Are you prepared for a digital- and data-driven world?
Simply having a digital plan of action today is no longer enough. Organizations, entrepreneurs, and leaders aspiring to succeed in today’s business world drive toward true digital transformation. How do you create value in digital worlds, and how is the approach different from traditional analog environments? How can you harness the power of data, create the right mindsets and skill sets, and align your teams and organizations on the digital journey for maximum success? Beyond the opportunities, what are the sets of responsibilities that leaders are increasingly confronting in digital settings?
Combined, the courses in Driving Digital Success provide the frameworks and methodologies to turn data into insight, technologies into strategy, and opportunities into value and responsibility. These courses are curated to help you develop a data-first mindset, improve your digital strategic thinking, and learn how to navigate, manage, and lead in these environments. You will build the confidence to provide practical data insights to improve analysis, communication, and decision-making.
Who is this series for?
Digital transformation is an imperative for virtually every organization in today’s world—from finance to non-profits, from health care to entertainment. Driving Digital Success is for any entrepreneur, manager, executive, or individual contributor looking to develop digital and data competency.
About the Faculty
Courses in the Driving Digital Success series represent the breadth and depth of Harvard University and its faculty. Learn from professors across disciplines -- from Harvard Business School to the John F. Kennedy School of Government to the Harvard Graduate School of Design -- and hear from experts in leading industries around the globe. Benefit from this wide ranging expertise, studying topics from different points of view and with different categories of emphasis.
Get Started With These Courses
Data Science Principles
Data Science Principles: prepares you to speak the language of data science and contribute to data-oriented discussions within your company and daily life. This isn’t a course for data scientists—it’s for everyone around them.
Learn from experts at industry-leading organizations such as the Center for Disease Control, the University of Pennsylvania, Google, the City of Somerville, MA, Burning Glass, the ACLU, the Boston Police Department, and more.
- Understand the modern data science landscape and learn the vocabulary needed to contribute to data-oriented discussions. Learn about predictions, causality, privacy, alternative data sources, data ecosystems, and big data areas.
- At the end of the course, you should be able to recognize major concepts and tools in the field of data science and determine where they can be appropriately applied.
- Learn from real-world experts and review case studies ranging from health care, to marketing, to government.
Data Science for Business
Data Science for Business: encourages managers and individual contributors to lean into what you know already about business. Use data science to hone your decision-making skills and create actionable recommendations by identifying and avoiding common mistakes while interpreting datasets, metrics, and visualizations.
Learn from experts at industry-leading organizations such as Carvana, Fannie Mae, Uber, Pluralsight, Vispera, and Twitter.
- Recognize business challenges in your organization that can be solved by using data-science—as a manager and decision-maker—to form hypotheses, design models, interpret results, and formulate actionable recommendations.
- Gain a foundational understanding of the basics of coding environments, such as R, and visualization tools to lead your team’s data inquiries.
- Understand widely applicable methodologies in statistics, data analytics, and data science, along with the basic skills to apply them.
Big Data for Social Good
Big Data for Social Good: shows how we can make progress on economic and social problems, such as income inequality, racial disparity, and access to education, using the tools of modern applied economics. No prior background in economics or statistics is required, but students will learn how to use statistical tools such as regression analysis and quasi-experimental methods as well as economic concepts such as incentive effects and equilibrium to analyze these and other critical problems that impact everyone’s lives.
- Teach key statistical methods used in modern social science research, such as linear regressions, randomization, and regression discontinuity design.
- Show that upward mobility is declining in the United States and elsewhere, and give students a sense of the kinds of policies that might revive upward mobility.
- Analyze the influence of various factors on upward mobility such as geography, policies, education, and racial disparities.
From Past Learners
“Data Science Principles applies to many aspects of our daily lives. The course helps guide people in everyday life through decision making and process thinking.”
- Jared B., Senior Director of Sales
“I found value in the real-world examples in Data Science Principles. With complicated topics and new terms, it's especially beneficial for learnings to be able to tie back new or abstract concepts to ideas that we understand. This course helped me understand data in this context and what algorithms are actually trying to solve.”
- Alejandro D., Financial Services Analyst
Organizations of all sizes can benefit from a partnership with these courses. Our partners at HBS Online can work with you to create a solution that fits your business’ learning and development needs.
Additional Course Topics in Development
Data Privacy and Technology
Data Privacy and Technology: think critically about privacy tradeoffs and the thorny societal problems spawned by historical changes in technology over time. In addition to helping learners avoid common privacy pitfalls, the course aims to help them become more informed citizens and members of privacy-forward communities, corporations, and governments.
- Think critically about privacy issues at the intersection of policy and technology and how privacy decisions are often differential in nature.
- Understand various definitions of privacy and the long conflict between privacy norms and technological advancement.
- Compare policy approaches to privacy and how they affect the collection, usage, and resale of data.
- Analyze challenges related to the anonymization of data and the tradeoffs for common techniques.
- Analyze the different ways value is applied, or is not applied, to privacy.
- Explore the potential impact of emerging technologies on the future of privacy.
Digital Strategy: demonstrates the importance of customer, product, and functional connections and how they create value. Participants will explore these connections through case studies featuring a variety of firms who have undergone successful digital transformation. Firms must learn to take advantage of network effects, handle both complements and competitors, and build business and operation models based on their own and their customers’ unique context.
- Understand why and how competing in a digital arena is different from traditional competition.
- Understand what it means to be truly customer-centric in a digital world.
- Recognize the scope and potential for new business models in the digital arena.
- Recognize and appreciate the barriers to effective digital change, the key success drivers, and how to overcome barriers.
- Understand some of the myths around digital success.
- Appreciate what contributes to business success and failure.
- Apply the learnings from this course to your own roles and businesses.
Open Innovation: will teach a foundational understanding of crowdsourcing. Crowdsourcing is a strategy that uncovers and connects problem holders to problem solvers regardless of employment status and location. Crowdsourcing results in external and unaffiliated actors solving a particular problem with higher-value results than an organization that has relied solely on internal resources could. Once participants have a solid foundation, they will dig deeper and explore the Who, What, When, Why, and How questions associated with contests, collaborative communities, and gig platforms/labor markets.
- Explain how and why crowdsourcing works.
- Analyze the types of problems that can be solved when using crowdsourcing (problem formulation).
- Identify and understand potential management challenges, e.g., intellectual property, budget, solution adoption, etc.
- Match your problem to the right approach: contests, collaborative communities, and gig platforms / labor markets.
- Describe how to use a contest, community, or gig platform/labor market effectively.
- Integrate a crowd-generated solution into your organization
Digital Health: provides a framework to think strategically about digital transformation in health care in the context of its complex ecosystem and culture. While digital tools hold great promise, their adoption has been hampered by several underappreciated challenges unique to health care that will be explored throughout the course. Through a deepened appreciation for both the capabilities of the technologies and health-care-specific challenges, learners will be better prepared to develop or implement digital innovations that create value and improve health care delivery.
- Understand how digital tools can address critical pain points in health care.
- Gain sophistication in thinking about novel applications of data to health care and the privacy and analytic pitfalls unique to health care data.
- Understand the opportunities and cautions of key digital approaches such as AI, apps and sensors.
- Recognize emerging business models for digital innovations in health care.
- Navigate the often conflicting needs of health care stakeholders in order to bring a digital innovation to market.
Digital Cities: offers different lenses through which to view how urbanization can be understood, facilitated, orchestrated and organized in a human centric and equitable way while leveraging cutting edge urban technologies and governance systems.
- Define what a smart city is.
- Understand the role of technology in the life of a city.
- Apply the lenses of ecologies and contexts to better understand how to leverage digital technologies.
- Analyze the role of data in determining and implementing smart city strategies.
- Understand the stakeholders involved in the work of smart cities and how they collaborate.
- Reflect on future challenges faced by cities and your own contexts and agency.