Innovation Timeline

This timeline is dedicated to Innovations in the MBA Curriculum. Throughout the year we make additions including courses offered for the first time, new approaches to pedagogy, new MBA majors, and we highlight faculty that are awarded our Teaching Commitment and Curricular Innovation Award.
Stephan Dieckmann – Deputy Vice Dean of Academic Affairs

New Course Offerings - Spring 2017

OIDD 612: Business Analytics (Flipped Format)

OIDD 612: Business Analytics (Flipped Format)

Recent years have witnessed a revolution in how data and analytics are used for informing (better) business decisions. Armed with massive data and easy access to vast computational resources, firms across virtually every industry are now seeking quantitative solutions to inform their actions. How should a coffee chain decide its sourcing and roasting strategy? How should an ad platform decide which ads to display where and when? How should a doctor or policy maker recommend a balanced diet that matches a patient’s tastes and is not too costly? How should an airline price its tickets and manage its limited capacity? How should an investor decide whether (and how much) capital to inject in a limited number or risky projects? How should a hospital schedule its limited resources to balance the efficiency and workload of the staff? How should a supermarket chain decide where to open new stores, and whether to operate an online store? How should a retailer mark down its merchandise during a clearance sale?

If you ever wondered how you could even start answering such questions in a quantitative way, then this is the right course for you! The main objective of OIDD 612 is to provide basic skills in quantitative modeling, by familiarizing students with the critical steps in an analytical approach to decision-making:

  1. constructing a model that can be used to address a particular important question,
  2. implementing the model in software, and
  3. using various tools, such as optimization, Monte Carlo simulation, sensitivity analysis or Decision Trees to generate and interpret recommendations.

The philosophy is to master these topics through a hands-on approach. The class is taught in a flipped format, with classroom time primarily devoted to exercises done in small teams, and focusing on a variety of applications drawn from advertising, healthcare, finance, supply chain management, revenue and yield optimization. The instructional medium used is Excel, with appropriate packages for optimization (Solver) and simulation (Oracle Crystal Ball).

OIDD 636 - Scaling Operations: Linking Strategy and Execution

OIDD 636 – Scaling Operations: Linking Strategy and Execution

This course helps students learn to make strategic scaling decisions that are grounded in operational reality. Students will study how to build and evaluate the “operation systems” of the firm to maximize value with the focus on scaling the firm’s operations. This involves tailoring the firm’s operational competencies, assets, and processes to a specific business strategy. The course will approach the challenge of scaling operations and operations strategy by taking a holistic view that incorporates competitive strategy, financial evaluation, and the customer experience.

Recommended Prerequisites: OIDD 611, OIDD 612, STAT 613 or those who have a solid understanding of elementary probability and statistics.

OIDD 642 - Analytics for Services

OIDD 642 – Analytics for Services

This course covers a range of analytical methods that are useful tools for capacity management in services, and it will provide you with insights into the economics of a range of services businesses including (i) High-level planning models that account for multiple dimensions of service capacity, (ii) Low-level models of system congestion that capture the relationship between capacity choices, quality of service and, in some cases, system revenue, (iii) Statistical estimation and forecasting models to characterize key measures of future supply and demand.

Students who have already taken OIDD 611, OIDD 612, and STAT 613 should be well-equipped for the class. Other students should have a solid understanding of elementary probability, statistics and linear programming.  For questions regarding the specifics of your background, please contact the instructor.

Requirements: Class participation, case write-ups, online quizzes, self-study exercises and a final exam.

OIDD 643 - Analytics for Revenue Management

OIDD 643 – Analytics for Revenue Management

This course introduces you to the essential concepts and techniques required to understand and implement revenue management (RM). The need for repeated, rapid and cycles of estimation and optimization has driven the development of a set of analytical tools that are particularly well suited for RM.  This course focuses on those tools.

Students who have already taken OPIM 612 and STAT 613 should be well equipped for this class. Other students should have a solid understanding of elementary probability, statistics and constrained optimization. For questions regarding the specifics of your background, please contact the instructor.

Requirements: Class participation, case write-ups, online quizzes, self-study exercises and a final exam.

FNCE 887 – Shareholder Activism

FNCE 887 – Shareholder Activism

The aim of the course is to provide an introduction to shareholder activism. The course makes use of lectures and case studies.  The lectures expose the students to the institutional and empirical facts as well as approaches followed by leading shareholder activists. The case studies are designed to provide students an experience on identifying potential opportunity for value creation through active engagement. Assignments require students to develop/practice skills on fundamental analysis.

MGMT 765 - Venture Capital and Entrepreneurial Management: Practices and Institutions of Silicon Valley (MEETS IN SAN FRANCISCO DURING SPRING BREAK FROM 3/4/17-3/12-17)

MGMT 765 – Venture Capital and Entrepreneurial Management: Practices and Institutions of Silicon Valley (MEETS IN SAN FRANCISCO DURING SPRING BREAK FROM 3/4/17-3/12-17)

This elective half-CU course will highlight venture capital and entrepreneurship in general and will explore selected aspects of this industry, including: industry trends and dynamics in Silicon Valley and the South of Market area (SOMA) of San Francisco; the recent emergence of alternative sources of startup financing, including incubators/accelerators and crowdfunding crowdfunding platforms, angel groups and stage-agnostic institutional investors; business and operational aspects of early stage companies in transition to mezzanine-level stages of growth; and company “exits,” including both initial public offerings and merger/sale transactions.

Format: Daily lectures along with site visits to technology companies, VC firms, incubators/accelerators, and debriefing presentations led by student teams.

Requirements: Individual participation in lectures, discussions, and company visits, student presentations, and final paper.

Prerequisites: MGMT 801 recommended

MKTG 851 Special Topics: Introduction to Brain Science for Business

MKTG 851 Special Topics: Introduction to Brain Science for Business

Can brain science help business? At first blush, this might seem like a bridge too far. After all, the efficiencies of the market virtually guarantee accurate asset pricing, marketing research and focus groups can test the efficacy of advertising, effective leadership can stimulate innovation and productivity, and sophisticated analytics can leverage big data to improve organizational structure to maximize return on investment. A deeper look, however, provokes the idea that brain science has enormous potential to inform business. We now know the basic architecture of the decision process in the human brain, from identification of choice options, to the calculation of their utility, to selecting one for consumption, and learning from this experience. We are also beginning to understand how fundamental economic principles like risk, ambiguity, and volatility shape these processes, and why these factors seem to influence different people in different ways and in different choice contexts. Importantly, neuroscience provides a powerful tool for understanding the private reasons, such as emotional responses or the influence of others, people make the choices they do—reasons they themselves may not be aware of or even understand. Brain science offers the potential to unlock the mechanisms underlying what many people consider to be the keys to the future of business, including creativity and innovation, empathy and connecting with others, social awareness and the common good, how people use information to guide decision making, and the experience and impact of online vs. live interaction and pedagogy. New developments, including biometrics, implantable and wearable brain interfaces, genomics, proteomics, metabolomics, and the human microbiome, offer the opportunity for enhanced precision not only in marketing and finance, but also in the talent identification and the development of full human potential.

This course will provide an overview of contemporary brain science and its applications to business. Students first will be introduced to the basic anatomy and physiology of the brain and become familiar with important techniques for measuring brain function. The course will then survey major findings in neuroscience with applications to business, including selective attention and advertising; valuation and marketing; decision making and the tyranny of choice; learning, innovation and creativity; and social influence, team-building, and leadership. The course will end with a discussion of ethics, brain-machine interactions, and artificial intelligence.

Prerequisites: None

Format: The first half of each class will be an interactive lecture, followed by presentation and discussion of team projects applying principles and techniques from brain science to business.

Teaching and Curricular Innovation Awards 2016

Peter Fader

Peter Fader for WHOOPPEE
Frances and Pei-Yuan Chia Professor, Marketing

“The technological innovation that they have recently created in coordination with Wharton Computing, the Wharton Online
Ordinal Peer Performance Evaluation Engine (” WHOOPPEE“), is exceptional and has the potential to be a
valuable asset for the school as a whole.” 

Corinne Low

Corinne Low for Microeconomics for Managers
Assistant Professor of Business Economics and Public Policy

“Professor Low is exceptional. This isn’t because of her brilliance or extraordinary accomplishments; I’m lucky enough to go to a school where more of my professors are similar in that regard than not. It’s because she cares about teaching in its truest sense: helping her students evolve and change the world, well beyond the province of managerial economics.” 

Arthur van Benthem

Arthur van Benthem for Energy Markets and Policy
Assistant Professor of Business Economics and Public Policy

“BEPP/OIDD 763 features innovative and extensive strategy simulations, includes truly international content, and -perhaps most importantly -provides many bridges to the “real world.”

Senthil Veeraraghavan

Senthil Veeraraghavan for Operations Strategy
Associate Professor, Operations, Information and Decisions

“Senthil teaches OIDD615, Operations Strategy. In this Spring semester he introduced three new technologies to enhance the student learning experience. All three technologies are designed to encourage broader and deeper student preparation and participation.”

New Course Offerings - Fall 2016

Fin Tech

Fin Tech

FNCE 885, taught by Prof. Kogan.

Big Data, Big Responsibilities: The Law and Ethics of Business Analytics

Big Data, Big Responsibilities: The Law and Ethics of Business Analytics

LGST 642, taught by Prof. Werbach.

Internship Term Paper

We have some exciting news for our international students. We are offering the course Internship Term Paper, WHCP 891, as a pilot. The course has been developed for international students who are about to enter their second year, and who will be doing a summer internship in the United States. WHCP 891 offers you an opportunity to reflect on some of the knowledge you acquired during your first year at Wharton applied in a business setting. You can take this course in support of your curricular practical training.


Entrepreneurship, MGMT 801, will be offered in two versions this Fall, and for the first time as a simulation version. Just as in the standard MGMT 801 class, your final team project will involve developing a pitch for a new business, but you will be playing the award-winning Looking Glass entrepreneurship simulation rather than doing individual reaction papers.  The Looking Glass simulation is an intense and fun 3-week simulation that is played outside of class and gives you the chance to experience what running a startup company is like.

Big Data, Big Responsibilities: The Law and Ethics of Business Analytics

Big Data, Big Responsibilities: The Law and Ethics of Business Analytics, taught by Prof. Werbach

Significant technologies always have unintended consequences, and their effects are never neutral. A world of ubiquitous data, subject to ever more sophisticated collection, aggregation, and analysis, creates massive opportunities for both financial gain and social good. It also creates dangers in areas such as privacy, security, discrimination, exploitation, and inequality, as well as simple hubris about the effectiveness of management by algorithm. Firms that anticipate the risks of these new practices will be best positioned to avoid missteps. This course introduces students to the legal, policy, and ethical dimensions of big data, predictive analytics, and related techniques. It then examines responses—both private and governmental—that may be employed to address these concerns.

Fin Tech

Fin Tech, taught by Prof. Kogan 

The course exposes students to the fast-growing and exciting intersection between finance (“Fin”) and technology (“Tech”) while emphasizing the role data and analytics play. The course is structured around three main FinTech areas: (i) Lending/Banking services, (ii) Clearing and (iii) Trading.  It provides specific coverage and examples of developments from (1) peer-to-peer lending, (2) blockchain and distributed ledgers, (3) networks and their use in trading, (4) algo trading and its use of non-standard data inputs. In each of these areas, we start by analyzing the marketplace and the incumbents and then study the business case and strategies of the incoming technology players, while understanding the role data and analytics play in driving the technology-based services. The course is built around a large number of examples and cases, guest lectures, student presentations, and group projects. Students are thus expected to work in teams and demonstrate a high level of independent learning and initiative.

New MBA Major - Business Analytics

Analytical judgment is a value embodied throughout our MBA curriculum. We continue to leverage our analytical DNA and introduce a new major – Business Analytics.

The Business Analytics major is designed to build deep competency in the skills needed to implement and oversee data-driven business decisions, including (i) collecting, managing and describing datasets, (ii) forming inferences and predictions from data and (iii) making optimal and robust decisions. Business analytics makes extensive use of statistical analysis and the applications of business analytics span many functional areas.

Students choosing the Business Analytics major are ideally suited for the growing set of careers broadly defined under the header of “data science” with responsibilities for managing and analyzing data. In addition, the major provides an excellent complement to students who choose to focus on one of the functional areas of business (such as accounting, finance, marketing, operations).

The course requirements for the major are listed below.  Business Analytics has the designated CIP code 52.1301. Please contact your academic adviser if you have questions.

BEPP780 Applied Data Analysis and Causality for Business and Public Policy

LGST642 Big Data, Big Responsibilities: The Law and Ethics of Business Analytics*

MKTG669 Experiments for Business Decision Making

MKTG712 Data and Analysis for Marketing Decisions

MKTG771 Models for Marketing Strategy*

MKTG776 Applied Probability Models in Marketing

OIDD642 Analytics for Services

OIDD643 Analytics for Revenue Management

OIDD653 Mathematical Modeling and its Application in Finance

OIDD658 Service Operations Management

OIDD672 Decision Support Systems

STAT701 Modern Data Mining*

STAT705 Statistical Programming with R*

STAT711 Forecasting Methods for Management*

STAT722 Predictive Analytics for Business*

STAT770 Data Analytics and Statistical Computing*

*offered Fall 2016