Three Harvard Schools. One Innovative Curriculum.

Designed by Top Minds in AI and Data Analytics

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The rigorous curriculum consists of entirely new courses, designed by Harvard faculty, that will help you build your capabilities in technical, analytical, and operational areas that can be used to advance your firm’s position in the global market. As a student you will:

  • sharpen your core data analysis and management skills;
  • explore emerging technologies and practices in next-generation analytics, such as blockchain, digital strategy, and AI/ML; and
  • learn how to interpret your findings and use them to uncover valuable business insights.

Our faculty will guide you in applying these concepts to your organization, with a mind toward maximizing efficiencies and outcomes.

Sample Course Structure

The Harvard Business Analytics Program consists of six core courses, two seminars, and two in-person immersions. The program can be completed in as little as nine months.

Standard 9-Month Program Structure






Term 3 (8 weeks)

Term 3 Immersion (3 days)

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Course Descriptions

Digital Strategy and Innovation

Taught by Marco Iansiti, Karim Lakhani, Antonio Moreno, and Feng Zhu

The broad digitization of the global economy is resulting in enormous stores of varied data being generated and collected. Competitive advantage in the 21st century is accruing to companies that are able to make data-driven analytics and decision-making a core part of their growth strategy, their business development endeavors, and all aspects of their operations. Large companies like Google, General Electric, Alibaba, and Baidu have embraced data analytics as a core aspect of their product and operations strategy, and multitudes of startups are emerging to disrupt existing players through the clever leveraging of big data. Through global case studies on market leaders and innovative startups in diverse industries, Professors Iansiti and Lakhani will examine the strategies and operational changes needed to make data analytics integral to your future success.

Foundations of Quantitative Analysis

Taught by Mark Glickman, Mike Parzen and Kevin Rader

This course is an introduction to using statistical approaches to solve business problems. It introduces statistical concepts via a management perspective and places special emphasis on developing the skills and instincts needed to make sound decisions and become an effective manager. The main components of the course include methods for describing and summarizing data, the fundamentals of probability, the basics of study design and data collection, and statistical inference. Data analyses, simulation, and design issues are implemented in the statistical computing package R run within the RStudio interface.

Leadership, Innovation, and Change

Taught by Michael Tushman and Rory McDonald

An emphasis on data analytics and algorithms at the center of an enterprise also means that leaders will have to drive both innovation and large-scale organizational change. This course will focus on the leader’s role in both executing their current strategy better than their competitors as well as their role in shaping strategic innovation. We employ the congruence model that links strategy to execution through alignment of culture, people, tasks, structure, and executive leadership. We also explore the inertial characteristics of aligned organizations and the strategic importance of driving innovation streams. We explore building ambidextrous organizations, organizations that can both exploit their existing strategy as well as explore into new strategic domains. Because ambidexterity requires leaders that can deal with punctuated change and paradoxical strategies, our course concludes with what we know about ambidextrous leadership and leading large system change.

*You must complete Digital Strategy and Innovation before you take this course.

Operations and Supply Chain Management

Taught by Ryan Buell, Dennis Campbell, Kris Ferreira, Jan Hammond, and VG Narayanan

Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product proliferation, short product life cycles, and global networks of suppliers and customers. Topics examined include inventory management, distribution economics, demand forecasting, and supplier management. The course emphasizes the “general manager’s perspective” in supply chains. Cases in the course illustrate that barriers to integrating supply chains often relate to behavioral issues (e.g., misaligned incentives or change management challenges) and operational execution problems that fall squarely in the domain of the general manager.

*You must complete Foundations of Quantitative Analysis before you take this course.

Programming and Data Science Systems

Taught by Henry Leitner and David Malan

Modern business analytics requires executives and managers to be conversant with programming and data architecture. The aim of this course is to provide participants with the fundamental knowledge and practice needed to appreciate the challenges and opportunities related to developing robust and scalable systems that are at the core of business analytics by emphasizing mastery of high-level concepts and design decisions. Through a mix of technical instruction, discussion of case studies, and weekly programming projects, this course empowers participants to make technological decisions even if not technologists themselves. Topics include cloud computing, networking, privacy, scalability, security, and more, with a particular emphasis on web and mobile technologies. Participants emerge from this course with first-hand appreciation of how it all works and all the more confident in the factors that should guide their decision-making.

Leadership and People Analytics

Taught by Jeff Polzer

People Analytics is designed to help practitioners use data to improve people-related decisions. Participants will build hands-on skills to analyze data in ways that complement the frameworks and intuitions they would normally use to guide their managerial actions on people issues. At a deeper level, students in any job, organization, or industry context will sharpen their ability to think critically through the lens of rigorous analytics. Anchored in data, this course will equip participants with an analytic approach to diagnosing the varied forces that influence individual, team, and organizational performance, leading to more effective interventions and actions. While developing analytic skills and trying out tools and techniques, participants will come to appreciate the opportunities, limits, and tensions involved in using data analytics to inform people issues, while simultaneously gaining deeper insight into the substance of the business issues in question.

*You must complete Foundations of Quantitative Analysis, and Leadership, Innovation, and Change before you take this course.

Data-Driven Marketing

Taught by Sunil Gupta, Ayelet Israeli and David Parkes

Marketing has been revolutionized and forever changed by data analytics. What used to be a qualitative and instinct-driven business function (think “Mad Men”) has now become a data-driven profession that relies on quantitative insights on how best to optimize ad creation and placement and influence consumer purchase behavior. This course will examine the ways in which marketing has changed and the new skills and capabilities needed to succeed in this function.

*You must complete Digital Strategy and Innovation, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

Data Science Pipeline and Critical Thinking

Taught by Joe Blitzstein, Iavor Bojinov, Srikant Datar, and Hanspeter Pfister

Ultimately, business analytics is about using data, analytics, and algorithms to make prescriptive predictions about future events and decisions. This course will take a holistic approach to helping participants understand the key factors involved, from data collection to analysis to prediction and insight. Projects will give students hands-on experience developing and running a data science pipeline to ensure that the correct business predictions are being made. Emphasis will be on merging technical skills with critical thinking to ensure that robust data science pipelines are being created for business benefit.

*You must complete Digital Strategy and Innovation, Operations and Supply Chain Management, Programming and Data Science Systems, and Foundations of Quantitative Analysis before you take this course.

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Learning Outcomes

Upon completion of the Harvard Business Analytics Program, you will be prepared to:

  • speak the language of data scientists;
  • leverage data and analytics to drive strategy and innovation across the firm;
  • gain competitive advantages in a data-centric world;
  • use data to clarify ambiguity and take advantage of economic opportunities;
  • apply data-driven strategies to effectively lead organizational change and inform managerial practices;
  • use data for predictive decision-making; and
  • understand basic programming, data architecture, and quantitative analysis.

The Harvard Business Analytics Program was instrumental in providing the knowledge, skills, and tools necessary to transition my academic background to an applied business analytics career. I believe the single most important attribute of the program is that it offers business analytics training from three separate schools.

Liette Ocker, Owner, Principal Consultant at Ocker Consulting, LLC

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Achieve better business strategy by becoming a data-driven leader. Request information about the online Harvard business analytics program.