leader:

1. Effectively manage data analytics teams, projects, and budgets. 📈
2. Enhance data leadership skills through real-world examples. 🌍
3. Get ready to lead data innovation and drive organizational success. 🚀

The final project requires students to develop a plan for establishing a new, very first data analytics department and present the plan to the company's CEO and board. The mini homework assignments build the necessary skills and knowledge for this final project, covering key aspects of data leadership.

Textbooks/Required Materials

Two books below are optional and can be supplemental materials.

Tentative Weekly Outline

Week One (6/27/2024)

Week 1: Overview: Decoding the Data Analytics Landscape

• Course overview, learning objectives, and logistics
• Fundamentals and applications of data analytics
• Importance of data analytics in modern leadership and decision-making
• Relationship between data analytics, data science, and business intelligence
• History and future trends of data analytics
• Group discussion: should all data leaders be technical?
• Final project overview: Establishing a data department. In this final course project, you will assume the role of a newly appointed data leader in a real or hypothetical company. You will develop a comprehensive plan and proposal for establishing and managing a new data analytics department, addressing key aspects such as resources, projects, timelines, and risks. The project will culminate in a presentation (no more than 20 slides) to the company's CEO and board members.

Week Two (7/11/2024)

Week 2: Data Analytics in Business Decision-Making

• Defining business problems and translating them into data problems
• Identifying and selecting relevant metrics
• Understand "data" from data sources, data governance, data quality, and data engineering
• Explainable results vs. Black-box Method
  • Transparency and interpretability
  • Regulatory and compliance considerations
  • Building user trust for high-stakes decisions
• Communicating effectively with data analytics teams
• Case studies: Leveraging data analytics to optimize ad design, targeting, and investment decisions across various marketing platforms to maximize customer acquisition and ROI.
• Group discussion: Whether data should be used to support existing hypotheses or to shape new hypotheses?
• Mini homework #1: Reflect on a past collaboration with a data analytics team, introducing your responsibilities, how you cooperated, difficulties encountered during the collaboration, and the final result.

Week Three (7/18/2024)

Week 3: Building Effective Data Analytics Teams

• Roles, responsibilities, and skills of data analytics team members
• Recruiting, interviewing, and evaluating talents
• Setting goals and managing analytical project progress
• Collaboration between data analytics teams and business departments
• Analytics teams in day-to-day work: tools & workflows
• Group discussion: Strategies to ask company executives (CFO, CEO, HR, etc. ) for more head counts in data analytics teams?
• Mini homework #2: Write a plan to communicate with a CEO who believes that data-driven digital transformation should be carried out and novel data analytics tools/approaches should be introduced to the company. The plan should include your long-term and short-term strategies for implementing these changes related to data analytics.

Online Session I (7/17/2024 Wed 5PM)

Topic. Fireside Chat with Ethan Evans

• Speaker: Ethan Evans
• Retired Amazon VP LinkedIn Top Voice
• Optional 60-min Zoom Session*

Join us for an exclusive 60-minute Fireside Chat with Ethan Evans, a visionary leader who served as VP at Amazon for 15 years. In this engaging discussion, Ethan will share his invaluable insights on leveraging data to drive product decisions and organizational success. Mark your calendars for July 17, 2024, and get ready to gain a fresh perspective on data leadership from one of the industry's most respected voices!

Through a casual Q&A format, Jeremy will dive deep into Ethan's wealth of experience, exploring topics such as:

• The evolution of data science at Amazon and its impact on decision-making
• Critical data skills for modern leaders at director, senior manager, and above levels
• Collaborating effectively with data science and analytics teams
• Balancing technical expertise with strong leadership and team management

Don't miss this rare opportunity to learn from a seasoned leader who has harnessed the power of data to drive innovation and growth. The session will conclude with a live audience Q&A, giving you the chance to ask Ethan your burning questions directly.

*This guest session will be held outside of regular class hours at a time to be determined. Students are encouraged to attend, but it is not mandatory. The session will be recorded and made available for those unable to attend live.

Week Four (7/25/2024)

Week 4: Data Analytics Leadership and High-Performing Teams

• Guest speaker session: How data leaders drive organizational success
  • Anirban Deb, SVP of Gap Inc.
• Strategies for building, scaling and optimizing data analytics teams
• Organizational design, and its rationale
• Cultivating a data-driven decision-making culture
• High-performing analytics teams bring in large business impacts
• Building relationship with stakeholders
• Group discussion: The future of analytics in the AI revolution
• Q/A with guest speaker
• Mini homework #3: Please describe your assessment of a data analytics team: what value you think an excellent data team can bring to your business and organization, and correspondingly, what are the costs and risks?

Online Session II (7/30/2024 Tuesday 4PM)

Topic. Analytical Tactics to Inform Product Decisions

• Speaker: Rachael Maltiel Swenson
• Former Meta Product Growth Director
• Optional 60-min Zoom Session*

If you're not using data to guide your decisions, you're just guessing. A large amount of data is created to measure user behavior that can be tapped into to guide product decisions. Knowing how to utilize data to improve product decision-making can ensure efficiency, velocity, and ultimately impact. Different analytical approaches best enable different points of decisions, be it surfacing potential opportunities, guiding prioritization, or enabling a data-driven culture with metrics to rally around.

In this conversation, Rachael will share how to:

• Align your success metrics with your strategy
• Analyze funnels and segments to find investment opportunities
• Impact-oriented prioritization through opportunity sizing
• Measure through experimentation for confidence in impact/results/resourcing
• Step into product analytics leadership through product strategy focus and partnership

*This guest session will be held outside of regular class hours at a time to be determined. Students are encouraged to attend, but it is not mandatory. The session will be recorded and made available for those unable to attend live.

Week Five (8/1/2024)

Week 5: Integrating Data Analytics into Business Leadership

• How business leaders integrate data analytics teams into their leadership
• The importance of domain expertise in data leadership.
• Cross-functional collaboration between analytics teams and domain experts
• Essential data literacy for business leaders
  • Descriptive analytics vs. predictive analytics
  • Causality vs. correlation
  • A/B testing and experimentation
  • Commonly-used advanced acronyms
• Case Studies: Prioritization of Product roadmap based on data insights
• Group discussion: how do you evaluate your data analytics team's performance?
• Mini homework #4: In your role as a business leader, outline the key insights you expect your data analytics team to provide for your specific business context. Describe how you plan to use those data-driven insights to inform decision-making and drive your business objectives.

Online Session III (8/5/2024 Monday 4PM)

Topic. Legal Considerations in Data Analytics: Crucial Takeaways for Managers

• Speaker: Christine Baylet Bergeron
• Senior Corporate Counsel - Technology and AI Governance at Shipt
• Optional 60-min Zoom Session*

In this presentation we will cover the legal issues managers should be aware of to lead compliant and ethical data analytics teams. The presentation will focus on the key topics of US based data privacy laws, intellectual property rights, and legal risks associated with using third-party data. Additionally, we will analyze case studies to highlight common pitfalls and missteps companies have made while grappling with regulatory requirements in their data driven initiatives. Finally, we will end the session by discussing the ethical implications of using AI and algorithms in decision-making processes, and the importance of fairness and transparency. Participants should leave the presentation with a foundational knowledge of the legal considerations surrounding data analytics, empowering them to make better informed and responsible choices for their organizations.

*This guest session will be held outside of regular class hours at a time to be determined. Students are encouraged to attend, but it is not mandatory. The session will be recorded and made available for those unable to attend live.

Week Six (8/8/2024)

Week 6: Data-Driven Investing and Value Creation

• Guest speaker session: Data-driven decision-making in investment
  • Leo Yao, Managing Partner of Mount Healy Capital.
• Developing data strategies for venture capitalists
• Using data to create new business value
• Measuring the success of data initiatives
• Group discussion: How investors value data companies?
• Q/A with guest speaker
• Mini homework #5: Imagine you have recently inherited a large data organization, with several data analytics managers and dozens of analysts now reporting to you. Draft an outline for your first all-hands meeting, where you will introduce yourself, leadership style and visions for the data org.

Week Seven (8/15/2024)

Week 7: Future Hot Topics in Analytics and Course Wrap-up

• Course review and reflection
• Continual learning: Recommended learning paths for leaders that outlines the essential skills, concepts, and best practices they need to acquire to become successful data leaders.
• Case Studies: Use of Large Language Model (LLM) for automating data analytics in fraud detection
• Empowering Analytics Experts: 4 ways to harness LLMs for your specific domains
  • Retraining a new LLM model with small domain-specific data
  • Fine-tuning a pre-trained model with hundreds or thousands of domain-specific examples
  • Retrieval Augmented Generation (RAG): Enhancing pre-trained models with external knowledge bases for domain-specific tasks
  • Prompt engineering: Crafting effective prompts to extract domain knowledge from pre-trained LLM models
• Ethical considerations in data-driven decision-making
• Final course project presentations and peer feedback